# 生成对抗网络相关论文

> 作者：zning（https://ning.ae） · 发布：2019/06/16 14:00 下午 (UTC+8) · 原文：https://zning.me/15606648118087.html

最近GDG深度学习之图像处理工作坊的施炎老师提供了生成对抗网络(GAN)相关论文的地址，这里整理记录下以便以后学习查找。

* 3D-ED-GAN - [Shape Inpainting using 3D Generative Adversarial Network and Recurrent Convolutional Networks](https://arxiv.org/abs/1711.06375) 
* 3D-GAN - [Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling](https://arxiv.org/abs/1610.07584) ([github](https://github.com/zck119/3dgan-release))
* 3D-IWGAN - [Improved Adversarial Systems for 3D Object Generation and Reconstruction](https://arxiv.org/abs/1707.09557) ([github](https://github.com/EdwardSmith1884/3D-IWGAN))
* 3D-PhysNet - [3D-PhysNet: Learning the Intuitive Physics of Non-Rigid Object Deformations](https://arxiv.org/abs/1805.00328) 
* 3D-RecGAN - [3D Object Reconstruction from a Single Depth View with Adversarial Learning](https://arxiv.org/abs/1708.07969) ([github](https://github.com/Yang7879/3D-RecGAN))
* ABC-GAN - [ABC-GAN: Adaptive Blur and Control for improved training stability of Generative Adversarial Networks](https://drive.google.com/file/d/0B3wEP_lEl0laVTdGcHE2VnRiMlE/view) ([github](https://github.com/IgorSusmelj/ABC-GAN))
* ABC-GAN - [GANs for LIFE: Generative Adversarial Networks for Likelihood Free Inference](https://arxiv.org/abs/1711.11139) 
* AC-GAN - [Conditional Image Synthesis With Auxiliary Classifier GANs](https://arxiv.org/abs/1610.09585) 
* acGAN - [Face Aging With Conditional Generative Adversarial Networks](https://arxiv.org/abs/1702.01983) 
* ACGAN - [Coverless Information Hiding Based on Generative adversarial networks](https://arxiv.org/abs/1712.06951) 
* acGAN - [On-line Adaptative Curriculum Learning for GANs](https://arxiv.org/abs/1808.00020) 
* ACtuAL - [ACtuAL: Actor-Critic Under Adversarial Learning](https://arxiv.org/abs/1711.04755) 
* AdaGAN - [AdaGAN: Boosting Generative Models](https://arxiv.org/abs/1701.02386v1) 
* Adaptive GAN - [Customizing an Adversarial Example Generator with Class-Conditional GANs](https://arxiv.org/abs/1806.10496) 
* AdvEntuRe - [AdvEntuRe: Adversarial Training for Textual Entailment with Knowledge-Guided Examples](https://arxiv.org/abs/1805.04680) 
* AdvGAN - [Generating adversarial examples with adversarial networks](https://arxiv.org/abs/1801.02610) 
* AE-GAN - [AE-GAN: adversarial eliminating with GAN](https://arxiv.org/abs/1707.05474) 
* AE-OT - [Latent Space Optimal Transport for Generative Models](https://arxiv.org/abs/1809.05964) 
* AEGAN - [Learning Inverse Mapping by Autoencoder based Generative Adversarial Nets](https://arxiv.org/abs/1703.10094) 
* AF-DCGAN - [AF-DCGAN: Amplitude Feature Deep Convolutional GAN for Fingerprint Construction in Indoor Localization System](https://arxiv.org/abs/1804.05347) 
* AffGAN - [Amortised MAP Inference for Image Super-resolution](https://arxiv.org/abs/1610.04490) 
* AIM - [Generating Informative and Diverse Conversational Responses via Adversarial Information Maximization](https://arxiv.org/abs/1809.05972) 
* AL-CGAN - [Learning to Generate Images of Outdoor Scenes from Attributes and Semantic Layouts](https://arxiv.org/abs/1612.00215) 
* ALI - [Adversarially Learned Inference](https://arxiv.org/abs/1606.00704) ([github](https://github.com/IshmaelBelghazi/ALI))
* AlignGAN - [AlignGAN: Learning to Align Cross-Domain Images with Conditional Generative Adversarial Networks](https://arxiv.org/abs/1707.01400) 
* AlphaGAN - [AlphaGAN: Generative adversarial networks for natural image matting](https://arxiv.org/abs/1807.10088) 
* AM-GAN - [Activation Maximization Generative Adversarial Nets](https://arxiv.org/abs/1703.02000) 
* AmbientGAN - [AmbientGAN: Generative models from lossy measurements](https://openreview.net/forum?id=Hy7fDog0b) ([github](https://github.com/AshishBora/ambient-gan))
* AMC-GAN - [Video Prediction with Appearance and Motion Conditions](https://arxiv.org/abs/1807.02635) 
