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class='section' id='blog'><div class='widget FeaturedPost' data-version='1' id='FeaturedPost1'> </div><div class='widget Blog' data-version='1' id='Blog1'> <div class='tensorsite-container--narrow'> <div class='tensorsite-detail'> <a aria-hidden='true' class='tensorsite-detail__next-url' hidden='true' href='https://blog.tensorflow.org/2019/04/the-power-of-building-on-accelerating-platform-deep-variant.html'></a> <div aria-hidden='true' class='tensorsite-detail__current-url' hidden='true'>https://blog.tensorflow.org/2019/05/introducing-tensorflow-graphics_9.html</div> <div aria-hidden='true' class='tensorsite-detail__tags' hidden='true'> <span>Graphics</span> <b class='label-divider-dot'>·</b> <span>TensorFlow Core</span> </div> <div aria-hidden='true' class='tensorsite-detail__main-image' hidden='true'> https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiLtbFBddaXSQ9x-oBlhU_mUrk7nd9XpEr0bWXFRiE9lNjdeGKKf6Zl5DKbqn7eiaY032Wmck2JDliqalyJx_f43Y-4Mspjkz3X7eBze1o7NhSnsyDRvEIpHli9oqEFBuJshVeRt7cEmW02/s1600/tf+graphics.jpeg </div> <p aria-hidden='true' class='tensorsite-detail__description' hidden='true'> <span class='tensorsite-content__info'> May 09, 2019 — </span> <em class="mp" style="background-color: white; box-sizing: inherit;">P</em><em class="mp" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.084px;">osted by </em><em class="mp" style="box-sizing: inherit;"><a class="be cl mq mr ms mt" href="https://twitter.com/JPCValentin" rel="noopener" target="_blank">Julien Valentin</em></a><em class="mp" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.084px;"> and </em><em class="mp" style="-webkit-tap-highlight-color: transparent; background-color: white; background-image: url("data:image/svg+xml; background-position: 0px calc(1em + 1px); background-repeat: repeat-x; background-size: 1px 1px; box-sizing: inherit; http: //www.w3.org/2000/svg\"><line x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\" stroke=\"rgba(0, 0, 0, 0.84)\" /></svg>"); letter-spacing: -0.084px; text-decoration-line: none;"><a class="be cl mq mr ms mt" href="https://twitter.com/_sofien_" rel="noopener" target="_blank">Sofien Bouaziz</a></em><br><b style="background-color: white; color: rgba(0, 0, 0, 0.84); font-family: inherit; letter-spacing: -0.004em;"><br></b><b style="background-color: white; color: rgba(0, 0, 0, 0.84); font-family: inherit; letter-spacing: -0.004em;">Github repository</b>: <a class="be cl mq mr ms mt" href="https://github.com/tensorflow/graphics" rel="noopener" target="_blank">https://github.com/tensorflow/graphics</a><br><br>The last few years have seen a rise in novel differentiable graphics layers which can be inserted in neural network architectures. From spatial transformers to differentiable graphics renderers, these new layers leverage the knowledge acquired over years of computer vision and graphics research to… </p> <div class='tensorsite-content__subtitle'> <a href='https://blog.tensorflow.org/search?label=Graphics&max-results=20'> <span>Graphics</span> </a> <b class='label-divider-dot'>·</b> <a href='https://blog.tensorflow.org/search?label=TensorFlow+Core&max-results=20'> <span>TensorFlow Core</span> </a> <b class='label-divider-dot'>·</b> <img alt='Google Article' class='community-icon' src='https://www.gstatic.com/tf_blog/images/ic_google.svg'/> </div> <div class='tensorsite-detail__title'> Introducing TensorFlow Graphics: Computer Graphics Meets Deep Learning </div> <div class='tensorsite-detail__contact'> <div class='tensorsite-detail__info'> <span class='tensorsite-detail__timestamp'>May 09, 2019</span> </div> <a class='icon-link' href='https://twitter.com/intent/tweet?text=%22Introducing TensorFlow Graphics: Computer Graphics Meets Deep Learning%22 from the TensorFlow Blog%0A%0Ahttps://blog.tensorflow.org/2019/05/introducing-tensorflow-graphics_9.html' rel='noopener noreferrer' target='_blank' title='Share this post on Twitter'> <svg alt='Twitter Social Icon' class='twitter-icon social-icon' height='19' viewBox='0 0 23 19' width='23' xmlns='http://www.w3.org/2000/svg'> <g fill='none' fill-rule='evenodd' transform='translate(-7 -9)'> <rect