diff --git a/README.md b/README.md index 2956041..fdef6e8 100644 --- a/README.md +++ b/README.md @@ -10,54 +10,54 @@ A curated list of GAN & Deepfake papers and repositories. :heavy_check_mark: mea Tl;dr GANs containg two competing neural networks which iteratively generate new data with the same statistics as the training set. ### Unconditional GANs -+ Vanilla GAN: Generative Adversarial Networks, [[paper]](https://arxiv.org/abs/1406.2661), [[github]](https://github.com/eriklindernoren/PyTorch-GAN/tree/master/implementations/gan) -+ DCGAN: Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks, [[paper]](https://arxiv.org/abs/1511.06434), [[github]](https://github.com/carpedm20/DCGAN-tensorflow) -+ WGAN: Wasserstein GAN, [[paper]](https://arxiv.org/abs/1701.07875), [[github]](https://github.com/martinarjovsky/WassersteinGAN) -+ WGAN-GP: Improved Training of Wasserstein GANs, [[paper]](https://arxiv.org/pdf/1704.00028.pdf), [[github]](https://github.com/caogang/wgan-gp) -+ RGAN: The relativistic discriminator: a key element missing from standard GAN, [[paper]](https://arxiv.org/abs/1807.00734), [[github]](https://github.com/AlexiaJM/RelativisticGAN) ++ :heavy_check_mark: Vanilla GAN: Generative Adversarial Networks, [[paper]](https://arxiv.org/abs/1406.2661), [[github]](https://github.com/eriklindernoren/PyTorch-GAN/tree/master/implementations/gan) ++ :heavy_check_mark: DCGAN: Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks, [[paper]](https://arxiv.org/abs/1511.06434), [[github]](https://github.com/carpedm20/DCGAN-tensorflow) ++ :heavy_check_mark: WGAN: Wasserstein GAN, [[paper]](https://arxiv.org/abs/1701.07875), [[github]](https://github.com/martinarjovsky/WassersteinGAN) ++ :heavy_check_mark: WGAN-GP: Improved Training of Wasserstein GANs, [[paper]](https://arxiv.org/pdf/1704.00028.pdf), [[github]](https://github.com/caogang/wgan-gp) ++ :heavy_check_mark: RGAN: The relativistic discriminator: a key element missing from standard GAN, [[paper]](https://arxiv.org/abs/1807.00734), [[github]](https://github.com/AlexiaJM/RelativisticGAN) ### Conditional GANs -+ CGAN: Conditional Generative Adversarial Nets, [[paper]](https://arxiv.org/abs/1411.1784), [[github]](https://github.com/eriklindernoren/PyTorch-GAN/blob/master/implementations/cgan/cgan.py) -+ ACGAN: Conditional Image Synthesis With Auxiliary Classifier GANs, [[paper]](https://arxiv.org/abs/1610.09585), [[github]](https://github.com/eriklindernoren/PyTorch-GAN/blob/master/implementations/acgan/acgan.py) ++ :heavy_check_mark: CGAN: Conditional Generative Adversarial Nets, [[paper]](https://arxiv.org/abs/1411.1784), [[github]](https://github.com/eriklindernoren/PyTorch-GAN/blob/master/implementations/cgan/cgan.py) ++ :heavy_check_mark: ACGAN: Conditional Image Synthesis With Auxiliary Classifier GANs, [[paper]](https://arxiv.org/abs/1610.09585), [[github]](https://github.com/eriklindernoren/PyTorch-GAN/blob/master/implementations/acgan/acgan.py) ### Image-to-Image Translation -+ CycleGAN: Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks, [[paper]](https://arxiv.org/abs/1703.10593), [[github]](https://github.com/junyanz/CycleGAN) -+ StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation, [[paper]](https://arxiv.org/abs/1711.09020), [[github]](https://github.com/yunjey/stargan) -+ Pix2Pix: Image-to-Image Translation with Conditional Adversarial Nets, [[paper]](https://arxiv.org/abs/1611.07004), [[github]](https://github.com/phillipi/pix2pix) ++ :heavy_check_mark: CycleGAN: Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks, [[paper]](https://arxiv.org/abs/1703.10593), [[github]](https://github.com/junyanz/CycleGAN) ++ :heavy_check_mark: StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation, [[paper]](https://arxiv.org/abs/1711.09020), [[github]](https://github.com/yunjey/stargan) ++ :heavy_check_mark: Pix2Pix: Image-to-Image Translation with Conditional Adversarial Nets, [[paper]](https://arxiv.org/abs/1611.07004), [[github]](https://github.com/phillipi/pix2pix) ### Volumetric (3D) Generation -+ 3DGAN: Learning a Probabilistic Latent Space of Object Shapes ++ :heavy_check_mark: 3DGAN: Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling, [[paper]](http://3dgan.csail.mit.edu/papers/3dgan_nips.pdf), [[github]](https://github.com/enochkan/3dgan-keras) -+ Inverse Graphics GAN: Inverse Graphics GAN - Learning to Generate 3D Shapes from Unstructured 2D Data, [[paper]](https://arxiv.org/pdf/2002.12674.pdf), [[github]](https://github.com/BraneShop/showreel/issues/504) ++ :heavy_check_mark: Inverse Graphics GAN: Inverse Graphics GAN - Learning to Generate 3D Shapes from Unstructured 2D Data, [[paper]](https://arxiv.org/pdf/2002.12674.pdf), [[github]](https://github.com/BraneShop/showreel/issues/504) ## Applications using GANs ### Anime generator + Towards the Automatic Anime Characters Creation with Generative Adversarial Networks, [[paper]](https://arxiv.org/pdf/1708.05509) -+ [Project] Keras-GAN-Animeface-Character, [[github]](https://github.com/forcecore/Keras-GAN-Animeface-Character) ++ :heavy_check_mark: [Project] Keras-GAN-Animeface-Character, [[github]](https://github.com/forcecore/Keras-GAN-Animeface-Character) ### Interactive Image generation -+ Generative Visual Manipulation on the Natural Image Manifold, [[paper]](https://arxiv.org/pdf/1609.03552), [[github]](https://github.com/junyanz/iGAN) -+ Neural Photo Editing with Introspective Adversarial Networks, [[paper]](http://arxiv.org/abs/1609.07093), [[github]](https://github.com/ajbrock/Neural-Photo-Editor) ++ :heavy_check_mark: Generative Visual Manipulation on the Natural Image Manifold, [[paper]](https://arxiv.org/pdf/1609.03552), [[github]](https://github.com/junyanz/iGAN) ++ :heavy_check_mark: Neural Photo Editing with Introspective Adversarial Networks, [[paper]](http://arxiv.org/abs/1609.07093), [[github]](https://github.com/ajbrock/Neural-Photo-Editor) ### 3D Object generation + 3D Shape Induction from 2D Views of Multiple Objects, [[paper]](https://arxiv.org/pdf/1612.05872.pdf) -+ Parametric 3D Exploration with Stacked Adversarial Networks, [[github]](https://github.com/maxorange/pix2vox), [[youtube]](https://www.youtube.com/watch?v=ITATOXVvWEM) -+ Fully Convolutional Refined Auto-Encoding Generative Adversarial Networks for 3D Multi Object Scenes, [[github]](https://github.com/yunishi3/3D-FCR-alphaGAN), [[blog]](https://becominghuman.ai/3d-multi-object-gan-7b7cee4abf80) ++ :heavy_check_mark: Parametric 3D Exploration with Stacked Adversarial Networks, [[github]](https://github.com/maxorange/pix2vox), [[youtube]](https://www.youtube.com/watch?v=ITATOXVvWEM) ++ :heavy_check_mark: Fully Convolutional Refined Auto-Encoding Generative Adversarial Networks for 3D Multi Object Scenes, [[github]](https://github.com/yunishi3/3D-FCR-alphaGAN), [[blog]](https://becominghuman.ai/3d-multi-object-gan-7b7cee4abf80) ### Super-resolution -+ Image super-resolution through deep learning, [[github]](https://github.com/david-gpu/srez) -+ Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network, [[paper]](https://arxiv.org/abs/1609.04802), [[github]](https://github.com/leehomyc/Photo-Realistic-Super-Resoluton) ++ :heavy_check_mark: Image super-resolution through deep learning, [[github]](https://github.com/david-gpu/srez) ++ :heavy_check_mark: Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network, [[paper]](https://arxiv.org/abs/1609.04802), [[github]](https://github.com/leehomyc/Photo-Realistic-Super-Resoluton) + High-Quality Face Image Super-Resolution Using Conditional Generative Adversarial Networks, [[paper]](https://arxiv.org/pdf/1707.00737.pdf) -+ Analyzing Perception-Distortion Tradeoff using Enhanced Perceptual Super-resolution Network, [[paper]](https://arxiv.org/pdf/1811.00344.pdf), [[github]](https://github.com/subeeshvasu/2018_subeesh_epsr_eccvw) ++ :heavy_check_mark: Analyzing Perception-Distortion Tradeoff using Enhanced Perceptual Super-resolution Network, [[paper]](https://arxiv.org/pdf/1811.00344.pdf), [[github]](https://github.com/subeeshvasu/2018_subeesh_epsr_eccvw) ### Image Inpainting (hole filling) -+ Context Encoders: Feature Learning by Inpainting, [[paper]](https://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Pathak_Context_Encoders_Feature_CVPR_2016_paper.pdf), [[github]](https://github.com/pathak22/context-encoder) -+ Semantic Image Inpainting with Perceptual and Contextual