* AnoGAN - [Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery](https://arxiv.org/abs/1703.05921v1) 
* APD - [Adversarial Distillation of Bayesian Neural Network Posteriors](https://arxiv.org/abs/1806.10317) 
* APE-GAN - [APE-GAN: Adversarial Perturbation Elimination with GAN](https://arxiv.org/abs/1707.05474) 
* ARAE - [Adversarially Regularized Autoencoders for Generating Discrete Structures](https://arxiv.org/abs/1706.04223) ([github](https://github.com/jakezhaojb/ARAE))
* ARDA - [Adversarial Representation Learning for Domain Adaptation](https://arxiv.org/abs/1707.01217) 
* ARIGAN - [ARIGAN: Synthetic Arabidopsis Plants using Generative Adversarial Network](https://arxiv.org/abs/1709.00938) 
* ArtGAN - [ArtGAN: Artwork Synthesis with Conditional Categorial GANs](https://arxiv.org/abs/1702.03410) 
* ASDL-GAN - [Automatic Steganographic Distortion Learning Using a Generative Adversarial Network](https://ieeexplore.ieee.org/document/8017430/) 
* ATA-GAN - [Attention-Aware Generative Adversarial Networks (ATA-GANs)](https://arxiv.org/abs/1802.09070) 
* Attention-GAN - [Attention-GAN for Object Transfiguration in Wild Images](https://arxiv.org/abs/1803.06798) 
* AttGAN - [Arbitrary Facial Attribute Editing: Only Change What You Want](https://arxiv.org/abs/1711.10678) ([github](https://github.com/LynnHo/AttGAN-Tensorflow))
* AttnGAN - [AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks](https://arxiv.org/abs/1711.10485) ([github](https://github.com/taoxugit/AttnGAN))
* AVID - [AVID: Adversarial Visual Irregularity Detection](https://arxiv.org/abs/1805.09521) 
* B-DCGAN - [B-DCGAN:Evaluation of Binarized DCGAN for FPGA](https://arxiv.org/abs/1803.10930) 
* b-GAN - [Generative Adversarial Nets from a Density Ratio Estimation Perspective](https://arxiv.org/abs/1610.02920) 
* BAGAN - [BAGAN: Data Augmentation with Balancing GAN](https://arxiv.org/abs/1803.09655) 
* Bayesian GAN - [Deep and Hierarchical Implicit Models](https://arxiv.org/abs/1702.08896) 
* Bayesian GAN - [Bayesian GAN](https://arxiv.org/abs/1705.09558) ([github](https://github.com/andrewgordonwilson/bayesgan/))
* BCGAN - [Bayesian Conditional Generative Adverserial Networks](https://arxiv.org/abs/1706.05477) 
* BCGAN - [Bidirectional Conditional Generative Adversarial networks](https://arxiv.org/abs/1711.07461) 
* BEAM - [Boltzmann Encoded Adversarial Machines](https://arxiv.org/abs/1804.08682) 
* BEGAN - [BEGAN: Boundary Equilibrium Generative Adversarial Networks](https://arxiv.org/abs/1703.10717) 
* BEGAN-CS - [Escaping from Collapsing Modes in a Constrained Space](https://arxiv.org/abs/1808.07258) 
* Bellman GAN - [Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN](https://arxiv.org/abs/1808.01960) 
* BGAN - [Binary Generative Adversarial Networks for Image Retrieval](https://arxiv.org/abs/1708.04150) ([github](https://github.com/htconquer/BGAN))
* Bi-GAN - [Autonomously and Simultaneously Refining Deep Neural Network Parameters by a Bi-Generative Adversarial Network Aided Genetic Algorithm](https://arxiv.org/abs/1809.10244) 
* BicycleGAN - [Toward Multimodal Image-to-Image Translation](https://arxiv.org/abs/1711.11586) ([github](https://github.com/junyanz/BicycleGAN))
* BiGAN - [Adversarial Feature Learning](https://arxiv.org/abs/1605.09782v7) 
* BinGAN - [BinGAN: Learning Compact Binary Descriptors with a Regularized GAN](https://arxiv.org/abs/1806.06778) 
* BourGAN - [BourGAN: Generative Networks with Metric Embeddings](https://arxiv.org/abs/1805.07674) 
* BranchGAN - [Branched Generative Adversarial Networks for Multi-Scale Image Manifold Learning](https://arxiv.org/abs/1803.08467) 
* BRE - [Improving GAN Training via Binarized Representation Entropy (BRE) Regularization](https://arxiv.org/abs/1805.03644) ([github](https://github.com/BorealisAI/bre-gan))
* BridgeGAN - [Generative Adversarial Frontal View to Bird View Synthesis](https://arxiv.org/abs/1808.00327) 
* BS-GAN - [Boundary-Seeking Generative Adversarial Networks](https://arxiv.org/abs/1702.08431v1) 