height='36' width='36'></rect> <path d='M14.076,27.2827953 C22.566,27.2827953 27.21,20.2477953 27.21,14.1477953 C27.21,13.9477953 27.21,13.7487953 27.197,13.5507953 C28.1,12.8977953 28.88,12.0887953 29.5,11.1617953 C28.657,11.5347953 27.764,11.7797953 26.848,11.8877953 C27.812,11.3107953 28.533,10.4037953 28.878,9.33479527 C27.972,9.87179527 26.98,10.2507953 25.947,10.4547953 C24.198,8.59579527 21.274,8.50679527 19.415,10.2547953 C18.217,11.3817953 17.708,13.0617953 18.08,14.6647953 C14.368,14.4787953 10.91,12.7257953 8.566,9.84279527 C7.341,11.9507953 7.967,14.6497953 9.995,16.0047953 C9.261,15.9827953 8.542,15.7837953 7.9,15.4267953 L7.9,15.4847953 C7.9,17.6827953 9.449,19.5747953 11.603,20.0107953 C10.924,20.1957953 10.211,20.2227953 9.519,20.0897953 C10.124,21.9707953 11.856,23.2587953 13.832,23.2957953 C12.197,24.5797953 10.178,25.2777953 8.098,25.2747953 C7.731,25.2747953 7.364,25.2527953 7,25.2087953 C9.111,26.5627953 11.567,27.2817953 14.076,27.2787953' fill='#545454'></path> </g> </svg> </a> </div> <div class='divider divider--article-top'></div> <div class='tensorsite-detail__body'> <span style="font-family: inherit;"><em class="mp" style="background-color: white; box-sizing: inherit;">P</em><em class="mp" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.084px;">osted by </em><a class="be cl mq mr ms mt" href="https://twitter.com/JPCValentin" rel="noopener" style="-webkit-tap-highlight-color: transparent; background-color: white; background-image: url("data:image/svg+xml; background-position: 0px calc(1em + 1px); background-repeat: repeat-x; background-size: 1px 1px; box-sizing: inherit; http: //www.w3.org/2000/svg\"><line x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\" stroke=\"rgba(0, 0, 0, 0.84)\" /></svg>"); letter-spacing: -0.084px; text-decoration-line: none;" target="_blank"><em class="mp" style="box-sizing: inherit;">Julien Valentin</em></a><em class="mp" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.084px;"> and </em><em class="mp" style="-webkit-tap-highlight-color: transparent; background-color: white; background-image: url("data:image/svg+xml; background-position: 0px calc(1em + 1px); background-repeat: repeat-x; background-size: 1px 1px; box-sizing: inherit; http: //www.w3.org/2000/svg\"><line x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\" stroke=\"rgba(0, 0, 0, 0.84)\" /></svg>"); letter-spacing: -0.084px; text-decoration-line: none;"><a class="be cl mq mr ms mt" href="https://twitter.com/_sofien_" rel="noopener" style="-webkit-tap-highlight-color: transparent; background-color: white; background-image: url("data:image/svg+xml; background-position: 0px calc(1em + 1px); background-repeat: repeat-x; background-size: 1px 1px; box-sizing: inherit; http: //www.w3.org/2000/svg\"><line x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\" stroke=\"rgba(0, 0, 0, 0.84)\" /></svg>"); letter-spacing: -0.084px; text-decoration-line: none;" target="_blank">Sofien Bouaziz</a></em></span><br /> <b style="background-color: white; color: rgba(0, 0, 0, 0.84); font-family: inherit; letter-spacing: -0.004em;"><br /></b> <b style="background-color: white; color: rgba(0, 0, 0, 0.84); font-family: inherit; letter-spacing: -0.004em;">Github repository</b><span style="background-color: white; color: rgba(0 , 0 , 0 , 0.84); font-family: inherit; letter-spacing: -0.004em;">: </span><a class="be cl mq mr ms mt" href="https://github.com/tensorflow/graphics" rel="noopener" style="background-color: white; font-family: inherit; letter-spacing: -0.004em;" target="_blank">https://github.com/tensorflow/graphics</a><br /> <span style="background-color: white; color: rgba(0 , 0 , 0 , 0.84); font-family: inherit; letter-spacing: -0.004em;"><br /></span> <span style="background-color: white; color: rgba(0 , 0 , 0 , 0.84); font-family: inherit; letter-spacing: -0.004em;">The last few years have seen a rise in novel differentiable graphics layers which can be inserted in neural network architectures. From spatial transformers to differentiable graphics renderers, these new layers leverage the knowledge acquired over years of computer vision and graphics research to build new and more efficient network architectures. Explicitly modeling geometric priors and constraints into neural networks opens up the door to architectures that can be trained robustly, efficiently, and more importantly, in a self-supervised fashion.