Decoder | Papers With Code

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Often used in sequence-to-sequence models, the decoder takes hidden states or contextual embeddings produced by an encoder and generates output sequences step-by-step, crucial for tasks like machine translation, text generation, and summarization." />  <meta property="og:title" content="Papers with Code - Decoder"> <meta property="og:description" content="Model components that transform encoded representations of input data into human-readable outputs, such as text or speech. 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Often used in sequence-to-sequence models, the decoder takes hidden states or contextual embeddings produced by an encoder and generates output sequences step-by-step, crucial for tasks like machine translation, text generation, and summarization.</textarea> </div> </div> <div id="div_id_image" class="form-group"> <label for="id_image" class=""> Image </label> <div class=""> <input type="file" name="image" accept="image/*" class="clearablefileinput form-control-file" id="id_image"> </div> </div> <div class="modal-footer"> <button type="submit" class="btn btn-primary"> Submit </button> </div> </form> </div> </div> </div> </div>  <div class="modal fade" id="addRow" role="dialog" aria-labelledby="addRowLabel" aria-hidden="true"> <div class="modal-dialog" role="document"> <div class="modal-content"> <div class="modal-header"> <h5 class="modal-title" id="addRowLabel">Add a new evaluation result row</h5> <button type="button" class="close btn-close" data-bs-dismiss="modal" 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48v256zm-320-208c0-26.51-21.49-48-48-48s-48 21.49-48 48 21.49 48 48 48 48-21.49 48-48zm-96 144v48h352v-112l-87.514-87.514c-4.687-4.687-12.285-4.687-16.971 0L272 257.999l-39.514-39.515c-4.688-4.686-12.285-4.686-16.972 0z"/></svg></span> <span>Time Series</span> </span> </a> </div> <div class="artefact-header"> <div class="float-right task-edit"> <div class="dropdown edit-button"> <a data-bs-toggle="modal" data-bs-target="#loginModal"> <span class="badge badge-method-edit" style="padding-top:10px;"><span class=" icon-wrapper icon-fa icon-fa-solid" data-name="edit"><svg viewBox="0 0 576 514.999" xmlns="http://www.w3.org/2000/svg"><path d="M402.6 85.198l90.2 90.2c3.8 3.8 3.8 10 0 13.8l-218.399 218.4-92.8 10.3c-12.4 1.4-22.9-9.1-21.5-21.5l10.3-92.8 218.4-218.4c3.799-3.8 10-3.8 13.799 0zm162-22.9c15.2 15.2 15.2 39.9 0 55.2l-35.4 35.4c-3.8 3.8-10 3.8-13.8 0l-90.2-90.2c-3.8-3.8-3.8-10 0-13.8l35.4-35.4c15.3-15.2 40-15.2 55.2 0zM384 348.198c0-3.2 1.3-6.2 3.5-8.5l40-40c7.6-7.5 20.5-2.2 20.5 8.5v157.8c0 26.5-21.5 48-48 48H48c-26.5 0-48-21.5-48-48v-352c0-26.5 21.5-48 48-48h285.8c10.7 0 16.1 12.9 8.5 20.5l-40 40c-2.3 2.2-5.3 3.5-8.5 3.5H64v320h320v-101.8z"/></svg></span> Edit</span> </a> </div> </div> <h1 id="task-home">Decoder</h1> <div class="artefact-information"> <p> 4004 papers with code • 0 benchmarks • 0 datasets </p> </div> </div> <div class="col-lg-10">  <div class="description"> <div class="description-content"> <p>Model components that transform encoded representations of input data into human-readable outputs, such as text or speech. Often used in sequence-to-sequence models, the decoder takes hidden states or contextual embeddings produced by an encoder and generates output sequences step-by-step, crucial for tasks like machine translation, text generation, and summarization.</p> </div> </div>   <div class="task-benchmarks"> <div id="benchmarks" class="collapsed"> <div class="title"> <h2 id="benchmarks">Benchmarks <div class="float-right"> <div class="dropdown edit-button task-add-a-result"> <a data-bs-toggle="modal" data-bs-target="#loginModal"> <span class="badge badge-primary" style="font-size:12px;"> Add a Result</span> </a> </div> </div> </h2> These leaderboards are used to track progress in Decoder <hr> </div> <div class="sota-no-sota"> No evaluation results yet. Help compare methods by <a data-bs-toggle="modal" data-bs-target="#loginModal">submitting evaluation metrics</a>. </div> </div> </div>  <div class="task-started"> <div class="title task-libraries"> <h2 id="task-libraries">Libraries <span class="lib-info" data-bs-toggle="popover" data-bs-placement="top" data-bs-trigger="hover" data-bs-title="Libraries" data-bs-content="These libraries are updated daily, based on the papers assigned to this task. If you think a Library is missing, make sure this library is added as code to the papers it implements, and that the papers have been assigned to this task." ><span class=" icon-wrapper