* BubGAN - [BubGAN: Bubble Generative Adversarial Networks for Synthesizing Realistic Bubbly Flow Images](https://arxiv.org/abs/1809.02266) 
* BWGAN - [Banach Wasserstein GAN](https://arxiv.org/abs/1806.06621) 
* C-GAN  - [Face Aging with Contextual Generative Adversarial Nets ](https://arxiv.org/abs/1802.00237 ) 
* C-RNN-GAN - [C-RNN-GAN: Continuous recurrent neural networks with adversarial training](https://arxiv.org/abs/1611.09904) ([github](https://github.com/olofmogren/c-rnn-gan/))
* CA-GAN - [Composition-aided Sketch-realistic Portrait Generation](https://arxiv.org/abs/1712.00899) 
* CaloGAN - [CaloGAN: Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks](https://arxiv.org/abs/1705.02355) ([github](https://github.com/hep-lbdl/CaloGAN))
* CAN - [CAN: Creative Adversarial Networks, Generating Art by Learning About Styles and Deviating from Style Norms](https://arxiv.org/abs/1706.07068) 
* CapsGAN - [CapsGAN: Using Dynamic Routing for Generative Adversarial Networks](https://arxiv.org/abs/1806.03968) 
* CapsuleGAN - [CapsuleGAN: Generative Adversarial Capsule Network ](http://arxiv.org/abs/1802.06167) 
* CatGAN - [Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks](https://arxiv.org/abs/1511.06390v2) 
* CatGAN - [CatGAN: Coupled Adversarial Transfer for Domain Generation](https://arxiv.org/abs/1711.08904) 
* CausalGAN - [CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training](https://arxiv.org/abs/1709.02023) 
* CC-GAN - [Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks](https://arxiv.org/abs/1611.06430) ([github](https://github.com/edenton/cc-gan))
* cd-GAN - [Conditional Image-to-Image Translation](https://arxiv.org/abs/1805.00251) 
* CDcGAN - [Simultaneously Color-Depth Super-Resolution with Conditional Generative Adversarial Network](https://arxiv.org/abs/1708.09105) 
* CE-GAN - [Deep Learning for Imbalance Data Classification using Class Expert Generative Adversarial Network](https://arxiv.org/abs/1807.04585) 
* CFG-GAN - [Composite Functional Gradient Learning of Generative Adversarial Models](https://arxiv.org/abs/1801.06309) 
* CGAN - [Conditional Generative Adversarial Nets](https://arxiv.org/abs/1411.1784) 
* CGAN - [Controllable Generative Adversarial Network](https://arxiv.org/abs/1708.00598) 
* Chekhov GAN - [An Online Learning Approach to Generative Adversarial Networks](https://arxiv.org/abs/1706.03269) 
* ciGAN - [Conditional Infilling GANs for Data Augmentation in Mammogram Classification](https://arxiv.org/abs/1807.08093) 
* CinCGAN - [Unsupervised Image Super-Resolution using Cycle-in-Cycle Generative Adversarial Networks](https://arxiv.org/abs/1809.00437) 
* CipherGAN - [Unsupervised Cipher Cracking Using Discrete GANs](https://arxiv.org/abs/1801.04883) 
* ClusterGAN - [ClusterGAN : Latent Space Clustering in Generative Adversarial Networks](https://arxiv.org/abs/1809.03627) 
* CM-GAN - [CM-GANs: Cross-modal Generative Adversarial Networks for Common Representation Learning](https://arxiv.org/abs/1710.05106) 
* CoAtt-GAN - [Are You Talking to Me? Reasoned Visual Dialog Generation through Adversarial Learning](https://arxiv.org/abs/1711.07613) 
* CoGAN - [Coupled Generative Adversarial Networks](https://arxiv.org/abs/1606.07536v2) 
* ComboGAN - [ComboGAN: Unrestrained Scalability for Image Domain Translation](https://arxiv.org/abs/1712.06909) ([github](https://github.com/AAnoosheh/ComboGAN))
* ConceptGAN - [Learning Compositional Visual Concepts with Mutual Consistency](https://arxiv.org/abs/1711.06148) 
* Conditional cycleGAN - [Conditional CycleGAN for Attribute Guided Face Image Generation](https://arxiv.org/abs/1705.09966) 
* constrast-GAN - [Generative Semantic Manipulation with Contrasting GAN](https://arxiv.org/abs/1708.00315) 
* Context-RNN-GAN - [Contextual RNN-GANs for Abstract Reasoning Diagram Generation](https://arxiv.org/abs/1609.09444) 