</span><br /> <a name='more'></a><br /> <div class="mb mc bv aq md b me mf mg mh mi mj mk ml mm mn mo" data-selectable-paragraph="" id="6715" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.004em; line-height: 1.58; margin-bottom: -0.46em; margin-top: 2em;"> <div class="separator" style="clear: both; text-align: center;"> <a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiLtbFBddaXSQ9x-oBlhU_mUrk7nd9XpEr0bWXFRiE9lNjdeGKKf6Zl5DKbqn7eiaY032Wmck2JDliqalyJx_f43Y-4Mspjkz3X7eBze1o7NhSnsyDRvEIpHli9oqEFBuJshVeRt7cEmW02/s1600/tf+graphics.jpeg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img alt="TensorFlow Graphics logo" border="0" data-original-height="636" data-original-width="1414" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiLtbFBddaXSQ9x-oBlhU_mUrk7nd9XpEr0bWXFRiE9lNjdeGKKf6Zl5DKbqn7eiaY032Wmck2JDliqalyJx_f43Y-4Mspjkz3X7eBze1o7NhSnsyDRvEIpHli9oqEFBuJshVeRt7cEmW02/s1600/tf+graphics.jpeg" title="" /></a></div> </div> <div class="mb mc bv aq md b me mf mg mh mi mj mk ml mm mn mo" data-selectable-paragraph="" id="3b95" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.004em; line-height: 1.58; margin-bottom: -0.46em; margin-top: 2em;"> <span style="font-family: inherit;">At a high level, a computer graphics pipeline requires 3D objects and their absolute positioning in the scene, a description of the material they are made of lights and a camera. This scene description is then interpreted by a renderer to generate a synthetic rendering.</span></div> <div class="separator" style="clear: both; text-align: center;"> <a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgBaq0VDcx_LKGWdEZsKbX8kNgTdYyaz7FuBYFBc31vIz2Q0He3KIIrnhDfRXN2dbzWvpQzy8P2nxIz9n4_PO-VcDVWMwMziZe9g3NE_4nmBUMyApGQZuiy3slLsqb7QAZh7dBJjpT0Bn8a/s1600/pic+2.jpeg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="826" data-original-width="1280" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgBaq0VDcx_LKGWdEZsKbX8kNgTdYyaz7FuBYFBc31vIz2Q0He3KIIrnhDfRXN2dbzWvpQzy8P2nxIz9n4_PO-VcDVWMwMziZe9g3NE_4nmBUMyApGQZuiy3slLsqb7QAZh7dBJjpT0Bn8a/s1600/pic+2.jpeg" /></a></div> <div class="mb mc bv aq md b me mf mg mh mi mj mk ml mm mn mo" data-selectable-paragraph="" id="3b95" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.004em; line-height: 1.58; margin-bottom: -0.46em; margin-top: 2em;"> <span style="letter-spacing: -0.084px;"><span style="font-family: inherit;">In comparison, a computer vision system would start from an image and try to infer the parameters of the scene. This allows the prediction of which objects are in the scene, what materials they are made of, and their three dimensional position and orientation.</span></span></div> <div class="separator" style="clear: both; text-align: center;"> <a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEih3omfnOl68e-Rxc__7p-W07lZAI6dYGaduwc7MIINdUhR1mmqCEv21qKz5OkoNzokbQW1TLlJ_MhCCPqCWD9Yff3pg3P9_7mlFNseqddl6p3nvZeXezwkTsFmuh0oIP87O6Y8RDKY3YeS/s1600/pic+3.jpeg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="831" data-original-width="1280" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEih3omfnOl68e-Rxc__7p-W07lZAI6dYGaduwc7MIINdUhR1mmqCEv21qKz5OkoNzokbQW1TLlJ_MhCCPqCWD9Yff3pg3P9_7mlFNseqddl6p3nvZeXezwkTsFmuh0oIP87O6Y8RDKY3YeS/s1600/pic+3.jpeg" /></a></div> <div class="mb mc bv aq md b me mf mg mh mi mj mk ml mm mn mo" data-selectable-paragraph="" id="3b95" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.004em; line-height: 1.58; margin-bottom: -0.46em; margin-top: 2em;"> <span style="font-family: inherit;"><span style="letter-spacing: -0.084px;">Training machine learning systems capable of solving these complex 3D vision tasks most often requires large quantities of data. As labelling data is a costly and complex process, it is important to have mechanisms to design machine learning models that can comprehend the three dimensional world while being trained without much supervision. Combining computer vision and computer graphics techniques provides a unique opportunity to leverage the vast amounts of readily available unlabelled data. </span><span style="letter-spacing: -0.084px;">As illustrated in the image below, this can, for instance, be achieved using analysis by synthesis where the vision system extracts the scene parameters and the graphics system renders back an image based on them. If the rendering matches the original image, the vision system has accurately extracted the scene parameters. In this setup, computer vision and computer graphics go hand-in-hand, forming a single machine learning system similar to an autoencoder, which can be trained in a self-supervised manner.