{"id":13738603,"url":"https://github.com/The-AI-Summer/GANs-in-Computer-Vision","last_synced_at":"2025-05-08T16:34:53.978Z","repository":{"id":42517628,"uuid":"272206315","full_name":"The-AI-Summer/GANs-in-Computer-Vision","owner":"The-AI-Summer","description":"GANs in computer vision AI Summer article series","archived":false,"fork":false,"pushed_at":"2020-10-07T14:14:03.000Z","size":777,"stargazers_count":68,"open_issues_count":0,"forks_count":12,"subscribers_count":6,"default_branch":"master","last_synced_at":"2024-08-04T03:13:02.723Z","etag":null,"topics":["adverserial","computer-vision","deep-learning","gan","gans","learning"],"latest_commit_sha":null,"homepage":"https://theaisummer.com/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/The-AI-Summer.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2020-06-14T13:20:05.000Z","updated_at":"2024-06-11T13:21:32.000Z","dependencies_parsed_at":"2022-09-21T00:20:33.061Z","dependency_job_id":null,"html_url":"https://github.com/The-AI-Summer/GANs-in-Computer-Vision","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/The-AI-Summer%2FGANs-in-Computer-Vision","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/The-AI-Summer%2FGANs-in-Computer-Vision/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/The-AI-Summer%2FGANs-in-Computer-Vision/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/The-AI-Summer%2FGANs-in-Computer-Vision/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/The-AI-Summer","download_url":"https://codeload.github.com/The-AI-Summer/GANs-in-Computer-Vision/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":224746952,"owners_count":17363159,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["adverserial","computer-vision","deep-learning","gan","gans","learning"],"created_at":"2024-08-03T03:02:28.888Z","updated_at":"2024-11-15T07:31:33.668Z","avatar_url":"https://github.com/The-AI-Summer.png","language":"Python","funding_links":[],"categories":["Python","100 + 𝗔𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗟𝗶𝘀𝘁 𝘄𝗶𝘁𝗵 𝗰𝗼𝗱𝗲","📚 Project Purpose"],"sub_categories":["Machine Learning (Intermediate-Level"],"readme":"\u003cdiv align=\"center\"\u003e\n\u003cimg src=\"cover/ebook-cover.png\" width=884 height=512/\u003e\n\u003c/div\u003e\n\n\n# GANs in Computer Vision\n\n\n## Abstract \nIn this article-series we are reviewing the most fundamental works of Generative Adversarial Networks in Computer Vision. We start from the very beginning from concepts such as **generative learning, adversarial learning**. We provide some code and illustrations for educational purposes. The goal is to focus on the intuition of the models, by tackling the multiple problems that arise when training a GAN. We have thoroughly analyzed more than **20 papers in 6 different articles in a chronological order**. We will continue to update the GAN series, based on the newer publications or older ones that we skipped. We do hope that this series will provide you a big overview of the field, so that you will not need to read all the literature by yourself, independent of your background on GANs.    \n\n#### Update 07/2020: free ebook is realesed in the [AI summer website](https://theaisummer.com/gans-computer-vision-ebook/)\n\n## Introduction to generative learning (part 1)\n\nLink to the article: [Introduction to generative learning - part 1](https://theaisummer.com/gan-computer-vision/) \n\n\n|First Author|Published|Title|Code|Conference/Journal|\n|---|---|---|---|---|\n|Ian J. Goodfellow| 10 Jun 2014 | [Generative Adversarial Networks](http://papers.nips.cc/paper/5423-generative-adversarial-nets)|[PyTorch](https://github.com/black0017/3D-GAN-pytorch)|NIPS|\n|Mehdi Mirza|6 Nov 2014|[Conditional Generative Adversarial