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class="vector-toc-numb">2</span> <span>Architecture and training</span> </div> </a> <ul id="toc-Architecture_and_training-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Datasets" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#Datasets"> <div class="vector-toc-text"> <span class="vector-toc-numb">3</span> <span>Datasets</span> </div> </a> <ul id="toc-Datasets-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Quality_evaluation" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#Quality_evaluation"> <div class="vector-toc-text"> <span class="vector-toc-numb">4</span> <span>Quality evaluation</span> </div> </a> <ul id="toc-Quality_evaluation-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Impact_and_applications" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#Impact_and_applications"> <div class="vector-toc-text"> <span class="vector-toc-numb">5</span> <span>Impact and applications</span> </div> </a> <ul id="toc-Impact_and_applications-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-List_of_notable_text-to-image_models" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#List_of_notable_text-to-image_models"> <div class="vector-toc-text"> <span class="vector-toc-numb">6</span> <span>List of notable text-to-image models</span> </div> </a> <ul id="toc-List_of_notable_text-to-image_models-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Explanatory_notes" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#Explanatory_notes"> <div class="vector-toc-text"> <span class="vector-toc-numb">7</span> <span>Explanatory notes</span> </div> </a> <ul id="toc-Explanatory_notes-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-See_also" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#See_also"> <div class="vector-toc-text"> <span class="vector-toc-numb">8</span> <span>See also</span> </div> </a> <ul id="toc-See_also-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-References" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#References"> <div class="vector-toc-text"> <span class="vector-toc-numb">9</span> <span>References</span> </div> </a> <ul id="toc-References-sublist" class="vector-toc-list"> </ul> </li> </ul> </div> </div> </nav> </div> </div> <div class="mw-content-container"> <main id="content" class="mw-body"> <header class="mw-body-header vector-page-titlebar"> <nav aria-label="Contents" class="vector-toc-landmark"> <div id="vector-page-titlebar-toc" class="vector-dropdown vector-page-titlebar-toc vector-button-flush-left" > <input 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class="interlanguage-link-target"><span>العربية</span></a></li><li class="interlanguage-link interwiki-ca mw-list-item"><a href="https://ca.wikipedia.org/wiki/Model_de_text_a_imatge" title="Model de text a imatge – Catalan" lang="ca" hreflang="ca" data-title="Model de text a imatge" data-language-autonym="Català" data-language-local-name="Catalan" class="interlanguage-link-target"><span>Català</span></a></li><li class="interlanguage-link interwiki-fa mw-list-item"><a href="https://fa.wikipedia.org/wiki/%D9%85%D8%AF%D9%84_%D9%85%D8%AA%D9%86_%D8%A8%D9%87_%D8%AA%D8%B5%D9%88%DB%8C%D8%B1" title="مدل متن به تصویر – Persian" lang="fa" hreflang="fa" data-title="مدل متن به تصویر" data-language-autonym="فارسی" data-language-local-name="Persian" class="interlanguage-link-target"><span>فارسی</span></a></li><li class="interlanguage-link interwiki-fr mw-list-item"><a href="https://fr.wikipedia.org/wiki/Prompt_art" title="Prompt art – French" lang="fr" hreflang="fr" data-title="Prompt art" data-language-autonym="Français" data-language-local-name="French" class="interlanguage-link-target"><span>Français</span></a></li><li class="interlanguage-link interwiki-gl mw-list-item"><a href="https://gl.wikipedia.org/wiki/Modelo_de_texto_a_imaxe" title="Modelo de texto a imaxe – Galician" lang="gl" hreflang="gl" data-title="Modelo de texto a imaxe" data-language-autonym="Galego" data-language-local-name="Galician" class="interlanguage-link-target"><span>Galego</span></a></li><li class="interlanguage-link interwiki-id mw-list-item"><a href="https://id.wikipedia.org/wiki/Model_teks-ke-gambar" title="Model teks-ke-gambar – Indonesian" lang="id" hreflang="id" data-title="Model teks-ke-gambar" data-language-autonym="Bahasa Indonesia" data-language-local-name="Indonesian" class="interlanguage-link-target"><span>Bahasa Indonesia</span></a></li><li class="interlanguage-link interwiki-he mw-list-item"><a href="https://he.wikipedia.org/wiki/%D7%9E%D7%97%D7%95%D7%9C%D7%9C_%D7%AA%D7%9E%D7%95%D7%A0%D7%95%D7%AA" title="מחולל תמונות – Hebrew" lang="he" hreflang="he" data-title="מחולל תמונות" data-language-autonym="עברית" data-language-local-name="Hebrew" class="interlanguage-link-target"><span>עברית</span></a></li><li class="interlanguage-link interwiki-ps mw-list-item"><a href="https://ps.wikipedia.org/wiki/%D9%85%D8%AA%D9%86_%D8%AF_%D8%A7%D9%86%DA%81%D9%88%D8%B1_%D9%BE%D9%87_%D8%A8%DA%BC%D9%87" title="متن د انځور په بڼه – Pashto" lang="ps" hreflang="ps" data-title="متن د انځور په بڼه" data-language-autonym="پښتو" data-language-local-name="Pashto" class="interlanguage-link-target"><span>پښتو</span></a></li><li class="interlanguage-link interwiki-pt mw-list-item"><a href="https://pt.wikipedia.org/wiki/Modelo_de_texto_para_imagem" title="Modelo de texto para imagem – Portuguese" lang="pt" hreflang="pt" data-title="Modelo de texto para imagem" data-language-autonym="Português" data-language-local-name="Portuguese" class="interlanguage-link-target"><span>Português</span></a></li><li class="interlanguage-link interwiki-sr mw-list-item"><a href="https://sr.wikipedia.org/wiki/Model_teksta_u_sliku" title="Model teksta u sliku – Serbian" lang="sr" hreflang="sr" data-title="Model teksta u sliku" data-language-autonym="Српски / srpski" data-language-local-name="Serbian" class="interlanguage-link-target"><span>Српски / srpski</span></a></li><li class="interlanguage-link interwiki-fi mw-list-item"><a href="https://fi.wikipedia.org/wiki/Kuvageneraattori" title="Kuvageneraattori – Finnish" lang="fi" hreflang="fi" data-title="Kuvageneraattori" data-language-autonym="Suomi" data-language-local-name="Finnish" class="interlanguage-link-target"><span>Suomi</span></a></li><li class="interlanguage-link interwiki-tr mw-list-item"><a href="https://tr.wikipedia.org/wiki/Metinden_resme_model" title="Metinden resme model – Turkish" lang="tr" hreflang="tr" data-title="Metinden resme model" data-language-autonym="Türkçe" data-language-local-name="Turkish" class="interlanguage-link-target"><span>Türkçe</span></a></li><li class="interlanguage-link interwiki-zh-yue mw-list-item"><a href="https://zh-yue.wikipedia.org/wiki/%E6%96%87%E6%9C%AC%E5%88%B0%E5%9C%96%E5%83%8F%E7%94%9F%E6%88%90%E6%A8%A1%E5%9E%8B" title="文本到圖像生成模型 – Cantonese" lang="yue" hreflang="yue" data-title="文本到圖像生成模型" data-language-autonym="粵語" data-language-local-name="Cantonese" class="interlanguage-link-target"><span>粵語</span></a></li><li class="interlanguage-link interwiki-zh mw-list-item"><a href="https://zh.wikipedia.org/wiki/%E6%96%87%E6%9C%AC%E5%88%B0%E5%9B%BE%E5%83%8F%E7%94%9F%E6%88%90%E6%A8%A1%E5%9E%8B" title="文本到图像生成模型 – Chinese" lang="zh" hreflang="zh" data-title="文本到图像生成模型" data-language-autonym="中文" data-language-local-name="Chinese" class="interlanguage-link-target"><span>中文</span></a></li> </ul> <div class="after-portlet after-portlet-lang"><span class="wb-langlinks-edit 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id="mw-content-subtitle"></div></div> <div id="mw-content-text" class="mw-body-content"><div class="mw-content-ltr mw-parser-output" lang="en" dir="ltr"><div class="shortdescription nomobile noexcerpt noprint searchaux" style="display:none">Machine learning model</div> <p class="mw-empty-elt"> </p> <figure class="mw-default-size" typeof="mw:File/Thumb"><a href="/wiki/File:Astronaut_Riding_a_Horse_Hiroshige_(SD3.5).webp" class="mw-file-description"><img src="//upload.wikimedia.org/wikipedia/commons/thumb/3/36/Astronaut_Riding_a_Horse_Hiroshige_%28SD3.5%29.webp/220px-Astronaut_Riding_a_Horse_Hiroshige_%28SD3.5%29.webp.png" decoding="async" width="220" height="220" class="mw-file-element" srcset="//upload.wikimedia.org/wikipedia/commons/thumb/3/36/Astronaut_Riding_a_Horse_Hiroshige_%28SD3.5%29.webp/330px-Astronaut_Riding_a_Horse_Hiroshige_%28SD3.5%29.webp.