</span></span></div> <div class="separator" style="clear: both; text-align: center;"> <a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjh9GROl5l8AlUiRd-ZshBUYYnYzd50V62Gdv3hzJHaCrPs2EhWl3X0J2Hi_uW7wxMeYUGFt7TqfjPFJQqT_0ScdH_rvGG-woum0t-gV07RpQwmgOilWm878y1WqLNVV_UGdfZ9z2bhzITE/s1600/pic4.jpeg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="757" data-original-width="1280" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjh9GROl5l8AlUiRd-ZshBUYYnYzd50V62Gdv3hzJHaCrPs2EhWl3X0J2Hi_uW7wxMeYUGFt7TqfjPFJQqT_0ScdH_rvGG-woum0t-gV07RpQwmgOilWm878y1WqLNVV_UGdfZ9z2bhzITE/s1600/pic4.jpeg" /></a></div> <h2 style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.022em; line-height: 1.12; margin: 1.95em 0px -0.28em;"> <span style="font-family: inherit; font-weight: normal;">Differentiable Graphics Layers</span></h2> <div class="mb mc bv aq md b me oc mg od mi oe mk of mm og mo" data-selectable-paragraph="" id="674a" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.004em; line-height: 1.58; margin-bottom: -0.46em; margin-top: 0.86em;"> <span style="font-family: inherit;">In the following, we will explore some of the functionalities available in TensorFlow Graphics. This tour is not exhaustive; for more information visit our <a class="be cl mq mr ms mt" href="https://github.com/tensorflow/graphics/" rel="noopener" style="-webkit-tap-highlight-color: transparent; background-image: url("data:image/svg+xml; background-position: 0px calc(1em + 1px); background-repeat: repeat-x; background-size: 1px 1px; box-sizing: inherit; http: //www.w3.org/2000/svg\"><line x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\" stroke=\"rgba(0, 0, 0, 0.84)\" /></svg>"); text-decoration-line: none;" target="_blank">Github</a> to discover the new possibilities made available by TensorFlow Graphics.</span></div> <h3 style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.004em; line-height: 1.58; margin-bottom: -0.46em; margin-top: 2em;"> <span class="md oh" style="box-sizing: inherit; font-weight: normal;"><span style="font-family: inherit;">Transformations</span></span></h3> <div class="mb mc bv aq md b me mf mg mh mi mj mk ml mm mn mo" data-selectable-paragraph="" id="fbde" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.004em; line-height: 1.58; margin-bottom: -0.46em; margin-top: 2em;"> <span style="font-family: inherit;">Object transformations control the position of objects in space. In the illustration below, the axis-angle formalism is used to rotate a cube. The rotation axis is pointing up and the angle is positive, leading the cube to rotate counterclockwise. In this <a class="be cl mq mr ms mt" href="https://colab.sandbox.google.com/github/tensorflow/graphics/blob/master/tensorflow_graphics/notebooks/6dof_alignment.ipynb" rel="noopener" style="-webkit-tap-highlight-color: transparent; background-image: url("data:image/svg+xml; background-position: 0px calc(1em + 1px); background-repeat: repeat-x; background-size: 1px 1px; box-sizing: inherit; http: //www.w3.org/2000/svg\"><line x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\" stroke=\"rgba(0, 0, 0, 0.84)\" /></svg>"); text-decoration-line: none;" target="_blank">Colab example</a>, we show how rotation formalisms can be trained in a neural network that is trained to both predict the rotation and translation of an observed object. This task is at the core of many applications, including robots that focus on interacting with their environment. In these scenarios, grasping objects (e.g. by their handle) with a robotic arm requires a precise estimation of the position of these objects with respect to the arm.