* CorrGAN - [Correlated discrete data generation using adversarial training](https://arxiv.org/abs/1804.00925) 
* Coulomb GAN - [Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields](https://arxiv.org/abs/1708.08819) 
* Cover-GAN - [Generative Steganography with Kerckhoffs' Principle based on Generative Adversarial Networks](https://arxiv.org/abs/1711.04916) 
* cowboy - [Defending Against Adversarial Attacks by Leveraging an Entire GAN](https://arxiv.org/abs/1805.10652) 
* CR-GAN - [CR-GAN: Learning Complete Representations for Multi-view Generation](https://arxiv.org/abs/1806.11191) 
* Cramèr GAN  - [The Cramer Distance as a Solution to Biased Wasserstein Gradients](https://arxiv.org/abs/1705.10743) 
* Cross-GAN - [Crossing Generative Adversarial Networks for Cross-View Person Re-identification](https://arxiv.org/abs/1801.01760) 
* crVAE-GAN - [Channel-Recurrent Variational Autoencoders](https://arxiv.org/abs/1706.03729) 
* CS-GAN - [Improving Neural Machine Translation with Conditional Sequence Generative Adversarial Nets](https://arxiv.org/abs/1703.04887) 
* CSG - [Speech-Driven Expressive Talking Lips with Conditional Sequential Generative Adversarial Networks](https://arxiv.org/abs/1806.00154) 
* CT-GAN - [CT-GAN: Conditional Transformation Generative Adversarial Network for Image Attribute Modification](https://arxiv.org/abs/1807.04812) 
* CVAE-GAN - [CVAE-GAN: Fine-Grained Image Generation through Asymmetric Training](https://arxiv.org/abs/1703.10155) 
* CycleGAN - [Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks](https://arxiv.org/abs/1703.10593) ([github](https://github.com/junyanz/CycleGAN))
* D-GAN - [Differential Generative Adversarial Networks: Synthesizing Non-linear Facial Variations with Limited Number of Training Data](https://arxiv.org/abs/1711.10267) 
* D-WCGAN - [I-vector Transformation Using Conditional Generative Adversarial Networks for Short Utterance Speaker Verification](https://arxiv.org/abs/1804.00290) 
* D2GAN - [Dual Discriminator Generative Adversarial Nets](http://arxiv.org/abs/1709.03831) 
* D2IA-GAN - [Tagging like Humans: Diverse and Distinct Image Annotation](https://arxiv.org/abs/1804.00113) 
* DA-GAN  - [DA-GAN: Instance-level Image Translation by Deep Attention Generative Adversarial Networks (with Supplementary Materials)](http://arxiv.org/abs/1802.06454) 
* DADA - [DADA: Deep Adversarial Data Augmentation for Extremely Low Data Regime Classification](https://arxiv.org/abs/1809.00981) 
* DAGAN - [Data Augmentation Generative Adversarial Networks](https://arxiv.org/abs/1711.04340) 
* DAN - [Distributional Adversarial Networks](https://arxiv.org/abs/1706.09549) 
* DBLRGAN - [Adversarial Spatio-Temporal Learning for Video Deblurring](https://arxiv.org/abs/1804.00533) 
* DCGAN - [Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks](https://arxiv.org/abs/1511.06434) ([github](https://github.com/Newmu/dcgan_code))
* DE-GAN - [Generative Adversarial Networks with Decoder-Encoder Output Noise](https://arxiv.org/abs/1807.03923) 
* DeblurGAN - [DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks](https://arxiv.org/abs/1711.07064) ([github](https://github.com/KupynOrest/DeblurGAN))
* DeepFD - [Learning to Detect Fake Face Images in the Wild](https://arxiv.org/abs/1809.08754) 
* Defense-GAN - [Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models ](https://arxiv.org/abs/1805.06605 ) ([github](https://github.com/kabkabm/defensegan))
* Defo-Net - [Defo-Net: Learning Body Deformation using Generative Adversarial Networks](https://arxiv.org/abs/1804.05928) 
* DeliGAN - [DeLiGAN : Generative Adversarial Networks for Diverse and Limited Data](https://arxiv.org/abs/1706.02071) ([github](https://github.com/val-iisc/deligan))
* DF-GAN - [Learning Disentangling and Fusing Networks for Face Completion Under Structured Occlusions](https://arxiv.org/abs/1712.04646) 
* DialogWAE - [DialogWAE: Multimodal Response Generation with Conditional Wasserstein Auto-Encoder](https://arxiv.org/abs/1805.12352) 
