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