</span></div> <div class="separator" style="clear: both; text-align: center;"> <a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgeR-5GD4qeYoXLDmKCWPCpQ9vs_d2QLgzMeIzcD36SINOBPt7ESrDAkSZjxPAIISowqmM-B7fipMfSRH8xuG6bJ4w1L6A3jRdL6HKaUjvxb9eE_ROdFDysy1MMfeah8H5I95mHL3N30uqh/s1600/pic+5.gif" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="554" data-original-width="1280" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgeR-5GD4qeYoXLDmKCWPCpQ9vs_d2QLgzMeIzcD36SINOBPt7ESrDAkSZjxPAIISowqmM-B7fipMfSRH8xuG6bJ4w1L6A3jRdL6HKaUjvxb9eE_ROdFDysy1MMfeah8H5I95mHL3N30uqh/s1600/pic+5.gif" /></a></div> <h3 style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.004em; line-height: 1.58; margin-bottom: -0.46em; margin-top: 2em;"> <span class="md oh" style="box-sizing: inherit; font-weight: normal;"><span style="font-family: inherit;">Modelling cameras</span></span></h3> <div class="mb mc bv aq md b me mf mg mh mi mj mk ml mm mn mo" data-selectable-paragraph="" id="4dd9" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.004em; line-height: 1.58; margin-bottom: -0.46em; margin-top: 2em;"> <span style="font-family: inherit;">Camera models play a fundamental role in computer vision as they greatly influence the appearance of three dimensional objects projected onto the image plane. As can be observed below, the cube appears to be scaling up and down, while in reality the changes are only due to changes in focal length. Try this <a class="be cl mq mr ms mt" href="https://colab.sandbox.google.com/github/tensorflow/graphics/blob/master/tensorflow_graphics/notebooks/intrinsics_optimization.ipynb" rel="noopener" style="-webkit-tap-highlight-color: transparent; background-image: url("data:image/svg+xml; background-position: 0px calc(1em + 1px); background-repeat: repeat-x; background-size: 1px 1px; box-sizing: inherit; http: //www.w3.org/2000/svg\"><line x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\" stroke=\"rgba(0, 0, 0, 0.84)\" /></svg>"); text-decoration-line: none;" target="_blank">Colab example</a> for more details about camera models and a concrete example of how to use them in TensorFlow.</span></div> <div class="separator" style="clear: both; text-align: center;"> <a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjZfNM_7ZDm5928UTuM-pneYvc7lggUfO4N2mEAdAGjDNtPJLKKZdGGGCemXSLGcLabrvN4S7UC3lSUPpFj5OL8zNH-e-UU_MDuUx4y3nVIJINi36B_riLqoo-P5z49yq6Umlq01aYhbx-A/s1600/pic+6.gif" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="500" data-original-width="1280" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjZfNM_7ZDm5928UTuM-pneYvc7lggUfO4N2mEAdAGjDNtPJLKKZdGGGCemXSLGcLabrvN4S7UC3lSUPpFj5OL8zNH-e-UU_MDuUx4y3nVIJINi36B_riLqoo-P5z49yq6Umlq01aYhbx-A/s1600/pic+6.gif" /></a></div> <h3 style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.004em; line-height: 1.58; margin-bottom: -0.46em; margin-top: 2em;"> <span class="md oh" style="box-sizing: inherit; font-weight: normal;"><span style="font-family: inherit;">Materials</span></span></h3> <div class="mb mc bv aq md b me mf mg mh mi mj mk ml mm mn mo" data-selectable-paragraph="" id="c2b3" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.004em; line-height: 1.58; margin-bottom: -0.46em; margin-top: 2em;"> <span style="font-family: inherit;">Material models define how light interacts with objects to give them their unique appearance. For instance, some materials like plaster reflect light uniformly in all directions, where others like mirrors are purely specular. In this interactive <a class="be cl mq mr ms mt" href="https://colab.sandbox.google.com/github/tensorflow/graphics/blob/master/tensorflow_graphics/notebooks/reflectance.ipynb" rel="noopener" style="-webkit-tap-highlight-color: transparent; background-image: url("data:image/svg+xml; background-position: 0px calc(1em + 1px); background-repeat: repeat-x; background-size: 1px 1px; box-sizing: inherit; http: //www.w3.org/2000/svg\"><line x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\" stroke=\"rgba(0, 0, 0, 0.84)\" /></svg>"); text-decoration-line: none;" target="_blank">Colab notebook</a>, you will learn how to generate the following renderings using Tensorflow Graphics. You will also have the opportunity to play with the parameters of the material and the light to develop a good sense of how they interact. Accurately predicting material properties is fundamental to many tasks. For instance, it can allow users to drop virtual furniture in their environment and have the pieces photo-realistically blend with their interior, giving users an accurate perception of how that piece of furniture would look.