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/3/36/Astronaut_Riding_a_Horse_Hiroshige_%28SD3.5%29.webp/440px-Astronaut_Riding_a_Horse_Hiroshige_%28SD3.5%29.webp.png 2x" data-file-width="1024" data-file-height="1024" /></a><figcaption>An image conditioned on the prompt "an astronaut riding a horse, by <a href="/wiki/Hiroshige" title="Hiroshige">Hiroshige</a>", generated by <a href="/wiki/Stable_Diffusion" title="Stable Diffusion">Stable Diffusion</a> 3.5, a large-scale text-to-image model first released in 2022</figcaption></figure> <p>A <b>text-to-image model</b> is a <a href="/wiki/Machine_learning_model" class="mw-redirect" title="Machine learning model">machine learning model</a> which takes an input <a href="/wiki/Natural_language" title="Natural language">natural language</a> description and produces an image matching that description. </p><p>Text-to-image models began to be developed in the mid-2010s during the beginnings of the <a href="/wiki/AI_boom" title="AI boom">AI boom</a>, as a result of advances in <a href="/wiki/Deep_learning" title="Deep learning">deep neural networks</a>. In 2022, the output of state-of-the-art text-to-image models—such as OpenAI's <a href="/wiki/DALL-E_2" class="mw-redirect" title="DALL-E 2">DALL-E 2</a>, <a href="/wiki/Google_Brain" title="Google Brain">Google Brain</a>'s <a href="/wiki/Google_Brain#Text-to-image_model" title="Google Brain">Imagen</a>, Stability AI's <a href="/wiki/Stable_Diffusion" title="Stable Diffusion">Stable Diffusion</a>, and <a href="/wiki/Midjourney" title="Midjourney">Midjourney</a>—began to be considered to approach the quality of <a href="/wiki/Photograph" title="Photograph">real photographs</a> and human-drawn <a href="/wiki/Folk_art" title="Folk art">art</a>. </p><p>Text-to-image models are generally <a href="/wiki/Latent_diffusion_model" title="Latent diffusion model">latent diffusion models</a>, which combine a <a href="/wiki/Language_model" title="Language model">language model</a>, which transforms the input text into a <a href="/wiki/Latent_variable_model" title="Latent variable model">latent representation</a>, and a <a href="/wiki/Generative_model" title="Generative model">generative image model</a>, which produces an image conditioned on that representation. The most effective models have generally been trained on massive amounts of image and text data <a href="/wiki/Web_scraping" title="Web scraping">scraped from the web</a>.<sup id="cite_ref-imagen-verge_1-0" class="reference"><a href="#cite_note-imagen-verge-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> </p> <meta property="mw:PageProp/toc" /> <div class="mw-heading mw-heading2"><h2 id="History">History</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text-to-image_model&action=edit&section=1" title="Edit section: History"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Before the rise of <a href="/wiki/Deep_learning" title="Deep learning">deep learning</a>,<sup class="noprint Inline-Template" style="white-space:nowrap;">[<i><a href="/wiki/Wikipedia:Manual_of_Style/Dates_and_numbers#Chronological_items" title="Wikipedia:Manual of Style/Dates and numbers"><span title="The time period mentioned near this tag is ambiguous. (October 2024)">when?</span></a></i>]</sup> attempts to build text-to-image models were limited to <a href="/wiki/Collage" title="Collage">collages</a> by arranging existing component images, such as from a database of <a href="/wiki/Clip_art" title="Clip art">clip art</a>.<sup id="cite_ref-agnese_2-0" class="reference"><a href="#cite_note-agnese-2"><span class="cite-bracket">[</span>2<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-zhu-2007_3-0" class="reference"><a href="#cite_note-zhu-2007-3"><span class="cite-bracket">[</span>3<span class="cite-bracket">]</span></a></sup> </p><p>The inverse task, <a href="/wiki/Natural_language_generation" title="Natural language generation">image captioning</a>, was more tractable, and a number of image captioning deep learning models came prior to the first text-to-image models.<sup id="cite_ref-mansimov-2015_4-0" class="reference"><a href="#cite_note-mansimov-2015-4"><span class="cite-bracket">[</span>4<span class="cite-bracket">]</span></a></sup> </p><p>The first modern text-to-image model, alignDRAW, was introduced in 2015 by researchers from the <a href="/wiki/University_of_Toronto" title="University of Toronto">University of Toronto</a>. alignDRAW extended the previously-introduced DRAW architecture (which used a <a href="/wiki/Recurrent_neural_network" title="Recurrent neural network">recurrent</a> <a href="/wiki/Variational_autoencoder" title="Variational autoencoder">variational autoencoder</a> with an <a href="/wiki/Attention_mechanism" class="mw-redirect" title="Attention mechanism">attention mechanism</a>) to be conditioned on text sequences.<sup id="cite_ref-mansimov-2015_4-1" class="reference"><a href="#cite_note-mansimov-2015-4"><span class="cite-bracket">[</span>4<span class="cite-bracket">]</span></a></sup> Images generated by alignDRAW were in small <a href="/wiki/Image_resolution" title="Image resolution">resolution</a> (32×32 pixels, attained from <a href="/wiki/Image_scaling" title="Image scaling">resizing</a>) and were considered to be 'low in diversity'. The model was able to generalize to objects not represented in the training data (such as a red school bus) and appropriately handled novel prompts such as "a stop sign is flying in blue skies", exhibiting output that it was not merely "memorizing" data from the <a href="/wiki/Data_set" title="Data set">training set</a>.<sup id="cite_ref-mansimov-2015_4-2" class="reference"><a href="#cite_note-mansimov-2015-4"><span class="cite-bracket">[</span>4<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-reed-2016_5-0" class="reference"><a href="#cite_note-reed-2016-5"><span class="cite-bracket">[</span>5<span class="cite-bracket">]</span></a></sup> </p> <div class="thumb tright" style=""><div class="thumbinner" style="width:270px"><div class="thumbimage noresize" style="width:268px;"> <span typeof="mw:File"><a href="/wiki/File:AlignDRAW_-_Flying_stop_sign.png" class="mw-file-description"><img src="//upload.wikimedia.org/wikipedia/commons/4/48/AlignDRAW_-_Flying_stop_sign.png" decoding="async" width="268" height="132" class="mw-file-element" data-file-width="134" data-file-height="66" /></a></span></div><div class="thumbcaption">Eight images generated from the text prompt "A stop sign is flying in blue skies." by AlignDRAW (2015). Enlarged to show detail.<sup id="cite_ref-6" class="reference"><a href="#cite_note-6"><span class="cite-bracket">[</span>6<span class="cite-bracket">]</span></a></sup></div></div></div> <p>In 2016, Reed, Akata, Yan et al. became the first to use <a href="/wiki/Generative_adversarial_network" title="Generative adversarial network">generative adversarial networks</a> for the text-to-image task.<sup id="cite_ref-reed-2016_5-1" class="reference"><a href="#cite_note-reed-2016-5"><span class="cite-bracket">[</span>5<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-frolov_7-0" class="reference"><a href="#cite_note-frolov-7"><span class="cite-bracket">[</span>7<span class="cite-bracket">]</span></a></sup> With models trained on narrow, domain-specific datasets, they were able to generate "visually plausible" images of birds and flowers from text captions like <i>"an all black bird with a distinct thick, rounded bill"</i>. A model trained on the more diverse <a href="/wiki/COCO_(dataset)" class="mw-redirect" title="COCO (dataset)">COCO</a> (Common Objects in Context) dataset produced images which were "from a distance... encouraging", but which lacked coherence in their details.<sup id="cite_ref-reed-2016_5-2" class="reference"><a href="#cite_note-reed-2016-5"><span class="cite-bracket">[</span>5<span class="cite-bracket">]</span></a></sup> Later systems include VQGAN-CLIP,<sup id="cite_ref-8" class="reference"><a href="#cite_note-8"><span class="cite-bracket">[</span>8<span class="cite-bracket">]</span></a></sup> XMC-GAN, and GauGAN2.