* DiscoGAN - [Learning to Discover Cross-Domain Relations with Generative Adversarial Networks](https://arxiv.org/abs/1703.05192v1) 
* DistanceGAN - [One-Sided Unsupervised Domain Mapping](https://arxiv.org/abs/1706.00826) 
* DM-GAN - [Dual Motion GAN for Future-Flow Embedded Video Prediction](https://arxiv.org/abs/1708.00284) 
* DMGAN - [Disconnected Manifold Learning for Generative Adversarial Networks](https://arxiv.org/abs/1806.00880) 
* DNA-GAN - [DNA-GAN: Learning Disentangled Representations from Multi-Attribute Images](https://arxiv.org/abs/1711.05415) 
* DOPING - [DOPING: Generative Data Augmentation for Unsupervised Anomaly Detection with GAN](https://arxiv.org/abs/1808.07632) 
* dp-GAN - [Differentially Private Releasing via Deep Generative Model](https://arxiv.org/abs/1801.01594) 
* DP-GAN - [DP-GAN: Diversity-Promoting Generative Adversarial Network for Generating Informative and Diversified Text ](https://arxiv.org/abs/1802.01345 ) 
* DPGAN  - [Differentially Private Generative Adversarial Network ](http://arxiv.org/abs/1802.06739) 
* DR-GAN - [Representation Learning by Rotating Your Faces](https://arxiv.org/abs/1705.11136) 
* DRAGAN - [How to Train Your DRAGAN](https://arxiv.org/abs/1705.07215) ([github](https://github.com/kodalinaveen3/DRAGAN))
* Dropout-GAN - [Dropout-GAN: Learning from a Dynamic Ensemble of Discriminators](https://arxiv.org/abs/1807.11346) 
* DRPAN - [Discriminative Region Proposal Adversarial Networks for High-Quality Image-to-Image Translation](https://arxiv.org/abs/1711.09554) 
* DSH-GAN - [Deep Semantic Hashing with Generative Adversarial Networks](https://arxiv.org/abs/1804.08275) 
* DSP-GAN - [Depth Structure Preserving Scene Image Generation](https://arxiv.org/abs/1706.00212) 
* DTLC-GAN - [Generative Adversarial Image Synthesis with Decision Tree Latent Controller](https://arxiv.org/abs/1805.10603) 
* DTN - [Unsupervised Cross-Domain Image Generation](https://arxiv.org/abs/1611.02200) 
* DTR-GAN - [DTR-GAN: Dilated Temporal Relational Adversarial Network for Video Summarization](https://arxiv.org/abs/1804.11228) 
* DualGAN - [DualGAN: Unsupervised Dual Learning for Image-to-Image Translation](https://arxiv.org/abs/1704.02510v1) 
* Dualing GAN - [Dualing GANs](https://arxiv.org/abs/1706.06216) 
* DVGAN - [Human Motion Modeling using DVGANs](https://arxiv.org/abs/1804.10652) 
* Dynamics Transfer GAN - [Dynamics Transfer GAN: Generating Video by Transferring Arbitrary Temporal Dynamics from a Source Video to a Single Target Image](https://arxiv.org/abs/1712.03534) 
* E-GAN - [Evolutionary Generative Adversarial Networks](https://arxiv.org/abs/1803.00657) 
* EAR - [Generative Model for Heterogeneous Inference](https://arxiv.org/abs/1804.09858) 
* EBGAN - [Energy-based Generative Adversarial Network](https://arxiv.org/abs/1609.03126v4) 
* ecGAN - [eCommerceGAN : A Generative Adversarial Network for E-commerce](https://arxiv.org/abs/1801.03244) 
* ED//GAN - [Stabilizing Training of Generative Adversarial Networks through Regularization](https://arxiv.org/abs/1705.09367) 
* Editable GAN - [Editable Generative Adversarial Networks: Generating and Editing Faces Simultaneously](https://arxiv.org/abs/1807.07700) 
* EGAN - [Enhanced Experience Replay Generation for Efficient Reinforcement Learning](https://arxiv.org/abs/1705.08245) 
* EL-GAN - [EL-GAN: Embedding Loss Driven Generative Adversarial Networks for Lane Detection](https://arxiv.org/abs/1806.05525) 
* ELEGANT - [ELEGANT: Exchanging Latent Encodings with GAN for Transferring Multiple Face Attributes](https://arxiv.org/abs/1803.10562) 
* EnergyWGAN - [Energy-relaxed Wassertein GANs (EnergyWGAN): Towards More Stable and High Resolution Image Generation](https://arxiv.org/abs/1712.01026) 
* ESRGAN - [ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks](https://arxiv.org/abs/1809.00219) 
* ExGAN - [Eye In-Painting with Exemplar Generative Adversarial Networks](https://arxiv.org/abs/1712.03999) 
