AdversarialNetsPapers
- The First paper
- Unclassified
- Ensemble
- Clustering
- Image Inpainting
- Joint Probability
- Super-Resolution
- Disocclusion
- Semantic Segmentation
- Object Detection
- RNN
- Conditional adversarial
- Video Prediction
- Texture Synthesis & style transfer
- GAN Theory
- 3D
- MUSIC
- Face Generative and Editing
- For discrete distributions
- Adversarial Examples
The classical Papers about adversarial nets
The First paper
Unclassified
[ ] [Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks] [Paper][Code]
[ ] [Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks] [Paper][Code](Gan with convolutional networks)(ICLR)
- [ ] [Generating Images with Perceptual Similarity Metrics based on Deep Networks] [Paper]
[ ] [Generating images with recurrent adversarial networks] [Paper][Code]
[ ] [Generative Visual Manipulation on the Natural Image Manifold] [Paper][Code]
[ ] [Generative Adversarial Text to Image Synthesis] [Paper][Code][code]
[ ] [Adversarial Training for Sketch Retrieval] [Paper]
[ ] [Generative Image Modeling using Style and Structure Adversarial Networks] [Paper][Code]
[ ] [Generative Adversarial Networks as Variational Training of Energy Based Models] [Paper](ICLR 2017)
[ ] [Adversarial Training Methods for Semi-Supervised Text Classification] [Paper][Note]( Ian Goodfellow Paper)
[ ] [Learning from Simulated and Unsupervised Images through Adversarial Training] [Paper][code](Apple paper)
[ ] [Synthesizing the preferred inputs for neurons in neural networks via deep generator networks] [Paper][Code]
[ ] [SalGAN: Visual Saliency Prediction with Generative Adversarial Networks] [Paper][Code]
[ ] [Adversarial Feature Learning] [Paper]
Ensemble
- [ ] [AdaGAN: Boosting Generative Models] [Paper][[Code]](Google Brain)
Clustering
- [ ] [Unsupervised Learning Using Generative Adversarial Training And Clustering] [Paper][Code](ICLR)
- [ ] [Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks] [Paper](ICLR)
Image Inpainting
[ ] [Semantic Image Inpainting with Perceptual and Contextual Losses] [Paper][Code]
[ ] [Context Encoders: Feature Learning by Inpainting] [Paper][Code]
[ ] [Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks] [Paper]
Joint Probability
Super-Resolution
[ ] [Image super-resolution through deep learning ][Code](Just for face dataset)
[ ] [Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network] [Paper][Code](Using Deep residual network)
[ ] [EnhanceGAN] [Docs][[Code]]
Disocclusion
- [ ] [Robust LSTM-Autoencoders for Face De-Occlusion in the Wild] [Paper]
Semantic Segmentation
- [ ] [Semantic Segmentation using Adversarial Networks] [Paper](soumith's paper)
Object Detection
[ ] [Perceptual generative adversarial networks for small object detection] [[Paper]](Submitted)
[ ] [A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection] [Paper][code](CVPR2017)
RNN
Conditional adversarial
[ ] [InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets] [Paper][Code]
[ ] [Conditional Image Synthesis With Auxiliary Classifier GANs] [Paper][Code](GoogleBrain ICLR 2017)
[ ] [Invertible Conditional GANs for image editing] [Paper][Code]
[ ] [Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space] [Paper][Code]
[ ] [StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks] [Paper][Code]
Video Prediction
[ ] [Deep multi-scale video prediction beyond mean square error] [Paper][Code](Yann LeCun's paper)
[ ] [Unsupervised Learning for Physical Interaction through Video Prediction] [Paper](Ian Goodfellow's paper)
[ ] [Generating Videos with Scene Dynamics] [Paper][Web][Code]
Texture Synthesis & style transfer
- [ ] [Precomputed real-time texture synthesis with markovian generative adversarial networks] [Paper][Code](ECCV 2016)
Image translation
[ ] [UNSUPERVISED CROSS-DOMAIN IMAGE GENERATION] [Paper][Code]
[ ] [Image-to-image translation using conditional adversarial nets] [Paper][Code][Code]
[ ] [Learning to Discover Cross-Domain Relations with Generative Adversarial Networks] [Paper][Code]
[ ] [Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks] [Paper][Code]
[ ] [Unsupervised Image-to-Image Translation with Generative Adversarial Networks] [Paper]
[ ] [Unsupervised Image-to-Image Translation Networks] [Paper]
GAN Theory
[ ] [Energy-based generative adversarial network] [Paper][Code](Lecun paper)
[ ] [Improved Techniques for Training GANs] [Paper][Code](Goodfellow's paper)
[ ] [Mode Regularized Generative Adversarial Networks] [Paper](Yoshua Bengio , ICLR 2017)
[ ] [Improving Generative Adversarial Networks with Denoising Feature Matching] [Paper][Code](Yoshua Bengio , ICLR 2017)
[ ] [Mode Regularized Generative Adversarial Networkss] [Paper]( Yoshua Bengio's paper)
[ ] [How to train Gans] [Docu]
[ ] [Towards Principled Methods for Training Generative Adversarial Networks] [Paper](ICLR 2017)
[ ] [Unrolled Generative Adversarial Networks] [Paper][Code](ICLR 2017)
[ ] [Least Squares Generative Adversarial Networks] [Paper][Code]
[ ] [Improved Training of Wasserstein GANs] [Paper][Code](The improve of wgan)
[ ] [Towards Principled Methods for Training Generative Adversarial Networks] [Paper]
3D
- [ ] [Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling] [Paper][Web][code](2016 NIPS)
MUSIC
- [ ] [MidiNet: A Convolutional Generative Adversarial Network for Symbolic-domain Music Generation using 1D and 2D Conditions] [Paper][HOMEPAGE]
Face Generative and Editing
[ ] [Autoencoding beyond pixels using a learned similarity metric] [Paper][code]
[ ] [Coupled Generative Adversarial Networks] [Paper][Caffe Code][Tensorflow Code](NIPS)
[ ] [Invertible Conditional GANs for image editing] [Paper][Code]
[ ] [Learning Residual Images for Face Attribute Manipulation] [Paper]
[ ] [Neural Photo Editing with Introspective Adversarial Networks] [Paper][Code](ICLR 2017)
For discrete distributions
[ ] [Maximum-Likelihood Augmented Discrete Generative Adversarial Networks] [Paper]
[ ] [Boundary-Seeking Generative Adversarial Networks] [Paper]
[ ] [GANS for Sequences of Discrete Elements with the Gumbel-softmax Distribution] [Paper]
Adversarial Examples
- [ ] [SafetyNet: Detecting and Rejecting Adversarial Examples Robustly] [Paper]
Project
[ ] [cleverhans] [Code](A library for benchmarking vulnerability to adversarial examples)
[ ] [reset-cppn-gan-tensorflow] [Code](Using Residual Generative Adversarial Networks and Variational Auto-encoder techniques to produce high resolution images)
[ ] [HyperGAN] [Code](Open source GAN focused on scale and usability)
Blogs
Author | Address |
---|---|
inFERENCe | Adversarial network |
inFERENCe | InfoGan |
distill | Deconvolution and Image Generation |
yingzhenli | Gan theory |
OpenAI | Generative model |
Other
[ ] [1] http://www.iangoodfellow.com/slides/2016-12-04-NIPS.pdf (NIPS Goodfellow Slides)[Chinese Trans][details]
[ ] [2] [PDF](NIPS Lecun Slides)