icon-ion" data-name="information-circle-outline"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M248 64C146.39 64 64 146.39 64 248s82.39 184 184 184 184-82.39 184-184S349.61 64 248 64z" fill="none" stroke="#000" stroke-miterlimit="10" stroke-width="32"/><path fill="none" stroke="#000" stroke-linecap="round" stroke-linejoin="round" stroke-width="32" d="M220 220h32v116"/><path fill="none" stroke="#000" stroke-linecap="round" stroke-miterlimit="10" stroke-width="32" d="M208 340h88"/><path d="M248 130a26 26 0 1 0 26 26 26 26 0 0 0-26-26z"/></svg></span></span> </h2> Use these libraries to find Decoder models and implementations <hr> <div id="libraries-short-list"> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/huggingface/transformers" onclick="captureOutboundLink('https://github.com/huggingface/transformers'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> huggingface/transformers </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 16 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 135,512 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/PaddlePaddle/PaddleSeg" onclick="captureOutboundLink('https://github.com/PaddlePaddle/PaddleSeg'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> PaddlePaddle/PaddleSeg </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 12 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 8,417 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/awslabs/sockeye" onclick="captureOutboundLink('https://github.com/awslabs/sockeye'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> awslabs/sockeye </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 9 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 1,212 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/zh320/realtime-semantic-segmentation-pytorch" onclick="captureOutboundLink('https://github.com/zh320/realtime-semantic-segmentation-pytorch'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> zh320/realtime-semantic-segmentatio… </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 9 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 133 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="table-options"> <a href="#" id="libraries-see-more-trigger">See all 21</a> libraries. </div> </div> <div id="libraries-full-list" style="display:none"> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/huggingface/transformers" onclick="captureOutboundLink('https://github.com/huggingface/transformers'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> huggingface/transformers </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 16 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 135,512 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/PaddlePaddle/PaddleSeg" onclick="captureOutboundLink('https://github.com/PaddlePaddle/PaddleSeg'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> PaddlePaddle/PaddleSeg </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 12 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 8,417 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/awslabs/sockeye" onclick="captureOutboundLink('https://github.com/awslabs/sockeye'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> awslabs/sockeye </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 9 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 1,212 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/zh320/realtime-semantic-segmentation-pytorch" onclick="captureOutboundLink('https://github.com/zh320/realtime-semantic-segmentation-pytorch'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> zh320/realtime-semantic-segmentatio… </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 9 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 133 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/PaddlePaddle/PaddleOCR" onclick="captureOutboundLink('https://github.com/PaddlePaddle/PaddleOCR'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> PaddlePaddle/PaddleOCR </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 8 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 44,511 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/PaddlePaddle/PaddleSpeech" onclick="captureOutboundLink('https://github.com/PaddlePaddle/PaddleSpeech'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> PaddlePaddle/PaddleSpeech </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 7 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 11,194 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/osmr/imgclsmob" onclick="captureOutboundLink('https://github.com/osmr/imgclsmob'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> osmr/imgclsmob </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 7 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 2,977 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/bzhangGo/zero" onclick="captureOutboundLink('https://github.com/bzhangGo/zero'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> bzhangGo/zero </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 7 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 149 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/Deci-AI/super-gradients" onclick="captureOutboundLink('https://github.com/Deci-AI/super-gradients'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> Deci-AI/super-gradients </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 6 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 4,601 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/clementchadebec/benchmark_VAE" onclick="captureOutboundLink('https://github.com/clementchadebec/benchmark_VAE'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> clementchadebec/benchmark_VAE </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 6 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 1,826 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/google-research/big_vision" onclick="captureOutboundLink('https://github.com/google-research/big_vision'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> google-research/big_vision </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 5 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 2,358 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/sooftware/OpenSpeech" onclick="captureOutboundLink('https://github.com/sooftware/OpenSpeech'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> sooftware/OpenSpeech </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 5 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 34 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/open-mmlab/mmdetection" onclick="captureOutboundLink('https://github.com/open-mmlab/mmdetection'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> open-mmlab/mmdetection </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 4 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 29,679 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/tensorflow/tensor2tensor" onclick="captureOutboundLink('https://github.com/tensorflow/tensor2tensor'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> tensorflow/tensor2tensor </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 4 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 15,581 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/PaddlePaddle/PaddleDetection" onclick="captureOutboundLink('https://github.com/PaddlePaddle/PaddleDetection'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> PaddlePaddle/PaddleDetection </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 4 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 12,850 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/facebookresearch/multimodal" onclick="captureOutboundLink('https://github.com/facebookresearch/multimodal'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> facebookresearch/multimodal </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 4 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 1,482 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/microsoft/speecht5" onclick="captureOutboundLink('https://github.com/microsoft/speecht5'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> microsoft/speecht5 </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 4 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 1,218 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/Alexander-H-Liu/End-to-end-ASR-Pytorch" onclick="captureOutboundLink('https://github.com/Alexander-H-Liu/End-to-end-ASR-Pytorch'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> Alexander-H-Liu/End-to-end-ASR-Pyto… </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 4 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 1,190 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/WenjieDu/PyPOTS" onclick="captureOutboundLink('https://github.com/WenjieDu/PyPOTS'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> WenjieDu/PyPOTS </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 4 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 1,118 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/thumt/THUMT" onclick="captureOutboundLink('https://github.com/thumt/THUMT'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> thumt/THUMT </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 4 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 