* ExposureGAN - [Exposure: A White-Box Photo Post-Processing Framework](https://arxiv.org/abs/1709.09602) ([github](https://github.com/yuanming-hu/exposure))
* ExprGAN - [ExprGAN: Facial Expression Editing with Controllable Expression Intensity](https://arxiv.org/abs/1709.03842) 
* f-CLSWGAN - [Feature Generating Networks for Zero-Shot Learning](https://arxiv.org/abs/1712.00981) 
* f-GAN - [f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization](https://arxiv.org/abs/1606.00709) 
* FairGAN - [FairGAN: Fairness-aware Generative Adversarial Networks](https://arxiv.org/abs/1805.11202) 
* Fairness GAN - [Fairness GAN](https://arxiv.org/abs/1805.09910) 
* FakeGAN - [Detecting Deceptive Reviews using Generative Adversarial Networks](https://arxiv.org/abs/1805.10364) 
* FBGAN - [Feedback GAN (FBGAN) for DNA: a Novel Feedback-Loop Architecture for Optimizing Protein Functions](https://arxiv.org/abs/1804.01694) 
* FBGAN - [Featurized Bidirectional GAN: Adversarial Defense via Adversarially Learned Semantic Inference](https://arxiv.org/abs/1805.07862) 
* FC-GAN - [Fast-converging Conditional Generative Adversarial Networks for Image Synthesis](https://arxiv.org/abs/1805.01972) 
* FF-GAN - [Towards Large-Pose Face Frontalization in the Wild](https://arxiv.org/abs/1704.06244) 
* FGGAN - [Adversarial Learning for Fine-grained Image Search](https://arxiv.org/abs/1807.02247) 
* Fictitious GAN - [Fictitious GAN: Training GANs with Historical Models](https://arxiv.org/abs/1803.08647) 
* FIGAN - [Frame Interpolation with Multi-Scale Deep Loss Functions and Generative Adversarial Networks](https://arxiv.org/abs/1711.06045) 
* Fila-GAN - [Synthesizing Filamentary Structured Images with GANs](https://arxiv.org/abs/1706.02185) 
* First Order GAN  - [First Order Generative Adversarial Networks ](https://arxiv.org/abs/1802.04591) ([github](https://github.com/zalandoresearch/first_order_gan))
* Fisher GAN - [Fisher GAN](https://arxiv.org/abs/1705.09675) 
* Flow-GAN - [Flow-GAN: Bridging implicit and prescribed learning in generative models](https://arxiv.org/abs/1705.08868) 
* FrankenGAN - [rankenGAN: Guided Detail Synthesis for Building Mass-Models Using Style-Synchonized GANs](https://arxiv.org/abs/1806.07179) 
* FSEGAN - [Exploring Speech Enhancement with Generative Adversarial Networks for Robust Speech Recognition](https://arxiv.org/abs/1711.05747) 
* FTGAN - [Hierarchical Video Generation from Orthogonal Information: Optical Flow and Texture](https://arxiv.org/abs/1711.09618) 
* FusedGAN - [Semi-supervised FusedGAN for Conditional Image Generation](https://arxiv.org/abs/1801.05551) 
* FusionGAN - [Learning to Fuse Music Genres with Generative Adversarial Dual Learning](https://arxiv.org/abs/1712.01456) 
* FusionGAN - [Generating a Fusion Image: One's Identity and Another's Shape](https://arxiv.org/abs/1804.07455) 
* G2-GAN - [Geometry Guided Adversarial Facial Expression Synthesis](https://arxiv.org/abs/1712.03474) 
* GAAN - [Generative Adversarial Autoencoder Networks](https://arxiv.org/abs/1803.08887) 
* GAF - [Generative Adversarial Forests for Better Conditioned Adversarial Learning](https://arxiv.org/abs/1805.05185) 
* GAGAN - [GAGAN: Geometry-Aware Generative Adverserial Networks](https://arxiv.org/abs/1712.00684) 
* GAIA - [Generative adversarial interpolative autoencoding: adversarial training on latent space interpolations encourage convex latent distributions](https://arxiv.org/abs/1807.06650) 
* GAIN  - [GAIN: Missing Data Imputation using Generative Adversarial Nets](https://arxiv.org/abs/1806.02920) 
* GAMN - [Generative Adversarial Mapping Networks](https://arxiv.org/abs/1709.09820) 
* GAN - [Generative Adversarial Networks](https://arxiv.org/abs/1406.2661) ([github](https://github.com/goodfeli/adversarial))
* GAN Lab - [GAN Lab: Understanding Complex Deep Generative Models using Interactive Visual Experimentation](https://arxiv.org/abs/1809.01587) 