<sup id="cite_ref-9" class="reference"><a href="#cite_note-9"><span class="cite-bracket">[</span>9<span class="cite-bracket">]</span></a></sup> </p> <style data-mw-deduplicate="TemplateStyles:r1237032888/mw-parser-output/.tmulti">.mw-parser-output .tmulti .multiimageinner{display:flex;flex-direction:column}.mw-parser-output .tmulti 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decoding="async" width="117" height="117" class="mw-file-element" srcset="//upload.wikimedia.org/wikipedia/commons/thumb/9/9a/Image_generator-A_stop_sign_is_flying_in_blue_skies-Dall-e3-01.png/176px-Image_generator-A_stop_sign_is_flying_in_blue_skies-Dall-e3-01.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/9/9a/Image_generator-A_stop_sign_is_flying_in_blue_skies-Dall-e3-01.png/234px-Image_generator-A_stop_sign_is_flying_in_blue_skies-Dall-e3-01.png 2x" data-file-width="1024" data-file-height="1024" /></a></span></div></div><div class="tsingle" style="width:119px;max-width:119px"><div class="thumbimage" style="height:117px;overflow:hidden"><span typeof="mw:File"><a href="/wiki/File:Image_generator-A_stop_sign_is_flying_in_blue_skies-Dall-e3-02.png" class="mw-file-description"><img alt="" src="//upload.wikimedia.org/wikipedia/commons/thumb/e/ec/Image_generator-A_stop_sign_is_flying_in_blue_skies-Dall-e3-02.png/117px-Image_generator-A_stop_sign_is_flying_in_blue_skies-Dall-e3-02.png" decoding="async" width="117" height="117" class="mw-file-element" srcset="//upload.wikimedia.org/wikipedia/commons/thumb/e/ec/Image_generator-A_stop_sign_is_flying_in_blue_skies-Dall-e3-02.png/176px-Image_generator-A_stop_sign_is_flying_in_blue_skies-Dall-e3-02.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/e/ec/Image_generator-A_stop_sign_is_flying_in_blue_skies-Dall-e3-02.png/234px-Image_generator-A_stop_sign_is_flying_in_blue_skies-Dall-e3-02.png 2x" data-file-width="1024" data-file-height="1024" /></a></span></div></div></div><div class="trow" style="display:flex"><div class="thumbcaption">DALL·E 2's (top, April 2022) and DALL·E 3's (bottom, September 2023) generated images for the prompt "A stop sign is flying in blue skies"</div></div></div></div> <p>One of the first text-to-image models to capture widespread public attention was <a href="/wiki/OpenAI" title="OpenAI">OpenAI</a>'s <a href="/wiki/DALL-E" title="DALL-E">DALL-E</a>, a <a href="/wiki/Transformer_(machine_learning_model)" class="mw-redirect" title="Transformer (machine learning model)">transformer</a> system announced in January 2021.<sup id="cite_ref-tc-dalle_10-0" class="reference"><a href="#cite_note-tc-dalle-10"><span class="cite-bracket">[</span>10<span class="cite-bracket">]</span></a></sup> A successor capable of generating more complex and realistic images, DALL-E 2, was unveiled in April 2022,<sup id="cite_ref-tc-dalle-2_11-0" class="reference"><a href="#cite_note-tc-dalle-2-11"><span class="cite-bracket">[</span>11<span class="cite-bracket">]</span></a></sup> followed by <a href="/wiki/Stable_Diffusion" title="Stable Diffusion">Stable Diffusion</a> that was publicly released in August 2022.<sup id="cite_ref-12" class="reference"><a href="#cite_note-12"><span class="cite-bracket">[</span>12<span class="cite-bracket">]</span></a></sup> In August 2022, <a href="/wiki/Text-to-image_personalization" title="Text-to-image personalization">text-to-image personalization</a> allows to teach the model a new concept using a small set of images of a new object that was not included in the training set of the text-to-image foundation model. This is achieved by <a href="/wiki/Text-to-image_personalization" title="Text-to-image personalization">textual inversion</a>, namely, finding a new text term that correspond to these images. </p><p>Following other text-to-image models, <a href="/wiki/Language_model" title="Language model">language model</a>-powered <a href="/wiki/Text-to-video" class="mw-redirect" title="Text-to-video">text-to-video</a> platforms such as Runway, Make-A-Video,<sup id="cite_ref-13" class="reference"><a href="#cite_note-13"><span class="cite-bracket">[</span>13<span class="cite-bracket">]</span></a></sup> Imagen Video,<sup id="cite_ref-14" class="reference"><a href="#cite_note-14"><span class="cite-bracket">[</span>14<span class="cite-bracket">]</span></a></sup> Midjourney,<sup id="cite_ref-15" class="reference"><a href="#cite_note-15"><span class="cite-bracket">[</span>15<span class="cite-bracket">]</span></a></sup> and Phenaki<sup id="cite_ref-16" class="reference"><a href="#cite_note-16"><span class="cite-bracket">[</span>16<span class="cite-bracket">]</span></a></sup> can generate video from text and/or text/image prompts.<sup id="cite_ref-17" class="reference"><a href="#cite_note-17"><span class="cite-bracket">[</span>17<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading2"><h2 id="Architecture_and_training">Architecture and training</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text-to-image_model&action=edit&section=2" title="Edit section: Architecture and training"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <figure class="mw-default-size" typeof="mw:File/Thumb"><a href="/wiki/File:State_of_AI_Art_Machine_Learning_Models.svg" class="mw-file-description"><img src="//upload.wikimedia.org/wikipedia/commons/thumb/1/13/State_of_AI_Art_Machine_Learning_Models.svg/220px-State_of_AI_Art_Machine_Learning_Models.svg.png" decoding="async" width="220" height="132" class="mw-file-element" srcset="//upload.wikimedia.org/wikipedia/commons/thumb/1/13/State_of_AI_Art_Machine_Learning_Models.svg/330px-State_of_AI_Art_Machine_Learning_Models.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/1/13/State_of_AI_Art_Machine_Learning_Models.svg/440px-State_of_AI_Art_Machine_Learning_Models.svg.png 2x" data-file-width="512" data-file-height="307" /></a><figcaption>High-level architecture showing the state of AI art machine learning models, and notable models and applications as a clickable SVG image map</figcaption></figure> <p>Text-to-image models have been built using a variety of architectures. The text encoding step may be performed with a <a href="/wiki/Recurrent_neural_network" title="Recurrent neural network">recurrent neural network</a> such as a <a href="/wiki/Long_short-term_memory" title="Long short-term memory">long short-term memory</a> (LSTM) network, though <a href="/wiki/Transformer_(machine_learning_model)" class="mw-redirect" title="Transformer (machine learning model)">transformer</a> models have since become a more popular option. For the image generation step, conditional <a href="/wiki/Generative_adversarial_network" title="Generative adversarial network">generative adversarial networks</a> (GANs) have been commonly used, with <a href="/wiki/Diffusion_model" title="Diffusion model">diffusion models</a> also becoming a popular option in recent years. Rather than directly training a model to output a high-resolution image conditioned on a text embedding, a popular technique is to train a model to generate low-resolution images, and use one or more auxiliary deep learning models to upscale it, filling in finer details. </p><p>Text-to-image models are trained on large datasets of (text, image) pairs, often scraped from the web. With their 2022 Imagen model, Google Brain reported positive results from using a <a href="/wiki/Large_language_model" title="Large language model">large language model</a> trained separately on a text-only corpus (with its weights subsequently frozen), a departure from the theretofore standard approach.