706 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> </div> </div> </div> <div class="row task-library"> <div class="col-12 col-md-6"> <a href="https://github.com/theamrzaki/text_summurization_abstractive_methods" onclick="captureOutboundLink('https://github.com/theamrzaki/text_summurization_abstractive_methods'); return true;"> <div class="library-logo"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> </div> theamrzaki/text_summurization_abstr… </a> </div> <div class="col-6 col-md-3"> <span class="task-library-pwc-count"> 4 papers </span> </div> <div class="col-6 col-md-3"> <div class="library-stars text-nowrap"> 527 <span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 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class="item-image" style="background-image: url('https://production-media.paperswithcode.com/social-images/oVEwwksZyfDziYzq.png');"> </div> </a> </div> <div class="col-lg-9"> <div class="row"> <div class="col-lg-9 item-content"> <h1><a href="/paper/attention-is-all-you-need">Attention Is All You Need</a></h1> <p class="author-section" style="padding-top:2px"> <span class="item-github-link"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> <a href="https://github.com/tensorflow/tensor2tensor" onclick="captureOutboundLink('https://github.com/tensorflow/tensor2tensor'); return true;" style="font-size:13px"> tensorflow/tensor2tensor </a> </span> • <span class="item-framework-link"> <img class="" src="data:image/png;base64,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" /> </span> • <span class="item-conference-link"> <a href="/conference/neurips-2017-12"> NeurIPS 2017 </a> </span> </p> <p class="item-strip-abstract">The dominant sequence transduction models are based on complex recurrent or convolutional neural networks in an encoder-decoder configuration.</p> </div> <div class="col-lg-3 item-interact text-center"> <div class="entity-stars"> <span class="badge badge-secondary"><span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> 575</span> </div> <div class="entity" style="margin-bottom: 20px;"> <a href="/paper/attention-is-all-you-need" class="badge badge-light "> <span class=" icon-wrapper icon-ion" data-name="document"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M428 224H288a48 48 0 0 1-48-48V36a4 4 0 0 0-4-4h-92a64 64 0 0 0-64 64v320a64 64 0 0 0 64 64h224a64 64 0 0 0 64-64V228a4 4 0 0 0-4-4z"/><path d="M419.22 188.59L275.41 44.78a2 2 0 0 0-3.41 1.41V176a16 16 0 0 0 16 16h129.81a2 2 0 0 0 1.41-3.41z"/></svg></span> Paper </a> <br/> <a href="/paper/attention-is-all-you-need#code" class="badge badge-dark "> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> Code </a> <br/> </div> </div> </div> </div> </div> </div> </div> <div class="paper-card infinite-item">  <div class="container-fluid"> <div class="row"> <div class="col-lg-3"> <a href="/paper/neural-machine-translation-by-jointly"> <div class="item-image" style="background-image: url('https://production-media.paperswithcode.com/thumbnails/paper/1409.0473.jpg');"> </div> </a> </div> <div class="col-lg-9"> <div class="row"> <div class="col-lg-9 item-content"> <h1><a href="/paper/neural-machine-translation-by-jointly">Neural Machine Translation by Jointly Learning to Align and Translate</a></h1> <p class="author-section" style="padding-top:2px"> <span class="item-github-link"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> <a href="https://github.com/graykode/nlp-tutorial" onclick="captureOutboundLink('https://github.com/graykode/nlp-tutorial'); return true;" style="font-size:13px"> graykode/nlp-tutorial </a> </span> • <span class="item-framework-link"> <img class="" src="https://production-assets.paperswithcode.com/perf/images/frameworks/pytorch-2fbf2cb9.png" /> </span> • <span class="author-name-text item-date-pub">1 Sep 2014</span> </p> <p class="item-strip-abstract">Neural machine translation is a recently proposed approach to machine translation.