</span></div> <div class="separator" style="clear: both; text-align: center;"> <a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEixHBGSpnAu5pM_zgqNmm-LozgV07X1_lqh2VPI0tHKRFIVWdahA1KCnpx76VqDaPNb0WTNITYsti171Zpcgak-CoxvODymYsf3kHEnfnm7rYLVaDZMyekzae9LHNRaneresF4hgrqLBa80/s1600/pic+7.jpeg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="288" data-original-width="950" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEixHBGSpnAu5pM_zgqNmm-LozgV07X1_lqh2VPI0tHKRFIVWdahA1KCnpx76VqDaPNb0WTNITYsti171Zpcgak-CoxvODymYsf3kHEnfnm7rYLVaDZMyekzae9LHNRaneresF4hgrqLBa80/s1600/pic+7.jpeg" /></a></div> <h3 style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.004em; line-height: 1.58; margin-bottom: -0.46em; margin-top: 2em;"> <span class="md oh" style="box-sizing: inherit; font-weight: normal;"><span style="font-family: inherit;">Geometry — 3D convolutions and pooling</span></span></h3> <div class="mb mc bv aq md b me mf mg mh mi mj mk ml mm mn mo" data-selectable-paragraph="" id="20ae" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.004em; line-height: 1.58; margin-bottom: -0.46em; margin-top: 2em;"> <span style="font-family: inherit;">In recent years, sensors outputting three dimensional data in the form of point clouds or meshes are becoming part of our everyday life, from smartphone depth sensors to self driving car lidars. Due to their irregular structure, convolutions on these representations are significantly harder to implement compared to images which offer a regular grid structure. TensorFlow Graphics comes with two 3D convolution layers, and one 3D pooling layer, allowing for instance the training of networks to perform semantic part classification on meshes as illustrated below and demonstrated in this <a class="be cl mq mr ms mt" href="https://colab.sandbox.google.com/github/tensorflow/graphics/blob/master/tensorflow_graphics/notebooks/mesh_segmentation_demo.ipynb" rel="noopener" style="-webkit-tap-highlight-color: transparent; background-image: url("data:image/svg+xml; background-position: 0px calc(1em + 1px); background-repeat: repeat-x; background-size: 1px 1px; box-sizing: inherit; http: //www.w3.org/2000/svg\"><line x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\" stroke=\"rgba(0, 0, 0, 0.84)\" /></svg>"); text-decoration-line: none;" target="_blank">Colab notebook</a>.</span></div> <div class="separator" style="clear: both; text-align: center;"> <a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgCstlGDzqhIawQZxU2U2lRlsLixIVq-OcKP90Twrs2hsSutO1wSWQMT0DF-sK_iwjBU563ZpRzyj7_AszmKYpDnFad4nLEg5ZTJ3wCPbH7NUsVk7iwPvPrZ0qhaAaRnVBGU1UKwZNyR3HT/s1600/pic+8.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="486" data-original-width="800" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgCstlGDzqhIawQZxU2U2lRlsLixIVq-OcKP90Twrs2hsSutO1wSWQMT0DF-sK_iwjBU563ZpRzyj7_AszmKYpDnFad4nLEg5ZTJ3wCPbH7NUsVk7iwPvPrZ0qhaAaRnVBGU1UKwZNyR3HT/s1600/pic+8.png" /></a></div> <h3 style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.022em; line-height: 1.12; margin: 1.95em 0px -0.28em;"> <span style="font-family: inherit; font-weight: normal;">TensorBoard 3d</span></h3> <div class="mb mc bv aq md b me oc mg od mi oe mk of mm og mo" data-selectable-paragraph="" id="53cf" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.004em; line-height: 1.58; margin-bottom: -0.46em; margin-top: 0.86em;"> <span style="font-family: inherit;">Visual debugging is a great way to assess whether an experiment is going in the right direction. To this end, TensorFlow Graphics comes with a TensorBoard plugin to interactively visualize 3d meshes and point clouds.