<sup id="cite_ref-imagen-paper_18-0" class="reference"><a href="#cite_note-imagen-paper-18"><span class="cite-bracket">[</span>18<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading2"><h2 id="Datasets">Datasets</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text-to-image_model&action=edit&section=3" title="Edit section: Datasets"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <figure class="mw-default-size" typeof="mw:File/Thumb"><a href="/wiki/File:Captioned_image_dataset_examples.jpg" class="mw-file-description"><img src="//upload.wikimedia.org/wikipedia/commons/thumb/0/0f/Captioned_image_dataset_examples.jpg/220px-Captioned_image_dataset_examples.jpg" decoding="async" width="220" height="275" class="mw-file-element" srcset="//upload.wikimedia.org/wikipedia/commons/thumb/0/0f/Captioned_image_dataset_examples.jpg/330px-Captioned_image_dataset_examples.jpg 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/0/0f/Captioned_image_dataset_examples.jpg/440px-Captioned_image_dataset_examples.jpg 2x" data-file-width="1770" data-file-height="2209" /></a><figcaption>Examples of images and captions from three public datasets which are commonly used to train text-to-image models</figcaption></figure> <p>Training a text-to-image model requires a dataset of images paired with text captions. One dataset commonly used for this purpose is the COCO dataset. Released by Microsoft in 2014, COCO consists of around 123,000 images depicting a diversity of objects with five captions per image, generated by human annotators. Oxford-120 Flowers and CUB-200 Birds are smaller datasets of around 10,000 images each, restricted to flowers and birds, respectively. It is considered less difficult to train a high-quality text-to-image model with these datasets because of their narrow range of subject matter.<sup id="cite_ref-frolov_7-1" class="reference"><a href="#cite_note-frolov-7"><span class="cite-bracket">[</span>7<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading2"><h2 id="Quality_evaluation">Quality evaluation</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text-to-image_model&action=edit&section=4" title="Edit section: Quality evaluation"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Evaluating and comparing the quality of text-to-image models is a problem involving assessing multiple desirable properties. A desideratum specific to text-to-image models is that generated images semantically align with the text captions used to generate them. A number of schemes have been devised for assessing these qualities, some automated and others based on human judgement.<sup id="cite_ref-frolov_7-2" class="reference"><a href="#cite_note-frolov-7"><span class="cite-bracket">[</span>7<span class="cite-bracket">]</span></a></sup> </p><p>A common algorithmic metric for assessing image quality and diversity is the <a href="/wiki/Inception_score" title="Inception score">Inception Score</a> (IS), which is based on the distribution of labels predicted by a pretrained <a href="/wiki/Inceptionv3" class="mw-redirect" title="Inceptionv3">Inceptionv3</a> <a href="/wiki/Computer_vision" title="Computer vision">image classification model</a> when applied to a sample of images generated by the text-to-image model. The score is increased when the image classification model predicts a single label with high probability, a scheme intended to favour "distinct" generated images. Another popular metric is the related <a href="/wiki/Fr%C3%A9chet_inception_distance" title="Fréchet inception distance">Fréchet inception distance</a>, which compares the distribution of generated images and real training images according to features extracted by one of the final layers of a pretrained image classification model.<sup id="cite_ref-frolov_7-3" class="reference"><a href="#cite_note-frolov-7"><span class="cite-bracket">[</span>7<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading2"><h2 id="Impact_and_applications">Impact and applications</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text-to-image_model&action=edit&section=5" title="Edit section: Impact and applications"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <div class="excerpt-block"><style data-mw-deduplicate="TemplateStyles:r1066933788">.mw-parser-output .excerpt-hat .mw-editsection-like{font-style:normal}</style><style data-mw-deduplicate="TemplateStyles:r1236090951">.mw-parser-output .hatnote{font-style:italic}.mw-parser-output div.hatnote{padding-left:1.6em;margin-bottom:0.5em}.mw-parser-output .hatnote i{font-style:normal}.mw-parser-output .hatnote+link+.hatnote{margin-top:-0.5em}@media print{body.ns-0 .mw-parser-output .hatnote{display:none!important}}</style><div role="note" class="hatnote navigation-not-searchable dablink excerpt-hat selfref">This section is an excerpt from <a href="/wiki/Artificial_intelligence_art#Impact_and_applications" title="Artificial intelligence art">Artificial intelligence art § Impact and applications</a>.<span class="mw-editsection-like plainlinks"><span class="mw-editsection-bracket">[</span><a class="external text" href="https://en.wikipedia.org/w/index.php?title=Artificial_intelligence_art&action=edit">edit</a><span class="mw-editsection-bracket">]</span></span></div><div class="excerpt"> AI has the potential for a <a href="/wiki/Societal_transformation" title="Societal transformation">societal transformation</a>, which may include enabling the expansion of noncommercial niche genres (such as <a href="/wiki/Cyberpunk_derivatives" title="Cyberpunk derivatives">cyberpunk derivatives</a> like <a href="/wiki/Solarpunk" title="Solarpunk">solarpunk</a>) by amateurs, novel entertainment, fast prototyping,<sup id="cite_ref-Artificial_intelligence_art_computerworld_19-0" class="reference"><a href="#cite_note-Artificial_intelligence_art_computerworld-19"><span class="cite-bracket">[</span>19<span class="cite-bracket">]</span></a></sup> increasing art-making accessibility,<sup id="cite_ref-Artificial_intelligence_art_computerworld_19-1" class="reference"><a href="#cite_note-Artificial_intelligence_art_computerworld-19"><span class="cite-bracket">[</span>19<span class="cite-bracket">]</span></a></sup> and artistic output per effort and/or expenses and/or time<sup id="cite_ref-Artificial_intelligence_art_computerworld_19-2" class="reference"><a href="#cite_note-Artificial_intelligence_art_computerworld-19"><span class="cite-bracket">[</span>19<span class="cite-bracket">]</span></a></sup>—e.g., via generating drafts, draft-refinitions, and image components (<a href="/wiki/Inpainting" title="Inpainting">inpainting</a>). Generated images are sometimes used as sketches,<sup id="cite_ref-Artificial_intelligence_art_nytimesRoose_20-0" class="reference"><a href="#cite_note-Artificial_intelligence_art_nytimesRoose-20"><span class="cite-bracket">[</span>20<span class="cite-bracket">]</span></a></sup> low-cost experiments,<sup id="cite_ref-Artificial_intelligence_art_CNBCLeswing_21-0" class="reference"><a href="#cite_note-Artificial_intelligence_art_CNBCLeswing-21"><span class="cite-bracket">[</span>21<span class="cite-bracket">]</span></a></sup> inspiration, or illustrations of <a href="/wiki/Proof-of-concept" class="mw-redirect" title="Proof-of-concept">proof-of-concept</a>-stage ideas. Additional functionalities or improvements may also relate to post-generation manual editing (i.e., polishing), such as subsequent tweaking with an image editor.<sup id="cite_ref-Artificial_intelligence_art_CNBCLeswing_21-1" class="reference"><a href="#cite_note-Artificial_intelligence_art_CNBCLeswing-21"><span class="cite-bracket">[</span>21<span class="cite-bracket">]</span></a></sup></div></div> <div class="mw-heading mw-heading2"><h2 id="List_of_notable_text-to-image_models">List of notable text-to-image models</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text-to-image_model&action=edit&section=6" title="Edit section: List of notable text-to-image models"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <table class="wikitable sortable"> <caption> </caption> <tbody><tr> <th>Name </th> <th>Release date </th> <th>Developer </th> <th>License </th></tr> <tr> <td><a href="/wiki/DALL-E" title="DALL-E">DALL-E</a> </td> <td>January 2021 </td> <td rowspan="3"><a href="/wiki/OpenAI" title="OpenAI">OpenAI</a> </td> <td rowspan="10">Proprietary </td></tr> <tr> <td><a href="/wiki/DALL-E" title="DALL-E">DALL-E 2</a> </td> <td>April 2022 </td></tr> <tr> <td><a href="/wiki/DALL-E" title="DALL-E">DALL-E 3</a> </td> <td>September 2023 </td></tr> <tr> <td><a href="/wiki/Ideogram_(text-to-image_model)" title="Ideogram (text-to-image model)">Ideogram 2.0</a> </td> <td>August 2024 </td> <td>Ideogram </td></tr> <tr> <td><a href="/wiki/Google_Brain#Text-to-image_model" title="Google Brain">Imagen</a> </td> <td>April 2023 </td> <td rowspan="4"><a href="/wiki/Google" title="Google">Google</a> </td></tr> <tr> <td>Imagen 2 </td> <td>December 2023<sup id="cite_ref-22" class="reference"><a href="#cite_note-22"><span class="cite-bracket">[</span>22<span class="cite-bracket">]</span></a></sup> </td></tr> <tr> <td>Imagen 3 </td> <td>May 2024 </td></tr> <tr> <td><a href="/wiki/Google_Brain#Text-to-image_model" title="Google Brain">Parti</a> </td> <td>Unreleased </td></tr> <tr> <td><a href="/wiki/Adobe_Firefly" title="Adobe Firefly">Firefly</a> </td> <td>March 2023 </td> <td><a href="/wiki/Adobe_Inc." title="Adobe Inc.">Adobe Inc.