摘要：在這里匯總了一個現在和經常使用的論文，所有文章都鏈接到了上面。如果你對感興趣，可以訪問這個專題。作者微信號簡書地址是一個專注于算法實戰的平臺，從基礎的算法到人工智能算法都有設計。加入實戰微信群，實戰群，算法微信群，算法群。

作者：chen_h
微信號 & QQ：862251340
微信公眾號：coderpai
簡書地址：https://www.jianshu.com/p/b7f...

關于生成對抗網絡（GAN）的新論文每周都會出現很多，跟蹤發現他們非常難，更不用說去辨別那些研究人員對 GAN 各種奇奇怪怪，令人難以置信的創造性的命名！當然，你可以通過閱讀 OpanAI 的博客或者 KDNuggets 中的概述性閱讀教程，了解更多的有關 GAN 的信息。

在這里匯總了一個現在和經常使用的GAN論文，所有文章都鏈接到了 Arxiv 上面。

GAN?—?Generative Adversarial Networks

3D-GAN?—?Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling

AC-GAN?—?Conditional Image Synthesis With Auxiliary Classifier GANs

AdaGAN?—?AdaGAN: Boosting Generative Models

AffGAN?—?Amortised MAP Inference for Image Super-resolution

AL-CGAN?—?Learning to Generate Images of Outdoor Scenes from Attributes and Semantic Layouts

ALI?—?Adversarially Learned Inference

AMGAN?—?Generative Adversarial Nets with Labeled Data by Activation Maximization

AnoGAN?—?Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery

ArtGAN?—?ArtGAN: Artwork Synthesis with Conditional Categorial GANs

b-GAN?—?b-GAN: Unified Framework of Generative Adversarial Networks

Bayesian GAN?—?Deep and Hierarchical Implicit Models

BEGAN?—?BEGAN: Boundary Equilibrium Generative Adversarial Networks

BiGAN?—?Adversarial Feature Learning

BS-GAN?—?Boundary-Seeking Generative Adversarial Networks

CGAN?—?Conditional Generative Adversarial Nets

CCGAN?—?Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks

CatGAN?—?Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks

CoGAN?—?Coupled Generative Adversarial Networks

Context-RNN-GAN?—?Contextual RNN-GANs for Abstract Reasoning Diagram Generation

C-RNN-GAN?—?C-RNN-GAN: Continuous recurrent neural networks with adversarial training

CVAE-GAN?—?CVAE-GAN: Fine-Grained Image Generation through Asymmetric Training

CycleGAN?—?Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

DTN?—?Unsupervised Cross-Domain Image Generation

DCGAN?—?Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

DiscoGAN?—?Learning to Discover Cross-Domain Relations with Generative Adversarial Networks

DR-GAN?—?Disentangled Representation Learning GAN for Pose-Invariant Face Recognition

DualGAN?—?DualGAN: Unsupervised Dual Learning for Image-to-Image Translation

EBGAN?—?Energy-based Generative Adversarial Network

f-GAN?—?f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization

GAWWN?—?Learning What and Where to Draw

GoGAN?—?Gang of GANs: Generative Adversarial Networks with Maximum Margin Ranking

GP-GAN?—?GP-GAN: Towards Realistic High-Resolution Image Blending

IAN?—?Neural Photo Editing with Introspective Adversarial Networks

iGAN?—?Generative Visual Manipulation on the Natural Image Manifold

IcGAN?—?Invertible Conditional GANs for image editing

ID-CGAN-?Image De-raining Using a Conditional Generative Adversarial Network

Improved GAN?—?Improved Techniques for Training GANs

InfoGAN?—?InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets

LAPGAN?—?Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks

LR-GAN?—?LR-GAN: Layered Recursive Generative Adversarial Networks for Image Generation

LSGAN?—?Least Squares Generative Adversarial Networks

LS-GAN?—?Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities

MGAN?—?Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks

MAGAN?—?MAGAN: Margin Adaptation for Generative Adversarial Networks

MAD-GAN?—?Multi-Agent Diverse Generative Adversarial Networks

MalGAN?—?Generating Adversarial Malware Examples for Black-Box Attacks Based on GAN

MARTA-GAN?—?Deep Unsupervised Representation Learning for Remote Sensing Images

McGAN?—?McGan: Mean and Covariance Feature Matching GAN

MedGAN?—?Generating Multi-label Discrete Electronic Health Records using Generative Adversarial Networks

MIX+GAN?—?Generalization and Equilibrium in Generative Adversarial Nets (GANs)

MPM-GAN?—?Message Passing Multi-Agent GANs

MV-BiGAN?—?Multi-view Generative Adversarial Networks

pix2pix?—?Image-to-Image Translation with Conditional Adversarial Networks

PPGN?—?Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space

PrGAN?—?3D Shape Induction from 2D Views of Multiple Objects

RenderGAN?—?RenderGAN: Generating Realistic Labeled Data

RTT-GAN?—?Recurrent Topic-Transition GAN for Visual Paragraph Generation

SGAN?—?Stacked Generative Adversarial Networks

SGAN?—?Texture Synthesis with Spatial Generative Adversarial Networks

SAD-GAN?—?SAD-GAN: Synthetic Autonomous Driving using Generative Adversarial Networks

SalGAN?—?SalGAN: Visual Saliency Prediction with Generative Adversarial Networks

SEGAN?—?SEGAN: Speech Enhancement Generative Adversarial Network

SeGAN?—?SeGAN: Segmenting and Generating the Invisible

SeqGAN?—?SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient

SketchGAN?—?Adversarial Training For Sketch Retrieval

SL-GAN?—?Semi-Latent GAN: Learning to generate and modify facial images from attributes

Softmax-GAN?—?Softmax GAN

SRGAN?—?Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

S2GAN?—?Generative Image Modeling using Style and Structure Adversarial Networks

SSL-GAN?—?Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks

StackGAN?—?StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks

TGAN?—?Temporal Generative Adversarial Nets

TAC-GAN?—?TAC-GAN?—?Text Conditioned Auxiliary Classifier Generative Adversarial Network

TP-GAN?—?Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis

Triple-GAN?—?Triple Generative Adversarial Nets

Unrolled GAN?—?Unrolled Generative Adversarial Networks

VGAN?—?Generating Videos with Scene Dynamics

VGAN?—?Generative Adversarial Networks as Variational Training of Energy Based Models

VAE-GAN?—?Autoencoding beyond pixels using a learned similarity metric

VariGAN?—?Multi-View Image Generation from a Single-View

ViGAN?—?Image Generation and Editing with Variational Info Generative AdversarialNetworks

WGAN?—?Wasserstein GAN

WGAN-GP?—?Improved Training of Wasserstein GANs

WaterGAN?—?WaterGAN: Unsupervised Generative Network to Enable Real-time Color Correction of Monocular Underwater Images

如果你對 GAN 感興趣，可以訪問這個專題。歡迎交流。

作者：chen_h
微信號 & QQ：862251340
簡書地址：https://www.jianshu.com/p/b7f...

CoderPai 是一個專注于算法實戰的平臺，從基礎的算法到人工智能算法都有設計。如果你對算法實戰感興趣，請快快關注我們吧。加入AI實戰微信群，AI實戰QQ群，ACM算法微信群，ACM算法QQ群。長按或者掃描如下二維碼，關注 “CoderPai” 微信號（coderpai）