</span></div> <div class="separator" style="clear: both; text-align: center;"> <a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg_RLdFiwF6LcgqlaCBoUJZgrcfGM5YycLlo2PZ4jhsX_qOqP41qmLavdFuI1QpCdbP24kWRzm_mnmqEhKIih6LZuYZzuy1_jvST9BcU_V_vQrR335Ukz7um8b-5JHbj7Wdi8VPtL59DY84/s1600/pic+9.gif" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="450" data-original-width="800" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg_RLdFiwF6LcgqlaCBoUJZgrcfGM5YycLlo2PZ4jhsX_qOqP41qmLavdFuI1QpCdbP24kWRzm_mnmqEhKIih6LZuYZzuy1_jvST9BcU_V_vQrR335Ukz7um8b-5JHbj7Wdi8VPtL59DY84/s1600/pic+9.gif" /></a></div> <div style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.022em; line-height: 1.12; margin: 1.95em 0px -0.28em;"> </div> <h3> <span style="font-weight: normal;"><span style="background-color: white; color: rgba(0 , 0 , 0 , 0.84); font-family: inherit; letter-spacing: -0.004em;">Get Started</span></span></h3> <span style="font-weight: normal;"><span style="background-color: white; color: rgba(0 , 0 , 0 , 0.84); font-family: inherit; letter-spacing: -0.004em;">The first release of TensorFlow Graphics supports is compatible with TensorFlow 1.13.1 and above. You will find the API and instructions to install the library by visiting</span><span class="md oh" style="background-color: white; box-sizing: inherit; color: rgba(0 , 0 , 0 , 0.84); font-family: inherit; letter-spacing: -0.004em;"> </span><a class="be cl mq mr ms mt" href="https://www.tensorflow.org/graphics/" rel="noopener" style="-webkit-tap-highlight-color: transparent; background-color: white; background-image: url("data:image/svg+xml; background-position: 0px calc(1em + 1px); background-repeat: repeat-x; background-size: 1px 1px; box-sizing: inherit; font-family: inherit; http: //www.w3.org/2000/svg\"><line x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\" stroke=\"rgba(0, 0, 0, 0.84)\" /></svg>"); letter-spacing: -0.004em; text-decoration-line: none;" target="_blank">https://www.tensorflow.org/graphics</a><span style="background-color: white; color: rgba(0 , 0 , 0 , 0.84); font-family: inherit; letter-spacing: -0.004em;">.</span></span><br /> <h3 style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.004em; line-height: 1.58; margin-bottom: -0.46em; margin-top: 0.86em;"> <span style="font-weight: normal; letter-spacing: -0.352px;">Acknowledgments</span></h3> <div class="mb mc bv aq md b me oc mg od mi oe mk of mm og mo" data-selectable-paragraph="" id="6ef7" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.004em; line-height: 1.58; margin-bottom: -0.46em; margin-top: 0.86em;"> <span style="font-family: inherit;">Creating TensorFlow Graphics was a team effort. Special thanks to Cem Keskin, <a class="be cl mq mr ms mt" href="https://twitter.com/podlipensky" rel="noopener" style="-webkit-tap-highlight-color: transparent; background-image: url("data:image/svg+xml; background-position: 0px calc(1em + 1px); background-repeat: repeat-x; background-size: 1px 1px; box-sizing: inherit; http: //www.w3.org/2000/svg\"><line x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\" stroke=\"rgba(0, 0, 0, 0.84)\" /></svg>"); text-decoration-line: none;" target="_blank">Pavel Pidlypenskyi</a>, <a class="be cl mq mr ms mt" href="https://twitter.com/kiamada" rel="noopener" style="-webkit-tap-highlight-color: transparent; background-image: url("data:image/svg+xml; background-position: 0px calc(1em + 1px); background-repeat: repeat-x; background-size: 1px 1px; box-sizing: inherit; http: //www.w3.org/2000/svg\"><line x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\" stroke=\"rgba(0, 0, 0, 0.84)\" /></svg>"); text-decoration-line: none;" target="_blank">Ameesh Makadia</a>, and <a class="be cl mq mr ms mt" href="https://twitter.com/AvneeshSud" rel="noopener" style="-webkit-tap-highlight-color: transparent; background-image: url("data:image/svg+xml; background-position: 0px calc(1em + 1px); background-repeat: repeat-x; background-size: 1px 1px; box-sizing: inherit; http: //www.w3.org/2000/svg\"><line x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\" stroke=\"rgba(0, 0, 0, 0.84)\" /></svg>"); text-decoration-line: none;" target="_blank">Avneesh Sud</a> who all made significant contributions.