</a> </td></tr> <tr> <td><a href="/wiki/Midjourney" title="Midjourney">Midjourney</a> </td> <td>July 2022 </td> <td>Midjourney, Inc. </td></tr> <tr> <td><a href="/wiki/Stable_Diffusion" title="Stable Diffusion">Stable Diffusion</a> </td> <td>August 2022 </td> <td>Stability AI </td> <td><a rel="nofollow" class="external text" href="https://stability.ai/community-license-agreement">Stability AI Community License</a><sup id="cite_ref-23" class="reference"><a href="#cite_note-23"><span class="cite-bracket">[</span>note 1<span class="cite-bracket">]</span></a></sup> </td></tr> <tr> <td><a href="/wiki/Flux_(text-to-image_model)" title="Flux (text-to-image model)">Flux</a> </td> <td>August 2024 </td> <td>Black Forest Labs </td> <td><a href="/wiki/Apache_License" title="Apache License">Apache License</a><sup id="cite_ref-24" class="reference"><a href="#cite_note-24"><span class="cite-bracket">[</span>note 2<span class="cite-bracket">]</span></a></sup> </td></tr> <tr> <td><a href="/wiki/RunwayML" class="mw-redirect" title="RunwayML">RunwayML</a> </td> <td>2018 </td> <td>Runway AI, Inc. </td> <td>Proprietary </td></tr></tbody></table> <div class="mw-heading mw-heading2"><h2 id="Explanatory_notes">Explanatory notes</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text-to-image_model&action=edit&section=7" title="Edit section: Explanatory notes"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <style data-mw-deduplicate="TemplateStyles:r1239543626">.mw-parser-output .reflist{margin-bottom:0.5em;list-style-type:decimal}@media screen{.mw-parser-output .reflist{font-size:90%}}.mw-parser-output .reflist .references{font-size:100%;margin-bottom:0;list-style-type:inherit}.mw-parser-output .reflist-columns-2{column-width:30em}.mw-parser-output .reflist-columns-3{column-width:25em}.mw-parser-output .reflist-columns{margin-top:0.3em}.mw-parser-output .reflist-columns ol{margin-top:0}.mw-parser-output .reflist-columns li{page-break-inside:avoid;break-inside:avoid-column}.mw-parser-output .reflist-upper-alpha{list-style-type:upper-alpha}.mw-parser-output .reflist-upper-roman{list-style-type:upper-roman}.mw-parser-output .reflist-lower-alpha{list-style-type:lower-alpha}.mw-parser-output .reflist-lower-greek{list-style-type:lower-greek}.mw-parser-output .reflist-lower-roman{list-style-type:lower-roman}</style><div class="reflist"> <div class="mw-references-wrap"><ol class="references"> <li id="cite_note-23"><span class="mw-cite-backlink"><b><a href="#cite_ref-23">^</a></b></span> <span class="reference-text">This license can be used by individuals and organizations up to $1 million in revenue, for organizations with annual revenue more than $1 million, Stability AI Enterprise License is needed. All outputs are retained by users regardless of revenue</span> </li> <li id="cite_note-24"><span class="mw-cite-backlink"><b><a href="#cite_ref-24">^</a></b></span> <span class="reference-text">For the schnell model, the dev model is using a non-commercial license while the pro model is proprietary (only available as <a href="/wiki/Application_programming_interface" class="mw-redirect" title="Application programming interface">API</a>)</span> </li> </ol></div></div> <div class="mw-heading mw-heading2"><h2 id="See_also">See also</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text-to-image_model&action=edit&section=8" title="Edit section: See also"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li><a href="/wiki/Artificial_intelligence_art" title="Artificial intelligence art">Artificial intelligence art</a></li></ul> <div class="mw-heading mw-heading2"><h2 id="References">References</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text-to-image_model&action=edit&section=9" title="Edit section: References"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1239543626"><div class="reflist"> <div class="mw-references-wrap mw-references-columns"><ol class="references"> <li id="cite_note-imagen-verge-1"><span class="mw-cite-backlink"><b><a href="#cite_ref-imagen-verge_1-0">^</a></b></span> <span class="reference-text"><style data-mw-deduplicate="TemplateStyles:r1238218222">.mw-parser-output cite.citation{font-style:inherit;word-wrap:break-word}.mw-parser-output .citation q{quotes:"\"""\"""'""'"}.mw-parser-output .citation:target{background-color:rgba(0,127,255,0.133)}.mw-parser-output .id-lock-free.id-lock-free a{background:url("//upload.wikimedia.org/wikipedia/commons/6/65/Lock-green.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-limited.id-lock-limited a,.mw-parser-output .id-lock-registration.id-lock-registration a{background:url("//upload.wikimedia.org/wikipedia/commons/d/d6/Lock-gray-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-subscription.id-lock-subscription a{background:url("//upload.wikimedia.org/wikipedia/commons/a/aa/Lock-red-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .cs1-ws-icon a{background:url("//upload.wikimedia.org/wikipedia/commons/4/4c/Wikisource-logo.svg")right 0.1em center/12px no-repeat}body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-free a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-limited a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-registration a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-subscription a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .cs1-ws-icon a{background-size:contain;padding:0 1em 0 0}.mw-parser-output .cs1-code{color:inherit;background:inherit;border:none;padding:inherit}.mw-parser-output .cs1-hidden-error{display:none;color:var(--color-error,#d33)}.mw-parser-output .cs1-visible-error{color:var(--color-error,#d33)}.mw-parser-output .cs1-maint{display:none;color:#085;margin-left:0.3em}.mw-parser-output .cs1-kern-left{padding-left:0.2em}.mw-parser-output .cs1-kern-right{padding-right:0.2em}.mw-parser-output .citation .mw-selflink{font-weight:inherit}@media screen{.mw-parser-output .cs1-format{font-size:95%}html.skin-theme-clientpref-night .mw-parser-output .cs1-maint{color:#18911f}}@media screen and (prefers-color-scheme:dark){html.skin-theme-clientpref-os .mw-parser-output .cs1-maint{color:#18911f}}</style><cite id="CITEREFVincent2022" class="citation news cs1">Vincent, James (May 24, 2022). <a rel="nofollow" class="external text" href="https://www.theverge.com/2022/5/24/23139297/google-imagen-text-to-image-ai-system-examples-paper">"All these images were generated by Google's latest text-to-image AI"</a>. <i>The Verge</i>. 