</p> </div> <div class="col-lg-3 item-interact text-center"> <div class="entity-stars"> <span class="badge badge-secondary"><span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> 125</span> </div> <div class="entity" style="margin-bottom: 20px;"> <a href="/paper/neural-machine-translation-by-jointly" class="badge badge-light "> <span class=" icon-wrapper icon-ion" data-name="document"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M428 224H288a48 48 0 0 1-48-48V36a4 4 0 0 0-4-4h-92a64 64 0 0 0-64 64v320a64 64 0 0 0 64 64h224a64 64 0 0 0 64-64V228a4 4 0 0 0-4-4z"/><path d="M419.22 188.59L275.41 44.78a2 2 0 0 0-3.41 1.41V176a16 16 0 0 0 16 16h129.81a2 2 0 0 0 1.41-3.41z"/></svg></span> Paper </a> <br/> <a href="/paper/neural-machine-translation-by-jointly#code" class="badge badge-dark "> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> Code </a> <br/> </div> </div> </div> </div> </div> </div> </div> <div class="paper-card infinite-item">  <div class="container-fluid"> <div class="row"> <div class="col-lg-3"> <a href="/paper/encoder-decoder-with-atrous-separable"> <div class="item-image" style="background-image: url('https://production-media.paperswithcode.com/thumbnails/paper/1802.02611.jpg');"> </div> </a> </div> <div class="col-lg-9"> <div class="row"> <div class="col-lg-9 item-content"> <h1><a href="/paper/encoder-decoder-with-atrous-separable">Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation</a></h1> <p class="author-section" style="padding-top:2px"> <span class="item-github-link"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> <a href="https://github.com/tensorflow/models" onclick="captureOutboundLink('https://github.com/tensorflow/models'); return true;" style="font-size:13px"> tensorflow/models </a> </span> • <span class="item-framework-link"> <img class="" src="data:image/png;base64,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" /> </span> • <span class="item-conference-link"> <a href="/conference/eccv-2018-9"> ECCV 2018 </a> </span> </p> <p class="item-strip-abstract">The former networks are able to encode multi-scale contextual information by probing the incoming features with filters or pooling operations at multiple rates and multiple effective fields-of-view, while the latter networks can capture sharper object boundaries by gradually recovering the spatial information.</p> </div> <div class="col-lg-3 item-interact text-center"> <div class="entity-stars"> <span class="badge badge-secondary"><span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> 78</span> </div> <div class="entity" style="margin-bottom: 20px;"> <a href="/paper/encoder-decoder-with-atrous-separable" class="badge badge-light "> <span class=" icon-wrapper icon-ion" data-name="document"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M428 224H288a48 48 0 0 1-48-48V36a4 4 0 0 0-4-4h-92a64 64 0 0 0-64 64v320a64 64 0 0 0 64 64h224a64 64 0 0 0 64-64V228a4 4 0 0 0-4-4z"/><path d="M419.22 188.59L275.41 44.78a2 2 0 0 0-3.41 1.41V176a16 16 0 0 0 16 16h129.81a2 2 0 0 0 1.41-3.41z"/></svg></span> Paper </a> <br/> <a href="/paper/encoder-decoder-with-atrous-separable#code" class="badge badge-dark "> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> Code </a> <br/> </div> </div> </div> </div> </div> </div> </div> <div class="paper-card infinite-item">  <div class="container-fluid"> <div class="row"> <div class="col-lg-3"> <a href="/paper/segnet-a-deep-convolutional-encoder-decoder"> <div class="item-image" style="background-image: url('https://production-media.paperswithcode.com/thumbnails/paper/1511.00561.jpg');"> </div> </a> </div> <div class="col-lg-9"> <div class="row"> <div class="col-lg-9 item-content"> <h1><a href="/paper/segnet-a-deep-convolutional-encoder-decoder">SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation</a></h1> <p class="author-section" style="padding-top:2px"> <span class="item-github-link"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> <a href="https://github.com/PaddlePaddle/PaddleSeg" onclick="captureOutboundLink('https://github.com/PaddlePaddle/PaddleSeg'); return true;" style="font-size:13px"> PaddlePaddle/PaddleSeg </a> </span> • <span class="item-framework-link"> <img class="" src="https://production-assets.paperswithcode.com/perf/images/frameworks/paddle-551b4bd3.png" /> </span> • <span class="author-name-text item-date-pub">2 Nov 2015</span> </p> <p class="item-strip-abstract">We show that SegNet provides good performance with competitive inference time and more efficient inference memory-wise as compared to other architectures.</p> </div> <div class="col-lg-3 item-interact text-center"> <div class="entity-stars"> <span class="badge badge-secondary"><span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> 72</span> </div> <div class="entity" style="margin-bottom: 20px;"> <a href="/paper/segnet-a-deep-convolutional-encoder-decoder" class="badge badge-light "> <span class=" icon-wrapper icon-ion" data-name="document"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M428 224H288a48 48 0 0 1-48-48V36a4 4 0 0 0-4-4h-92a64 64 0 0 0-64 64v320a64 64 0 0 0 64 64h224a64 64 0 0 0 64-64V228a4 4 0 0 0-4-4z"/><path d="M419.22 188.59L275.41 44.78a2 2 0 0 0-3.41 1.41V176a16 16 0 0 0 16 16h129.81a2 2 0 0 0 1.41-3.41z"/></svg></span> Paper </a> <br/> <a href="/paper/segnet-a-deep-convolutional-encoder-decoder#code" class="badge badge-dark "> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> Code </a> <br/> </div> </div> </div> </div> </div> </div> </div> <div class="paper-card infinite-item">  <div class="container-fluid"> <div class="row"> <div class="col-lg-3"> <a href="/paper/searching-for-mobilenetv3"> <div class="item-image" style="background-image: url('https://production-media.paperswithcode.com/thumbnails/paper/1905.02244.jpg');"> </div> </a> </div> <div class="col-lg-9"> <div class="row"> <div class="col-lg-9 item-content"> <h1><a href="/paper/searching-for-mobilenetv3">Searching for MobileNetV3</a></h1> <p class="author-section" style="padding-top:2px"> <span class="item-github-link"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> <a href="https://github.com/tensorflow/models/tree/master/research/deeplab" onclick="captureOutboundLink('https://github.com/tensorflow/models/tree/master/research/deeplab'); return true;" style="font-size:13px"> tensorflow/models </a> </span> • <span class="item-framework-link"> <img class="" src="data:image/png;base64,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" /> </span> • <span class="item-conference-link"> <a href="/conference/iccv-2019-10"> ICCV 2019 </a> </span> </p> <p class="item-strip-abstract">We achieve new state of the art results for mobile classification, detection and segmentation.</p> </div> <div class="col-lg-3 item-interact text-center"> <div class="entity-stars"> <span class="badge badge-secondary"><span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> 63</span> </div> <div class="entity" style="margin-bottom: 20px;"> <a href="/paper/searching-for-mobilenetv3" class="badge badge-light "> <span class=" icon-wrapper icon-ion" data-name="document"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M428 224H288a48 48 0 0 1-48-48V36a4 4 0 0 0-4-4h-92a64 64 0 0 0-64 64v320a64 64 0 0 0 64 64h224a64 64 0 0 0 64-64V228a4 4 0 0 0-4-4z"/><path d="M419.22 188.59L275.41 44.78a2 2 0 0 0-3.41 1.41V176a16 16 0 0 0 16 16h129.81a2 2 0 0 0 1.41-3.41z"/></svg></span> Paper </a> <br/> <a href="/paper/searching-for-mobilenetv3#code" class="badge badge-dark "> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> Code </a> <br/> </div> </div> </div> </div> </div> </div> </div> <div class="paper-card infinite-item">  <div class="container-fluid"> <div class="row"> <div class="col-lg-3"> <a href="/paper/masked-autoencoders-are-scalable-vision"> <div class="item-image" style="background-image: url('https://production-media.paperswithcode.com/thumbnails/paper/2111.06377.jpg');"> </div> </a> </div> <div class="col-lg-9"> <div class="row"> <div class="col-lg-9 item-content"> <h1><a href="/paper/masked-autoencoders-are-scalable-vision">Masked Autoencoders Are Scalable Vision Learners</a></h1> <p class="author-section" style="padding-top:2px"> <span class="item-github-link"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> <a href="https://github.com/facebookresearch/mae" onclick="captureOutboundLink('https://github.com/facebookresearch/mae'); return true;" style="font-size:13px"> facebookresearch/mae </a> </span> • <span class="item-framework-link"> <img class="" src="https://production-assets.paperswithcode.com/perf/images/frameworks/pytorch-2fbf2cb9.png" /> </span> • <span class="item-conference-link"> <a href="/conference/cvpr-2022-1"> CVPR 2022 </a> </span> </p> <p class="item-strip-abstract">Our MAE approach is simple: we mask random patches of the input image and reconstruct the missing pixels.</p> </div> <div class="col-lg-3 item-interact text-center"> <div class="entity-stars"> <span class="badge badge-secondary"><span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> 54</span> </div> <div class="entity" style="margin-bottom: 20px;"> <a href="/paper/masked-autoencoders-are-scalable-vision" class="badge badge-light "> <span class=" icon-wrapper icon-ion" data-name="document"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M428 224H288a48 48 0 0 1-48-48V36a4 4 0 0 0-4-4h-92a64 64 0 0 0-64 64v320a64 64 0 0 0 64 64h224a64 64 0 0 0 64-64V228a4 4 0 0 0-4-4z"/><path d="M419.22 188.59L275.41 44.78a2 2 0 0 0-3.41 1.41V176a16 16 0 0 0 16 16h129.81a2 2 0 0 0 1.41-3.41z"/></svg></span> Paper </a> <br/> <a href="/paper/masked-autoencoders-are-scalable-vision#code" class="badge badge-dark "> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> Code </a> <br/> </div> </div> </div> </div> </div> </div> </div> <div class="paper-card infinite-item">  <div class="container-fluid"> <div class="row"> <div