Nets](https://arxiv.org/abs/1411.1784)|[Tensorflow](https://github.com/znxlwm/tensorflow-MNIST-cGAN-cDCGAN)|arXiv|\n|Alec Radford|19 Nov 2015|[Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks](https://arxiv.org/abs/1511.06434)|[Tensorflow](https://github.com/carpedm20/DCGAN-tensorflow)|arXiv|\n|Xi Chen|12 Jun 2016|[InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets](https://arxiv.org/abs/1606.03657)| [Tensorflow](https://github.com/openai/InfoGAN)|NIPS|\n|Tim Salimans|10 Jun 2016|[Improved Techniques for Training GANs](https://arxiv.org/abs/1606.03498)|[Tensorflow](https://github.com/openai/improved-gan)|NIPS|\n\n\n## Conditional image synthesis and 3D object generation (part2)\n\nLink to the article: [Conditional image synthesis and 3D object generation - part 2](https://theaisummer.com/gan-computer-vision-object-generation/) \n\n|First Author|Published|Title|Code|Conference/Journal|\n|---|---|---|---|---|\n|Augustus Odena|30 Oct 2016|[Conditional Image Synthesis With Auxiliary Classifier GANs](https://arxiv.org/abs/1610.09585)|[Keras](https://github.com/lukedeo/keras-acgan)   [TF](https://github.com/buriburisuri/ac-gan) [PyTorch ](https://github.com/eriklindernoren/PyTorch-GAN)|arXiv|\n|Jiajun Wu|24 Oct 2016 | [Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling](https://arxiv.org/abs/1610.07584)|[PyTorch](https://github.com/black0017/3D-GAN-pytorch)|NIPS|\n|Zinan Lin|12 Dec 2017|[PacGAN: The power of two samples in generative adversarial networks](http://papers.nips.cc/paper/7423-pacgan-the-power-of-two-samples-in-generative-adversarial-networks)|[TF](https://github.com/fjxmlzn/PacGAN)|NIPS|\n|Phillip Isola|21 Nov 2016 |[Image-to-Image Translation with Conditional Adversarial Networks](https://arxiv.org/abs/1611.07004)|[TF](https://github.com/affinelayer/Pix2Pix-tensorflow) [PyTorch ](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix)|arXiv|\n|Jun-Yan Zhu|30 Mar 2017|[Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks](https://arxiv.org/abs/1703.10593)|[TF](https://github.com/junyanz/CycleGAN) [PyTorch ](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix)|arXiv|\n\n\n\n\n## Improved training with Wasserstein distance, game theory control and progressively growing schemes (part3)\n\nLink to the article: [Improved training with Wasserstein distance, game theory control and progressively growing schemes - part3 ](https://theaisummer.com/gan-computer-vision-incremental-training/) \n\n|First Author|Published|Title|Code|Conference/Journal|\n|---|---|---|---|---|\n|Martin Arjovsky|  26 Jan 2017 | [Wasserstein GAN](http://proceedings.mlr.press/v70/arjovsky17a.html) | [TF](https://github.com/LynnHo/DCGAN-LSGAN-WGAN-GP-DRAGAN-Tensorflow-2) [PyTorch ](https://github.com/martinarjovsky/WassersteinGAN) | PMLR|\n|David Berthelot|  31 Mar 2017 | [BEGAN: Boundary Equilibrium Generative Adversarial Networks](https://arxiv.org/abs/1703.10717) | [TF](https://github.com/junyanz/CycleGAN) [PyTorch ](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix) | NIPS|\n|Tero Karras|  27 Oct 2017 | [Progressive Growing of GANs for Improved Quality, Stability, and Variation](https://arxiv.org/abs/1710.10196) | [TF](https://github.com/tkarras/progressive_growing_of_gans) [PyTorch ](https://github.com/facebookresearch/pytorch_GAN_zoo) | ICLR|\n\n## 2K image and video synthesis, and large-scale class-conditional image generation (part 4)\n\nLink to the article: [2K image and video synthesis, and large-scale class-conditional image generation - part4 ](https://theaisummer.com/gan-computer-vision-video-synthesis/) \n\n\n|First Author|Published|Title|Code|Conference/Journal|\n|---|---|---|---|---|\n|Ting-Chun Wang| 30 Nov 2017 | [High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs](https://arxiv.org/abs/1711.11585) | [PyTorch ](https://github.com/NVIDIA/pix2pixHD) | CVPR |\n| Ting-Chun Wang | 20 Aug 2018 | [Video-to-Video Synthesis](https://arxiv.org/abs/1711.11585) | [PyTorch ](https://github.com/NVIDIA/vid2vid) | NIPS |\n|Andrew Brock| 28 Sep 2018 | [Large Scale GAN Training for High Fidelity Natural Image Synthesis](https://arxiv.org/abs/1809.11096) | [TF](https://github.com/taki0112/BigGAN-Tensorflow) [PyTorch ](https://github.com/ajbrock/BigGAN-PyTorch) | ICLR |\n\n\n## Self-supervised adversarial training and high-resolution image synthesis with style incorporation (part 5)\n\nLink to the article: [Self-supervised adversarial training and high-resolution image synthesis with style incorporation part 5](https://theaisummer.com/gan-computer-vision-style-gan/) \n\n\n|First Author|Published|Title|Code|Conference/Journal|\n|---|---|---|---|---|\n|Ting Chen|  27 Nov 2018  | [Self-Supervised GANs via Auxiliary Rotation Loss](https://arxiv.org/abs/1811.11212) | [PyTorch ](https://github.com/vandit15/Self-Supervised-Gans-Pytorch) | CVPR |\n| Tero Karras | 12 Dec 2018 | [A Style-Based Generator Architecture for Generative Adversarial Networks](https://arxiv.org/abs/1812.04948) | [TF](https://github.com/NVlabs/stylegan) [PyTorch ](https://github.com/facebookresearch/pytorch_GAN_zoo) | CVPR |\n\n\n## Semantic image synthesis and learning a generative model from a single image (part 6)\n\nLink to the article: [Semantic image synthesis and learning a generative model from a single image part 6](https://theaisummer.com/gan-computer-vision-semantic-synthesis/) \n\n\n|First Author|Published|Title|Code|Conference/Journal|\n|---|---|---|---|---|\n|Taesung Park|  18 Mar 2019| [Semantic Image Synthesis with Spatially-Adaptive Normalization](https://arxiv.org/abs/1903.07291) | [PyTorch](https://github.com/NVlabs/SPADE) | CVPR |\n|Tamar Rott Shaham|  2 May 2019| [SinGAN: Learning a Generative Model from a Single Natural Image](https://arxiv.org/abs/1903.07291) | [PyTorch](https://github.com/tamarott/SinGAN) | ICCV |\n\n\n\n##  Other awesome GAN repositories and resources\n\n- Play with Generative Adversarial Networks (GANs) in your [browser](https://poloclub.github.io/ganlab/)! \n- The [GAN Zoo](https://github.com/hindupuravinash/the-gan-zoo): A  list of all named GANs\n- Facebook AI [GAN repo](https://github.com/facebookresearch/pytorch_GAN_zoo): A mix of GAN **implementations** including progressive growing \n- **PyTorch** multiple [implementations](https://github.com/eriklindernoren/PyTorch-GAN) of Generative Adversarial Networks\n- Another **PyTorch** GAN [library](https://github.com/kwotsin/mimicry) that reproduces research results for popular GANs (CVPR 2020 Workshop)\n- **Keras** [implementations](https://github.com/eriklindernoren/Keras-GAN) of Generative Adversarial Networks. \n- **Open Questions** about Generative Adversarial Networks, Augustus Odena, [Distill](https://distill.pub/2019/gan-open-problems/) 2019\n- Generative Adversarial Networks in Computer Vision: [A Survey and Taxonomy](https://arxiv.org/abs/1906.01529)\n- [From GAN to WGAN](https://lilianweng.github.io/lil-log/2017/08/20/from-GAN-to-WGAN.html), Lil'Log blog 2017\n\n\n\n## The article-series can be cited as:\n\n\n```python\n@article{adaloglou2020gans,\n    title   = \"GANs in computer vision\",\n    author  = \"Adaloglou, Nikolas and Karagiannakos, Sergios \",\n    journal = \"https://theaisummer.com/\",\n    year    = \"2020\",\n    url     = \"https://theaisummer.com/gan-computer-vision/\"\n  }\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FThe-AI-Summer%2FGANs-in-Computer-Vision","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FThe-AI-Summer%2FGANs-in-Computer-Vision","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FThe-AI-Summer%2FGANs-in-Computer-Vision/lists"}