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classification">Loss functions</a></li> <li><a href="/wiki/Regression_analysis" title="Regression analysis">Regression</a> <ul><li><a href="/wiki/Bias%E2%80%93variance_tradeoff" title="Bias–variance tradeoff">Bias–variance tradeoff</a></li> <li><a href="/wiki/Double_descent" title="Double descent">Double descent</a></li> <li><a href="/wiki/Overfitting" title="Overfitting">Overfitting</a></li></ul></li> <li><a href="/wiki/Cluster_analysis" title="Cluster analysis">Clustering</a></li> <li><a href="/wiki/Gradient_descent" title="Gradient descent">Gradient descent</a> <ul><li><a href="/wiki/Stochastic_gradient_descent" title="Stochastic gradient descent">SGD</a></li> <li><a href="/wiki/Quasi-Newton_method" title="Quasi-Newton method">Quasi-Newton method</a></li> <li><a href="/wiki/Conjugate_gradient_method" title="Conjugate gradient method">Conjugate gradient method</a></li></ul></li> <li><a href="/wiki/Backpropagation" title="Backpropagation">Backpropagation</a></li> <li><a href="/wiki/Attention_(machine_learning)" title="Attention (machine learning)">Attention</a></li> <li><a href="/wiki/Convolution" title="Convolution">Convolution</a></li> <li><a href="/wiki/Normalization_(machine_learning)" title="Normalization (machine learning)">Normalization</a> <ul><li><a href="/wiki/Batch_normalization" title="Batch normalization">Batchnorm</a></li></ul></li> <li><a href="/wiki/Activation_function" title="Activation function">Activation</a> <ul><li><a href="/wiki/Softmax_function" title="Softmax function">Softmax</a></li> <li><a href="/wiki/Sigmoid_function" title="Sigmoid function">Sigmoid</a></li> <li><a href="/wiki/Rectifier_(neural_networks)" title="Rectifier (neural networks)">Rectifier</a></li></ul></li> <li><a href="/wiki/Gating_mechanism" title="Gating mechanism">Gating</a></li> <li><a href="/wiki/Weight_initialization" title="Weight initialization">Weight initialization</a></li> <li><a href="/wiki/Regularization_(mathematics)" title="Regularization (mathematics)">Regularization</a></li> <li><a href="/wiki/Training,_validation,_and_test_data_sets" title="Training, validation, and test data sets">Datasets</a> <ul><li><a href="/wiki/Data_augmentation" title="Data augmentation">Augmentation</a></li></ul></li> <li><a href="/wiki/Reinforcement_learning" title="Reinforcement learning">Reinforcement learning</a> <ul><li><a href="/wiki/Q-learning" title="Q-learning">Q-learning</a></li> <li><a href="/wiki/State%E2%80%93action%E2%80%93reward%E2%80%93state%E2%80%93action" title="State–action–reward–state–action">SARSA</a></li> <li><a href="/wiki/Imitation_learning" title="Imitation learning">Imitation</a></li></ul></li> <li><a href="/wiki/Diffusion_process" title="Diffusion process">Diffusion</a></li> <li><a href="/wiki/Latent_diffusion_model" title="Latent diffusion model">Latent diffusion model</a></li> <li><a href="/wiki/Autoregressive_model" title="Autoregressive model">Autoregression</a></li> <li><a href="/wiki/Adversarial_machine_learning" title="Adversarial machine learning">Adversary</a></li> <li><a href="/wiki/Retrieval-augmented_generation" title="Retrieval-augmented generation">RAG</a></li> <li><a href="/wiki/Reinforcement_learning_from_human_feedback" title="Reinforcement learning from human feedback">RLHF</a></li> <li><a href="/wiki/Self-supervised_learning" title="Self-supervised learning">Self-supervised learning</a></li> <li><a href="/wiki/Prompt_engineering" title="Prompt engineering">Prompt engineering</a></li> <li><a href="/wiki/Word_embedding" title="Word embedding">Word embedding</a></li> <li><a href="/wiki/Hallucination_(artificial_intelligence)" title="Hallucination (artificial intelligence)">Hallucination</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Applications</th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Machine_learning" title="Machine learning">Machine learning</a> <ul><li><a href="/wiki/Prompt_engineering#In-context_learning" title="Prompt engineering">In-context learning</a></li></ul></li> <li><a href="/wiki/Neural_network_(machine_learning)" title="Neural network (machine learning)">Artificial neural network</a> <ul><li><a href="/wiki/Deep_learning" title="Deep learning">Deep learning</a></li></ul></li> <li><a href="/wiki/Language_model" title="Language model">Language model</a> <ul><li><a href="/wiki/Large_language_model" title="Large language model">Large language model</a></li> <li><a href="/wiki/Neural_machine_translation" title="Neural machine translation">NMT</a></li></ul></li> <li><a href="/wiki/Artificial_general_intelligence" title="Artificial general intelligence">Artificial general intelligence</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Implementations</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="row" class="navbox-group" style="width:1%">Audio–visual</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/AlexNet" title="AlexNet">AlexNet</a></li> <li><a href="/wiki/WaveNet" title="WaveNet">WaveNet</a></li> <li><a href="/wiki/Human_image_synthesis" title="Human image synthesis">Human image synthesis</a></li> <li><a href="/wiki/Handwriting_recognition" title="Handwriting recognition">HWR</a></li> <li><a href="/wiki/Optical_character_recognition" title="Optical character recognition">OCR</a></li> <li><a href="/wiki/Deep_learning_speech_synthesis" title="Deep learning speech synthesis">Speech synthesis</a> <ul><li><a href="/wiki/ElevenLabs" title="ElevenLabs">ElevenLabs</a></li></ul></li> <li><a href="/wiki/Speech_recognition" title="Speech recognition">Speech recognition</a> <ul><li><a href="/wiki/Whisper_(speech_recognition_system)" title="Whisper (speech recognition system)">Whisper</a></li></ul></li> <li><a href="/wiki/Facial_recognition_system" title="Facial recognition system">Facial recognition</a></li> <li><a href="/wiki/AlphaFold" title="AlphaFold">AlphaFold</a></li> <li><a class="mw-selflink selflink">Text-to-image models</a> <ul><li><a href="/wiki/DALL-E" title="DALL-E">DALL-E</a></li> <li><a href="/wiki/Flux_(text-to-image_model)" title="Flux (text-to-image model)">Flux</a></li> <li><a href="/wiki/Ideogram_(text-to-image_model)" title="Ideogram (text-to-image model)">Ideogram</a></li> <li><a href="/wiki/Midjourney" title="Midjourney">Midjourney</a></li> <li><a href="/wiki/Stable_Diffusion" title="Stable Diffusion">Stable Diffusion</a></li></ul></li> <li><a href="/wiki/Text-to-video_model" title="Text-to-video model">Text-to-video models</a> <ul><li><a href="/wiki/Sora_(text-to-video_model)" title="Sora (text-to-video model)">Sora</a></li> <li><a href="/wiki/Dream_Machine_(text-to-video_model)" title="Dream Machine (text-to-video model)">Dream Machine</a></li> <li><a href="/wiki/VideoPoet" title="VideoPoet">VideoPoet</a></li></ul></li> <li><a href="/wiki/Music_and_artificial_intelligence" title="Music and artificial intelligence">Music generation</a> <ul><li><a href="/wiki/Suno_AI" title="Suno AI">Suno AI</a></li> <li><a href="/wiki/Udio" title="Udio">Udio</a></li></ul></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Text</th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Word2vec" title="Word2vec">Word2vec</a></li> <li><a href="/wiki/Seq2seq" title="Seq2seq">Seq2seq</a></li> <li><a href="/wiki/GloVe" title="GloVe">GloVe</a></li> <li><a href="/wiki/BERT_(language_model)" title="BERT (language model)">BERT</a></li> <li><a href="/wiki/T5_(language_model)" title="T5 (language model)">T5</a></li> <li><a href="/wiki/Llama_(language_model)" title="Llama (language model)">Llama</a></li> <li><a href="/wiki/Chinchilla_(language_model)" title="Chinchilla (language model)">Chinchilla AI</a></li> <li><a href="/wiki/PaLM" title="PaLM">PaLM</a></li> <li><a href="/wiki/Generative_pre-trained_transformer" title="Generative pre-trained transformer">GPT</a> <ul><li><a href="/wiki/GPT-1" title="GPT-1">1</a></li> <li><a href="/wiki/GPT-2" title="GPT-2">2</a></li> <li><a href="/wiki/GPT-3" title="GPT-3">3</a></li> <li><a href="/wiki/GPT-J" title="GPT-J">J</a></li> <li><a href="/wiki/ChatGPT" title="ChatGPT">ChatGPT</a></li> <li><a href="/wiki/GPT-4" title="GPT-4">4</a></li> <li><a href="/wiki/GPT-4o" title="GPT-4o">4o</a></li> <li><a href="/wiki/OpenAI_o1" title="OpenAI o1">o1</a></li></ul></li> <li><a href="/wiki/Claude_(language_model)" title="Claude (language model)">Claude</a></li> <li><a href="/wiki/Gemini_(language_model)" title="Gemini (language model)">Gemini</a></li> <li><a href="/wiki/Grok_(chatbot)" title="Grok (chatbot)">Grok</a></li> <li><a href="/wiki/LaMDA" title="LaMDA">LaMDA</a></li> <li><a href="/wiki/BLOOM_(language_model)" title="BLOOM (language model)">BLOOM</a></li> <li><a href="/wiki/Project_Debater" title="Project Debater">Project Debater</a></li> <li><a href="/wiki/IBM_Watson" title="IBM Watson">IBM Watson</a></li> <li><a href="/wiki/IBM_Watsonx" title="IBM Watsonx">IBM Watsonx</a></li> <li><a href="/wiki/IBM_Granite" title="IBM Granite">Granite</a></li> <li><a href="/wiki/Huawei_PanGu" title="Huawei PanGu">PanGu-Σ</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Decisional</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/AlphaGo" title="AlphaGo">AlphaGo</a></li> <li><a href="/wiki/AlphaZero" title="AlphaZero">AlphaZero</a></li> <li><a href="/wiki/OpenAI_Five" title="OpenAI Five">OpenAI Five</a></li> <li><a href="/wiki/Self-driving_car" title="Self-driving car">Self-driving car</a></li> <li><a