class="col-lg-3"> <a href="/paper/neural-discrete-representation-learning"> <div class="item-image" style="background-image: url('https://production-media.paperswithcode.com/thumbnails/paper/1711.00937.jpg');"> </div> </a> </div> <div class="col-lg-9"> <div class="row"> <div class="col-lg-9 item-content"> <h1><a href="/paper/neural-discrete-representation-learning">Neural Discrete Representation Learning</a></h1> <p class="author-section" style="padding-top:2px"> <span class="item-github-link"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> <a href="https://github.com/deepmind/sonnet/blob/v2/sonnet/src/nets/vqvae.py" onclick="captureOutboundLink('https://github.com/deepmind/sonnet/blob/v2/sonnet/src/nets/vqvae.py'); return true;" style="font-size:13px"> deepmind/sonnet </a> </span> • <span class="item-framework-link"> <img class="" src="data:image/png;base64,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" /> </span> • <span class="item-conference-link"> <a href="/conference/neurips-2017-12"> NeurIPS 2017 </a> </span> </p> <p class="item-strip-abstract">Learning useful representations without supervision remains a key challenge in machine learning.</p> </div> <div class="col-lg-3 item-interact text-center"> <div class="entity-stars"> <span class="badge badge-secondary"><span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> 47</span> </div> <div class="entity" style="margin-bottom: 20px;"> <a href="/paper/neural-discrete-representation-learning" class="badge badge-light "> <span class=" icon-wrapper icon-ion" data-name="document"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M428 224H288a48 48 0 0 1-48-48V36a4 4 0 0 0-4-4h-92a64 64 0 0 0-64 64v320a64 64 0 0 0 64 64h224a64 64 0 0 0 64-64V228a4 4 0 0 0-4-4z"/><path d="M419.22 188.59L275.41 44.78a2 2 0 0 0-3.41 1.41V176a16 16 0 0 0 16 16h129.81a2 2 0 0 0 1.41-3.41z"/></svg></span> Paper </a> <br/> <a href="/paper/neural-discrete-representation-learning#code" class="badge badge-dark "> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> Code </a> <br/> </div> </div> </div> </div> </div> </div> </div> <div class="paper-card infinite-item">  <div class="container-fluid"> <div class="row"> <div class="col-lg-3"> <a href="/paper/high-quality-monocular-depth-estimation-via"> <div class="item-image" style="background-image: url('https://production-media.paperswithcode.com/thumbnails/paper/1812.11941.jpg');"> </div> </a> </div> <div class="col-lg-9"> <div class="row"> <div class="col-lg-9 item-content"> <h1><a href="/paper/high-quality-monocular-depth-estimation-via">High Quality Monocular Depth Estimation via Transfer Learning</a></h1> <p class="author-section" style="padding-top:2px"> <span class="item-github-link"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> <a href="https://github.com/ialhashim/DenseDepth" onclick="captureOutboundLink('https://github.com/ialhashim/DenseDepth'); return true;" style="font-size:13px"> ialhashim/DenseDepth </a> </span> • <span class="item-framework-link"> <img class="" src="data:image/png;base64,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" /> </span> • <span class="author-name-text item-date-pub">31 Dec 2018</span> </p> <p class="item-strip-abstract">Accurate depth estimation from images is a fundamental task in many applications including scene understanding and reconstruction.</p> </div> <div class="col-lg-3 item-interact text-center"> <div class="entity-stars"> <span class="badge badge-secondary"><span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> 45</span> </div> <div class="entity" style="margin-bottom: 20px;"> <a href="/paper/high-quality-monocular-depth-estimation-via" class="badge badge-light "> <span class=" icon-wrapper icon-ion" data-name="document"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M428 224H288a48 48 0 0 1-48-48V36a4 4 0 0 0-4-4h-92a64 64 0 0 0-64 64v320a64 64 0 0 0 64 64h224a64 64 0 0 0 64-64V228a4 4 0 0 0-4-4z"/><path d="M419.22 188.59L275.41 44.78a2 2 0 0 0-3.41 1.41V176a16 16 0 0 0 16 16h129.81a2 2 0 0 0 1.41-3.41z"/></svg></span> Paper </a> <br/> <a href="/paper/high-quality-monocular-depth-estimation-via#code" class="badge badge-dark "> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> Code </a> <br/> </div> </div> </div> </div> </div> </div> </div> <div class="paper-card infinite-item">  <div class="container-fluid"> <div class="row"> <div class="col-lg-3"> <a href="/paper/bart-denoising-sequence-to-sequence-pre"> <div class="item-image" style="background-image: url('https://production-media.paperswithcode.com/thumbnails/paper/1910.13461.jpg');"> </div> </a> </div> <div