Losses, [[paper]](https://arxiv.org/abs/1607.07539), [[github]](https://github.com/bamos/dcgan-completion.tensorflow) -+ Generative Face Completion, [[paper]](https://drive.google.com/file/d/0B8_MZ8a8aoSeenVrYkpCdnFRVms/edit), [[github]](https://github.com/Yijunmaverick/GenerativeFaceCompletion) ++ :heavy_check_mark: Context Encoders: Feature Learning by Inpainting, [[paper]](https://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Pathak_Context_Encoders_Feature_CVPR_2016_paper.pdf), [[github]](https://github.com/pathak22/context-encoder) ++ :heavy_check_mark: Semantic Image Inpainting with Perceptual and Contextual Losses, [[paper]](https://arxiv.org/abs/1607.07539), [[github]](https://github.com/bamos/dcgan-completion.tensorflow) ++ :heavy_check_mark: Generative Face Completion, [[paper]](https://drive.google.com/file/d/0B8_MZ8a8aoSeenVrYkpCdnFRVms/edit), [[github]](https://github.com/Yijunmaverick/GenerativeFaceCompletion) ### Medical Image Segmentation -+ Vox2Vox: 3D-GAN for Brain Tumor Segmentation, [[paper]](https://arxiv.org/abs/2003.13653), [[github]](https://github.com/enochkan/vox2vox) ++ :heavy_check_mark: Vox2Vox: 3D-GAN for Brain Tumor Segmentation, [[paper]](https://arxiv.org/abs/2003.13653), [[github]](https://github.com/enochkan/vox2vox) + SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation, [[paper]](https://arxiv.org/abs/1706.01805) + Generative Adversarial Neural Networks for Pigmented and Non-Pigmented Skin Lesions Detection in Clinical Images, [[paper]](https://ieeexplore.ieee.org/document/7968584/) @@ -65,23 +65,23 @@ via 3D Generative-Adversarial Modeling, [[paper]](http://3dgan.csail.mit.edu/pap Tl;dr Deepfakes are fake videos or audio recordings that look and sound just like the real thing. ### CNN-based Face-swapping -+ Fast Face-swap Using Convolutional Neural Networks, [[paper]](https://arxiv.org/abs/1611.09577), [[github]](https://github.com/deepfakes/faceswap#overview) -+ DeepFaceLab: A simple, flexible and extensible face ++ :heavy_check_mark: Fast Face-swap Using Convolutional Neural Networks, [[paper]](https://arxiv.org/abs/1611.09577), [[github]](https://github.com/deepfakes/faceswap#overview) ++ :heavy_check_mark: DeepFaceLab: A simple, flexible and extensible face swapping framework, [[paper]](https://arxiv.org/pdf/2005.05535v4.pdf), [[github]](https://github.com/iperov/DeepFaceLab) ### GAN-based Face-swapping -+ Fewshot Face Translation GAN, [[github]](https://github.com/shaoanlu/fewshot-face-translation-GAN) ++ :heavy_check_mark: Fewshot Face Translation GAN, [[github]](https://github.com/shaoanlu/fewshot-face-translation-GAN) + Faceswap-GAN, [[github]](https://github.com/shaoanlu/faceswap-GAN) -+ AttGAN: Facial Attribute Editing by Only ++ :heavy_check_mark: AttGAN: Facial Attribute Editing by Only Changing What You Want, [[paper]](http://vipl.ict.ac.cn/uploadfile/upload/2019112511573287.pdf), [[github]](https://github.com/LynnHo/AttGAN-Tensorflow) + MulGAN: Facial Attribute Editing by Exemplar, [[paper]](https://arxiv.org/abs/1912.12396) -+ MaskGAN: Towards Diverse and Interactive Facial Image Manipulation, [[paper]](https://arxiv.org/abs/1907.11922), [[github]](https://github.com/switchablenorms/CelebAMask-HQ) -+ StarGAN v2: Diverse Image Synthesis for Multiple Domains, [[paper]](https://arxiv.org/abs/1912.01865), [[github]](https://github.com/clovaai/stargan-v2) ++ :heavy_check_mark: MaskGAN: Towards Diverse and Interactive Facial Image Manipulation, [[paper]](https://arxiv.org/abs/1907.11922), [[github]](https://github.com/switchablenorms/CelebAMask-HQ) ++ :heavy_check_mark: StarGAN v2: Diverse Image Synthesis for Multiple Domains, [[paper]](https://arxiv.org/abs/1912.01865), [[github]](https://github.com/clovaai/stargan-v2) ## Deepfake Detection ### CNN-based methods -+ MesoNet [[paper]](https://arxiv.org/abs/1809.00888), [[github]](https://github.com/HongguLiu/MesoNet-Pytorch) ++ :heavy_check_mark: MesoNet [[paper]](https://arxiv.org/abs/1809.00888), [[github]](https://github.com/HongguLiu/MesoNet-Pytorch) + Detecting Deep-Fake Videos from Phoneme-Viseme Mismatches, [[paper]](https://www.ohadf.com/papers/AgarwalFaridFriedAgrawala_CVPRW2020.pdf) + Deep Fake Image Detection Based on Pairwise Learning, [[paper]](https://www.mdpi.com/2076-3417/10/1/370)