href="/wiki/MuZero" title="MuZero">MuZero</a></li> <li><a href="/wiki/Action_selection" title="Action selection">Action selection</a> <ul><li><a href="/wiki/AutoGPT" title="AutoGPT">AutoGPT</a></li></ul></li> <li><a href="/wiki/Robot_control" title="Robot control">Robot control</a></li></ul> </div></td></tr></tbody></table><div></div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">People</th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Alan_Turing" title="Alan Turing">Alan Turing</a></li> <li><a href="/wiki/Warren_Sturgis_McCulloch" title="Warren Sturgis McCulloch">Warren Sturgis McCulloch</a></li> <li><a href="/wiki/Walter_Pitts" title="Walter Pitts">Walter Pitts</a></li> <li><a href="/wiki/John_von_Neumann" title="John von Neumann">John von Neumann</a></li> <li><a href="/wiki/Claude_Shannon" title="Claude Shannon">Claude Shannon</a></li> <li><a href="/wiki/Marvin_Minsky" title="Marvin Minsky">Marvin Minsky</a></li> <li><a href="/wiki/John_McCarthy_(computer_scientist)" title="John McCarthy (computer scientist)">John McCarthy</a></li> <li><a href="/wiki/Nathaniel_Rochester_(computer_scientist)" title="Nathaniel Rochester (computer scientist)">Nathaniel Rochester</a></li> <li><a href="/wiki/Allen_Newell" title="Allen Newell">Allen Newell</a></li> <li><a href="/wiki/Cliff_Shaw" title="Cliff Shaw">Cliff Shaw</a></li> <li><a href="/wiki/Herbert_A._Simon" title="Herbert A. Simon">Herbert A. Simon</a></li> <li><a href="/wiki/Oliver_Selfridge" title="Oliver Selfridge">Oliver Selfridge</a></li> <li><a href="/wiki/Frank_Rosenblatt" title="Frank Rosenblatt">Frank Rosenblatt</a></li> <li><a href="/wiki/Bernard_Widrow" title="Bernard Widrow">Bernard Widrow</a></li> <li><a href="/wiki/Joseph_Weizenbaum" title="Joseph Weizenbaum">Joseph Weizenbaum</a></li> <li><a href="/wiki/Seymour_Papert" title="Seymour Papert">Seymour Papert</a></li> <li><a href="/wiki/Seppo_Linnainmaa" title="Seppo Linnainmaa">Seppo Linnainmaa</a></li> <li><a href="/wiki/Paul_Werbos" title="Paul Werbos">Paul Werbos</a></li> <li><a href="/wiki/J%C3%BCrgen_Schmidhuber" title="Jürgen Schmidhuber">Jürgen Schmidhuber</a></li> <li><a href="/wiki/Yann_LeCun" title="Yann LeCun">Yann LeCun</a></li> <li><a href="/wiki/Geoffrey_Hinton" title="Geoffrey Hinton">Geoffrey Hinton</a></li> <li><a href="/wiki/John_Hopfield" title="John Hopfield">John Hopfield</a></li> <li><a href="/wiki/Yoshua_Bengio" title="Yoshua Bengio">Yoshua Bengio</a></li> <li><a href="/wiki/Lotfi_A._Zadeh" title="Lotfi A. Zadeh">Lotfi A. Zadeh</a></li> <li><a href="/wiki/Stephen_Grossberg" title="Stephen Grossberg">Stephen Grossberg</a></li> <li><a href="/wiki/Alex_Graves_(computer_scientist)" title="Alex Graves (computer scientist)">Alex Graves</a></li> <li><a href="/wiki/Andrew_Ng" title="Andrew Ng">Andrew Ng</a></li> <li><a href="/wiki/Fei-Fei_Li" title="Fei-Fei Li">Fei-Fei Li</a></li> <li><a href="/wiki/Alex_Krizhevsky" title="Alex Krizhevsky">Alex Krizhevsky</a></li> <li><a href="/wiki/Ilya_Sutskever" title="Ilya Sutskever">Ilya Sutskever</a></li> <li><a href="/wiki/Demis_Hassabis" title="Demis Hassabis">Demis Hassabis</a></li> <li><a href="/wiki/David_Silver_(computer_scientist)" title="David Silver (computer scientist)">David Silver</a></li> <li><a href="/wiki/Ian_Goodfellow" title="Ian Goodfellow">Ian Goodfellow</a></li> <li><a href="/wiki/Andrej_Karpathy" title="Andrej Karpathy">Andrej Karpathy</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Organizations</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Anthropic" title="Anthropic">Anthropic</a></li> <li><a href="/wiki/EleutherAI" title="EleutherAI">EleutherAI</a></li> <li><a href="/wiki/Google_DeepMind" title="Google DeepMind">Google DeepMind</a></li> <li><a href="/wiki/Hugging_Face" title="Hugging Face">Hugging Face</a></li> <li><a href="/wiki/Kuaishou" title="Kuaishou">Kuaishou</a></li> <li><a href="/wiki/Meta_AI" title="Meta AI">Meta AI</a></li> <li><a href="/wiki/Mila_(research_institute)" title="Mila (research institute)">Mila</a></li> <li><a href="/wiki/MiniMax_(company)" title="MiniMax (company)">MiniMax</a></li> <li><a href="/wiki/Mistral_AI" title="Mistral AI">Mistral AI</a></li> <li><a href="/wiki/MIT_Computer_Science_and_Artificial_Intelligence_Laboratory" title="MIT Computer Science and Artificial Intelligence Laboratory">MIT CSAIL</a></li> <li><a href="/wiki/OpenAI" title="OpenAI">OpenAI</a></li> <li><a href="/wiki/Runway_(company)" title="Runway (company)">Runway</a></li> <li><a href="/wiki/Stability_AI" title="Stability AI">Stability AI</a></li> <li><a href="/wiki/XAI_(company)" title="XAI (company)">xAI</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Architectures</th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Neural_Turing_machine" title="Neural Turing machine">Neural Turing machine</a></li> <li><a href="/wiki/Differentiable_neural_computer" title="Differentiable neural computer">Differentiable neural computer</a></li> <li><a href="/wiki/Transformer_(deep_learning_architecture)" title="Transformer (deep learning architecture)">Transformer</a> <ul><li><a href="/wiki/Vision_transformer" title="Vision transformer">Vision transformer (ViT)</a></li></ul></li> <li><a href="/wiki/Recurrent_neural_network" title="Recurrent neural network">Recurrent neural network (RNN)</a></li> <li><a href="/wiki/Long_short-term_memory" title="Long short-term memory">Long short-term memory (LSTM)</a></li> <li><a href="/wiki/Gated_recurrent_unit" title="Gated recurrent unit">Gated recurrent unit (GRU)</a></li> <li><a href="/wiki/Echo_state_network" title="Echo state network">Echo state network</a></li> <li><a href="/wiki/Multilayer_perceptron" title="Multilayer perceptron">Multilayer perceptron (MLP)</a></li> <li><a href="/wiki/Convolutional_neural_network" title="Convolutional neural network">Convolutional neural network (CNN)</a></li> <li><a href="/wiki/Residual_neural_network" title="Residual neural network">Residual neural network (RNN)</a></li> <li><a href="/wiki/Highway_network" title="Highway network">Highway network</a></li> <li><a href="/wiki/Mamba_(deep_learning_architecture)" title="Mamba (deep learning architecture)">Mamba</a></li> <li><a href="/wiki/Autoencoder" title="Autoencoder">Autoencoder</a></li> <li><a href="/wiki/Variational_autoencoder" title="Variational autoencoder">Variational autoencoder (VAE)</a></li> <li><a href="/wiki/Generative_adversarial_network" title="Generative adversarial network">Generative adversarial network (GAN)</a></li> <li><a href="/wiki/Graph_neural_network" title="Graph neural network">Graph neural network (GNN)</a></li></ul> </div></td></tr><tr><td class="navbox-abovebelow" colspan="2"><div> <ul><li><span class="noviewer" typeof="mw:File"><a href="/wiki/File:Symbol_portal_class.svg" class="mw-file-description" title="Portal"><img alt="" src="//upload.wikimedia.org/wikipedia/en/thumb/e/e2/Symbol_portal_class.svg/16px-Symbol_portal_class.svg.png" decoding="async" width="16" height="16" class="mw-file-element" srcset="//upload.wikimedia.org/wikipedia/en/thumb/e/e2/Symbol_portal_class.svg/23px-Symbol_portal_class.svg.png 1.5x, //upload.wikimedia.org/wikipedia/en/thumb/e/e2/Symbol_portal_class.svg/31px-Symbol_portal_class.svg.png 2x" data-file-width="180" data-file-height="185" /></a></span> Portals <ul><li><a href="/wiki/Portal:Technology" title="Portal:Technology">Technology</a></li></ul></li> <li><span class="noviewer" typeof="mw:File"><span title="Category"><img alt="" src="//upload.wikimedia.org/wikipedia/en/thumb/9/96/Symbol_category_class.svg/16px-Symbol_category_class.svg.png" decoding="async" width="16" height="16" class="mw-file-element" srcset="//upload.wikimedia.org/wikipedia/en/thumb/9/96/Symbol_category_class.svg/23px-Symbol_category_class.svg.png 1.5x, //upload.wikimedia.org/wikipedia/en/thumb/9/96/Symbol_category_class.svg/31px-Symbol_category_class.svg.png 2x" data-file-width="180" data-file-height="185" /></span></span> Categories <ul><li><a href="/wiki/Category:Artificial_neural_networks" title="Category:Artificial neural networks">Artificial neural networks</a></li> <li><a href="/wiki/Category:Machine_learning" title="Category:Machine learning">Machine learning</a></li></ul></li></ul> </div></td></tr></tbody></table></div> <div