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added "Applications using GANs"
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Nikunj Dobariya
2020-11-06 10:47:56 +05:30
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@@ -23,6 +23,32 @@ A curated list of GAN & Deepfake papers and repositories.
* [https://github.com/jacobgil/keras-dcgan]
* [https://github.com/eriklindernoren/Keras-GAN/blob/master/dcgan/dcgan.py]
* [https://github.com/mitchelljy/DCGAN-Keras]
## 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)
### 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)
### 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)
### 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)
+ 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)
### 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)
## Deepfakes
- Faceswap [(paper)](https://arxiv.org/pdf/2005.05535v4.pdf)
@@ -56,4 +82,4 @@ A curated list of GAN & Deepfake papers and repositories.
- ["SwapMe and Faceswap" dataset](https://www.sciencedirect.com/science/article/pii/S0957417419302350?via%3Dihub)
- ["Fake Faces in the Wild (FFW) dataset](http://ali.khodabakhsh.org/research/ffw/)
- [Tampered Face (TAMFA) Dataset](https://www.sciencedirect.com/science/article/pii/S0957417419302350?via%3Dihub)
- [Celeb-DF(v2) Celebrity Deepfake Dataset](http://www.cs.albany.edu/~lsw/celeb-deepfakeforensics.html)
- [Celeb-DF(v2) Celebrity Deepfake Dataset](http://www.cs.albany.edu/~lsw/celeb-deepfakeforensics.html)