</span></div> </div> </div> <div class='tensorsite-detail-footer'> <div class='article-divider'> <img alt='Diamond Article Divider' src='https://www.gstatic.com/tf_blog/images/ic_article_end.svg'/> </div> <a class='tensorsite-chip' href='https://blog.tensorflow.org/search?label=Graphics&max-results=20'> Graphics </a> <a class='tensorsite-chip' href='https://blog.tensorflow.org/search?label=TensorFlow+Core&max-results=20'> TensorFlow Core </a> </div> </div> <div class='tensorsite-next'> <div class='tensorsite-container--large'> <div class='tensorsite-next__title'>Next post</div> <div class='tensorsite-card'> <a aria-label='Next Card' class='tensorsite-card__href next' href='https://blog.tensorflow.org/2019/05/introducing-tensorflow-graphics_9.html'></a> <div class='tensorsite-content__image-wrapper'> <img alt='Introducing TensorFlow Graphics: Computer Graphics Meets Deep Learning' class='tensorsite-content__image' src='https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiLtbFBddaXSQ9x-oBlhU_mUrk7nd9XpEr0bWXFRiE9lNjdeGKKf6Zl5DKbqn7eiaY032Wmck2JDliqalyJx_f43Y-4Mspjkz3X7eBze1o7NhSnsyDRvEIpHli9oqEFBuJshVeRt7cEmW02/s1600/tf+graphics.jpeg'/> </div> <div class='tensorsite-content'> <div class='tensorsite-content__subtitle next'> <span>Graphics</span> <b class='label-divider-dot'>·</b> <span>TensorFlow Core</span> <b class='label-divider-dot'>·</b> <img alt='Google Article' class='community-icon' src='https://www.gstatic.com/tf_blog/images/ic_google.svg'/> </div> <div class='tensorsite-content__title next'> Introducing TensorFlow Graphics: Computer Graphics Meets Deep Learning </div> <p class='tensorsite-content__description next'> <span class='tensorsite-content__info'> May 09, 2019 </span> — <span> <em class="mp" style="background-color: white; box-sizing: inherit;">P</em><em class="mp" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.084px;">osted by </em><em class="mp" style="box-sizing: inherit;"><a class="be cl mq mr ms mt" href="https://twitter.com/JPCValentin" rel="noopener" target="_blank">Julien Valentin</em></a><em class="mp" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); letter-spacing: -0.084px;"> and </em><em class="mp" style="-webkit-tap-highlight-color: transparent; background-color: white; background-image: url("data:image/svg+xml; background-position: 0px calc(1em + 1px); background-repeat: repeat-x; background-size: 1px 1px; box-sizing: inherit; http: //www.w3.org/2000/svg\"><line x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\" stroke=\"rgba(0, 0, 0, 0.84)\" /></svg>"); letter-spacing: -0.084px; text-decoration-line: none;"><a class="be cl mq mr ms mt" href="https://twitter.com/_sofien_" rel="noopener" target="_blank">Sofien Bouaziz</a></em><br><b style="background-color: white; color: rgba(0, 0, 0, 0.84); font-family: inherit; letter-spacing: -0.004em;"><br></b><b style="background-color: white; color: rgba(0, 0, 0, 0.84); font-family: inherit; letter-spacing: -0.004em;">Github repository</b>: <a class="be cl mq mr ms mt" href="https://github.com/tensorflow/graphics" rel="noopener" target="_blank">https://github.com/tensorflow/graphics</a><br><br>The last few years have seen a rise in novel differentiable graphics layers which can be inserted in neural network architectures. From spatial transformers to differentiable graphics renderers, these new layers leverage the knowledge acquired over years of computer vision and graphics research to… </span> </p> </div> </div> </div> </div>  </div></div> </div>  <div class='tensorsite-full-footer'> <div class='section' id='footer'><div class='widget HTML' data-version='1' id='HTML2'> <section class='tensorsite-footer'> <div class='tensorsite-container tensorsite-footer__container'> <div class='tensorsite-footer__side tensorsite-footer__side--left'></div> <div class='tensorsite-footer__side tensorsite-footer__side--right'></div> <div class='tensorsite-footer__content'> <div class='tensorsite-content'> <div class='tensorsite-content__title tensorsite-content__title--grow'> Build, deploy, and experiment easily with TensorFlow </div> <div class='tensorsite-content__cta-wrapper'> <a class='tensorsite-content__button tensorsite-button tensorsite-button--white' href='https://www.tensorflow.org/'> Get started </a> </div> 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