class="navbox-styles"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1129693374"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1236075235"></div><div role="navigation" class="navbox" aria-labelledby="Computer_graphics" style="padding:3px"><table class="nowraplinks mw-collapsible mw-collapsed navbox-inner" style="border-spacing:0;background:transparent;color:inherit"><tbody><tr><th scope="col" class="navbox-title" colspan="2"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1129693374"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1239400231"><div class="navbar plainlinks hlist navbar-mini"><ul><li class="nv-view"><a href="/wiki/Template:Computer_graphics" title="Template:Computer graphics"><abbr title="View this template">v</abbr></a></li><li class="nv-talk"><a href="/wiki/Template_talk:Computer_graphics" title="Template talk:Computer graphics"><abbr title="Discuss this template">t</abbr></a></li><li class="nv-edit"><a href="/wiki/Special:EditPage/Template:Computer_graphics" title="Special:EditPage/Template:Computer graphics"><abbr title="Edit this template">e</abbr></a></li></ul></div><div id="Computer_graphics" style="font-size:114%;margin:0 4em"><a href="/wiki/Computer_graphics_(computer_science)" title="Computer graphics (computer science)">Computer graphics</a></div></th></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="/wiki/Vector_graphics" title="Vector graphics">Vector graphics</a></th><td class="navbox-list-with-group navbox-list navbox-odd hlist" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Diffusion_curve" title="Diffusion curve">Diffusion curve</a></li> <li><a href="/wiki/Pixel" title="Pixel">Pixel</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="/wiki/2D_computer_graphics" title="2D computer graphics">2D graphics</a></th><td class="navbox-list-with-group navbox-list navbox-even hlist" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Alpha_compositing" title="Alpha compositing">Alpha compositing</a></li> <li><a href="/wiki/Layers_(digital_image_editing)" title="Layers (digital image editing)">Layers</a></li> <li><a class="mw-selflink selflink">Text-to-image</a></li></ul> </div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><th id="2.5D" scope="row" class="navbox-group" style="width:1%"><a href="/wiki/2.5D" title="2.5D">2.5D</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Isometric_video_game_graphics" title="Isometric video game graphics">Isometric graphics</a></li> <li><a href="/wiki/Mode_7" title="Mode 7">Mode 7</a></li> <li><a href="/wiki/Parallax_scrolling" title="Parallax scrolling">Parallax scrolling</a></li> <li><a href="/wiki/Ray_casting" title="Ray casting">Ray casting</a></li> <li><a href="/wiki/Skybox_(video_games)" title="Skybox (video games)">Skybox</a></li></ul> </div></td></tr></tbody></table><div> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="/wiki/3D_computer_graphics" title="3D computer graphics">3D graphics</a></th><td class="navbox-list-with-group navbox-list navbox-even hlist" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/3D_projection" title="3D projection">3D projection</a></li> <li><a href="/wiki/3D_rendering" title="3D rendering">3D rendering</a></li> <li>(<a href="/wiki/Image-based_modeling_and_rendering" title="Image-based modeling and rendering">Image-based</a></li> <li><a href="/wiki/Spectral_rendering" title="Spectral rendering">Spectral</a></li> <li><a href="/wiki/Unbiased_rendering" title="Unbiased rendering">Unbiased</a>)</li> <li><a href="/wiki/Aliasing" title="Aliasing">Aliasing</a></li> <li><a href="/wiki/Anisotropic_filtering" title="Anisotropic filtering">Anisotropic filtering</a></li> <li><a href="/wiki/Cel_shading" title="Cel shading">Cel shading</a></li> <li><a href="/wiki/Fluid_animation" title="Fluid animation">Fluid animation</a></li> <li><a href="/wiki/Computer_graphics_lighting" title="Computer graphics lighting">Lighting</a> <ul><li><a href="/wiki/Global_illumination" title="Global illumination">Global illumination</a></li></ul></li> <li><a href="/wiki/Hidden-surface_determination" title="Hidden-surface determination">Hidden-surface determination</a></li> <li><a href="/wiki/Polygon_mesh" title="Polygon mesh">Polygon mesh</a></li> <li>(<a href="/wiki/Triangle_mesh" title="Triangle mesh">Triangle mesh</a>)</li> <li><a href="/wiki/Shading" title="Shading">Shading</a> <ul><li><a href="/wiki/Deferred_shading" title="Deferred shading">Deferred</a></li></ul></li> <li><a href="/wiki/Surface_triangulation" title="Surface triangulation">Surface triangulation</a></li> <li><a href="/wiki/Wire-frame_model" title="Wire-frame model">Wire-frame model</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Concepts</th><td class="navbox-list-with-group navbox-list navbox-odd hlist" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Affine_transformation" title="Affine transformation">Affine transformation</a></li> <li><a href="/wiki/Back-face_culling" title="Back-face culling">Back-face culling</a></li> <li><a href="/wiki/Clipping_(computer_graphics)" title="Clipping (computer graphics)">Clipping</a></li> <li><a href="/wiki/Collision_detection" title="Collision detection">Collision detection</a></li> <li><a href="/wiki/Planar_projection" title="Planar projection">Planar projection</a></li> <li><a href="/wiki/Reflection_(computer_graphics)" title="Reflection (computer graphics)">Reflection</a></li> <li><a href="/wiki/Rendering_(computer_graphics)" title="Rendering (computer graphics)">Rendering</a> <ul><li><a href="/wiki/Beam_tracing" title="Beam tracing">Beam tracing</a></li> <li><a href="/wiki/Cone_tracing" title="Cone tracing">Cone tracing</a></li> <li><a href="/wiki/Checkerboard_rendering" title="Checkerboard rendering">Checkerboard rendering</a></li> <li><a href="/wiki/Ray_tracing_(graphics)" title="Ray tracing (graphics)">Ray tracing</a></li> <li><a href="/wiki/Path_tracing" title="Path tracing">Path tracing</a></li> <li><a href="/wiki/Ray_casting" title="Ray casting">Ray casting</a></li> <li><a href="/wiki/Scanline_rendering" title="Scanline rendering">Scanline rendering</a></li></ul></li> <li><a href="/wiki/Rotation_(mathematics)" title="Rotation (mathematics)">Rotation</a></li> <li><a href="/wiki/Scaling_(geometry)" title="Scaling (geometry)">Scaling</a></li> <li><a href="/wiki/Shadow_mapping" title="Shadow mapping">Shadow mapping</a></li> <li><a href="/wiki/Shadow_volume" title="Shadow volume">Shadow volume</a></li> <li><a href="/wiki/Shear_matrix" class="mw-redirect" title="Shear matrix">Shear matrix</a></li> <li><a href="/wiki/Shader" title="Shader">Shader</a></li> <li><a href="/wiki/Texel_(graphics)" title="Texel (graphics)">Texel</a></li> <li><a href="/wiki/Translation_(geometry)" title="Translation (geometry)">Translation</a></li> <li><a href="/wiki/Volume_rendering" title="Volume rendering">Volume rendering</a></li> <li><a href="/wiki/Voxel" title="Voxel">Voxel</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="/wiki/Graphics_software" title="Graphics software">Graphics software</a></th><td class="navbox-list-with-group navbox-list navbox-even hlist" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/List_of_3D_computer_graphics_software" title="List of 3D computer graphics software">3D computer graphics software</a> <ul><li><a href="/wiki/List_of_3D_animation_software" title="List of 3D animation software">animation</a></li> <li><a href="/wiki/List_of_3D_modeling_software" title="List of 3D modeling software">modeling</a></li> <li><a href="/wiki/List_of_3D_rendering_software" title="List of 3D rendering software">rendering</a></li></ul></li> <li><a href="/wiki/Raster_graphics_editor" title="Raster graphics editor">Raster graphics editors</a></li> <li><a href="/wiki/Comparison_of_vector_graphics_editors" title="Comparison of vector graphics editors">Vector graphics editors</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Algorithms</th><td class="navbox-list-with-group navbox-list navbox-odd hlist" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/List_of_computer_graphics_algorithms" class="mw-redirect" title="List of computer graphics algorithms">List of computer graphics algorithms</a></li></ul> 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