* GAN Q-learning - [GAN Q-learning](https://arxiv.org/abs/1805.04874) 
* GAN-AD - [Anomaly Detection with Generative Adversarial Networks for Multivariate Time Series](https://arxiv.org/abs/1809.04758) 
* GAN-ATV - [A Novel Approach to Artistic Textual Visualization via GAN](https://arxiv.org/abs/1710.10553) 
* GAN-CLS - [Generative Adversarial Text to Image Synthesis](https://arxiv.org/abs/1605.05396) ([github](https://github.com/reedscot/icml2016))
* GAN-RS - [Towards Qualitative Advancement of Underwater Machine Vision with Generative Adversarial Networks](https://arxiv.org/abs/1712.00736) 
* GAN-SD - [Virtual-Taobao: Virtualizing Real-world Online Retail Environment for Reinforcement Learning](https://arxiv.org/abs/1805.10000) 
* GAN-sep - [GANs for Biological Image Synthesis](https://arxiv.org/abs/1708.04692) ([github](https://github.com/aosokin/biogans))
* GAN-VFS - [Generative Adversarial Network-based Synthesis of Visible Faces from Polarimetric Thermal Faces](https://arxiv.org/abs/1708.02681) 
* GAN-Word2Vec - [Adversarial Training of Word2Vec for Basket Completion](https://arxiv.org/abs/1805.08720) 
* GANAX - [GANAX: A Unified MIMD-SIMD Acceleration for Generative Adversarial Networks](https://arxiv.org/abs/1806.01107) 
* GANCS - [Deep Generative Adversarial Networks for Compressed Sensing Automates MRI](https://arxiv.org/abs/1706.00051) 
* GANDI - [Guiding the search in continuous state-action spaces by learning an action sampling distribution from off-target samples](https://arxiv.org/abs/1711.01391) 
* GANG - [GANGs: Generative Adversarial Network Games](https://arxiv.org/abs/1712.00679) 
* GANG - [Beyond Local Nash Equilibria for Adversarial Networks](https://arxiv.org/abs/1806.07268) 
* GANosaic - [GANosaic: Mosaic Creation with Generative Texture Manifolds](https://arxiv.org/abs/1712.00269) 
* GANVO - [GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks](https://arxiv.org/abs/1809.05786) 
* GAP - [Context-Aware Generative Adversarial Privacy](https://arxiv.org/abs/1710.09549) 
* GAP - [Generative Adversarial Privacy](https://arxiv.org/abs/1807.05306) 
* GATS - [Sample-Efficient Deep RL with Generative Adversarial Tree Search](https://arxiv.org/abs/1806.05780) 
* GAWWN - [Learning What and Where to Draw](https://arxiv.org/abs/1610.02454) ([github](https://github.com/reedscot/nips2016))
* GC-GAN - [Geometry-Contrastive Generative Adversarial Network for Facial Expression Synthesis](https://arxiv.org/abs/1802.01822 ) 
* GcGAN - [Geometry-Consistent Adversarial Networks for One-Sided Unsupervised Domain Mapping](https://arxiv.org/abs/1809.05852) 
* GeneGAN - [GeneGAN: Learning Object Transfiguration and Attribute Subspace from Unpaired Data](https://arxiv.org/abs/1705.04932) ([github](https://github.com/Prinsphield/GeneGAN))
* GeoGAN - [Generating Instance Segmentation Annotation by Geometry-guided GAN ](https://arxiv.org/abs/1801.08839 ) 
* Geometric GAN - [Geometric GAN](https://arxiv.org/abs/1705.02894) 
* GIN - [Generative Invertible Networks (GIN): Pathophysiology-Interpretable Feature Mapping and Virtual Patient Generation](https://arxiv.org/abs/1808.04495) 
* GLCA-GAN - [Global and Local Consistent Age Generative Adversarial Networks ](https://arxiv.org/abs/1801.08390) 
* GM-GAN - [Gaussian Mixture Generative Adversarial Networks for Diverse Datasets, and the Unsupervised Clustering of Images](https://arxiv.org/abs/1808.10356) 
* GMAN - [Generative Multi-Adversarial Networks](http://arxiv.org/abs/1611.01673) 
* GMM-GAN - [Towards Understanding the Dynamics of Generative Adversarial Networks](https://arxiv.org/abs/1706.09884) 
* GoGAN - [Gang of GANs: Generative Adversarial Networks with Maximum Margin Ranking](https://arxiv.org/abs/1704.04865) 
* GONet - [GONet: A Semi-Supervised Deep Learning Approach For Traversability Estimation](https://arxiv.org/abs/1803.03254) 
* GP-GAN - [GP-GAN: Towards Realistic High-Resolution Image Blending](https://arxiv.org/abs/1703.07195) ([github](https://github.com/wuhuikai/GP-GAN))