class="col-lg-9"> <div class="row"> <div class="col-lg-9 item-content"> <h1><a href="/paper/bart-denoising-sequence-to-sequence-pre">BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension</a></h1> <p class="author-section" style="padding-top:2px"> <span class="item-github-link"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> <a href="https://github.com/huggingface/transformers" onclick="captureOutboundLink('https://github.com/huggingface/transformers'); return true;" style="font-size:13px"> huggingface/transformers </a> </span> • <span class="item-framework-link"> <img class="" src="https://production-assets.paperswithcode.com/perf/images/frameworks/pytorch-2fbf2cb9.png" /> </span> • <span class="item-conference-link"> <a href="/conference/acl-2020-6"> ACL 2020 </a> </span> </p> <p class="item-strip-abstract">We evaluate a number of noising approaches, finding the best performance by both randomly shuffling the order of the original sentences and using a novel in-filling scheme, where spans of text are replaced with a single mask token.</p> </div> <div class="col-lg-3 item-interact text-center"> <div class="entity-stars"> <span class="badge badge-secondary"><span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> 45</span> </div> <div class="entity" style="margin-bottom: 20px;"> <a href="/paper/bart-denoising-sequence-to-sequence-pre" class="badge badge-light "> <span class=" icon-wrapper icon-ion" data-name="document"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M428 224H288a48 48 0 0 1-48-48V36a4 4 0 0 0-4-4h-92a64 64 0 0 0-64 64v320a64 64 0 0 0 64 64h224a64 64 0 0 0 64-64V228a4 4 0 0 0-4-4z"/><path d="M419.22 188.59L275.41 44.78a2 2 0 0 0-3.41 1.41V176a16 16 0 0 0 16 16h129.81a2 2 0 0 0 1.41-3.41z"/></svg></span> Paper </a> <br/> <a href="/paper/bart-denoising-sequence-to-sequence-pre#code" class="badge badge-dark "> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> Code </a> <br/> </div> </div> </div> </div> </div> </div> </div> <div class="paper-card infinite-item">  <div class="container-fluid"> <div class="row"> <div class="col-lg-3"> <a href="/paper/learning-phrase-representations-using-rnn"> <div class="item-image" style="background-image: url('https://production-media.paperswithcode.com/thumbnails/paper/1406.1078.jpg');"> </div> </a> </div> <div class="col-lg-9"> <div class="row"> <div class="col-lg-9 item-content"> <h1><a href="/paper/learning-phrase-representations-using-rnn">Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation</a></h1> <p class="author-section" style="padding-top:2px"> <span class="item-github-link"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> <a href="https://github.com/graykode/nlp-tutorial" onclick="captureOutboundLink('https://github.com/graykode/nlp-tutorial'); return true;" style="font-size:13px"> graykode/nlp-tutorial </a> </span> • <span class="item-framework-link"> <img class="" src="https://production-assets.paperswithcode.com/perf/images/frameworks/pytorch-2fbf2cb9.png" /> </span> • <span class="author-name-text item-date-pub">3 Jun 2014</span> </p> <p class="item-strip-abstract">In this paper, we propose a novel neural network model called RNN Encoder-Decoder that consists of two recurrent neural networks (RNN).</p> </div> <div class="col-lg-3 item-interact text-center"> <div class="entity-stars"> <span class="badge badge-secondary"><span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> 42</span> </div> <div class="entity" style="margin-bottom: 20px;"> <a href="/paper/learning-phrase-representations-using-rnn" class="badge badge-light "> <span class=" icon-wrapper icon-ion" data-name="document"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M428 224H288a48 48 0 0 1-48-48V36a4 4 0 0 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48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> Code </a> <br/> </div> </div> </div> </div> </div> </div> </div> </div> <div class="loading" style="display: none"> <div class="loader-ellips infinite-scroll-request"> <span class="loader-ellips__dot"></span> <span class="loader-ellips__dot"></span> <span class="loader-ellips__dot"></span> <span class="loader-ellips__dot"></span> </div> </div> <a class="infinite-more-link" href="?page=2&q="></a> </div> <div class="loading-trigger"></div> </div> <div class="col-lg-2 slim-sidebar task-infobox" id="task-sidebar"> <div class="task-toc"> <h4>Content</h4> <hr> <nav> <a class="toc-link" href="#task-home"><span class=" icon-wrapper icon-fa icon-fa-light" data-name="book"><svg viewBox="0 0 448 520.146" 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