* GP-GAN - [GP-GAN: Gender Preserving GAN for Synthesizing Faces from Landmarks](https://arxiv.org/abs/1710.00962) 
* GPU - [A generative adversarial framework for positive-unlabeled classification](https://arxiv.org/abs/1711.08054) 
* GRAN - [Generating images with recurrent adversarial networks](https://arxiv.org/abs/1602.05110) ([github](https://github.com/jiwoongim/GRAN))
* Graphical-GAN - [Graphical Generative Adversarial Networks](https://arxiv.org/abs/1804.03429) 
* GraphSGAN - [Semi-supervised Learning on Graphs with Generative Adversarial Nets](https://arxiv.org/abs/1809.00130) 
* GraspGAN - [Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping](https://arxiv.org/abs/1709.07857) 
* GT-GAN - [Deep Graph Translation](https://arxiv.org/abs/1805.09980) 
* HAN - [Chinese Typeface Transformation with Hierarchical Adversarial Network](https://arxiv.org/abs/1711.06448) 
* HAN - [Bidirectional Learning for Robust Neural Networks](https://arxiv.org/abs/1805.08006) 
* HiGAN - [Exploiting Images for Video Recognition with Hierarchical Generative Adversarial Networks](https://arxiv.org/abs/1805.04384) 
* HP-GAN - [HP-GAN: Probabilistic 3D human motion prediction via GAN](https://arxiv.org/abs/1711.09561) 
* HR-DCGAN - [High-Resolution Deep Convolutional Generative Adversarial Networks](https://arxiv.org/abs/1711.06491) 
* hredGAN - [Multi-turn Dialogue Response Generation in an Adversarial Learning framework](https://arxiv.org/abs/1805.11752) 
* IAN - [Neural Photo Editing with Introspective Adversarial Networks](https://arxiv.org/abs/1609.07093) ([github](https://github.com/ajbrock/Neural-Photo-Editor))
* IcGAN - [Invertible Conditional GANs for image editing](https://arxiv.org/abs/1611.06355) ([github](https://github.com/Guim3/IcGAN))
* ID-CGAN - [Image De-raining Using a Conditional Generative Adversarial Network](https://arxiv.org/abs/1701.05957v3) 
* IdCycleGAN - [Face Translation between Images and Videos using Identity-aware CycleGAN](https://arxiv.org/abs/1712.00971) 
* IFcVAEGAN - [Conditional Autoencoders with Adversarial Information Factorization](https://arxiv.org/abs/1711.05175) 
* iGAN - [Generative Visual Manipulation on the Natural Image Manifold](https://arxiv.org/abs/1609.03552v2) ([github](https://github.com/junyanz/iGAN))
* IGMM-GAN - [Coupled IGMM-GANs for deep multimodal anomaly detection in human mobility data](https://arxiv.org/abs/1809.02728) 
* Improved GAN - [Improved Techniques for Training GANs](https://arxiv.org/abs/1606.03498) ([github](https://github.com/openai/improved-gan))
* In2I - [In2I : Unsupervised Multi-Image-to-Image Translation Using Generative Adversarial Networks](https://arxiv.org/abs/1711.09334) 
* InfoGAN - [InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets](https://arxiv.org/abs/1606.03657v1) ([github](https://github.com/openai/InfoGAN))
* IntroVAE - [IntroVAE: Introspective Variational Autoencoders for Photographic Image Synthesis](https://arxiv.org/abs/1807.06358) 
* IR2VI - [IR2VI: Enhanced Night Environmental Perception by Unsupervised Thermal Image Translation](https://arxiv.org/abs/1806.09565) 
* IRGAN - [IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval models](https://arxiv.org/abs/1705.10513v1) 
* IRGAN - [Generative Adversarial Nets for Information Retrieval: Fundamentals and Advances](https://arxiv.org/abs/1806.03577) 
* ISGAN - [Invisible Steganography via Generative Adversarial Network](https://arxiv.org/abs/1807.08571) 
* ISP-GPM - [Inner Space Preserving Generative Pose Machine](https://arxiv.org/abs/1808.02104) 
* Iterative-GAN - [Two Birds with One Stone: Iteratively Learn Facial Attributes with GANs](https://arxiv.org/abs/1711.06078) ([github](https://github.com/punkcure/Iterative-GAN))
* IterGAN - [IterGANs: Iterative GANs to Learn and Control 3D Object Transformation](https://arxiv.org/abs/1804.05651) 
* IVE-GAN - [IVE-GAN: Invariant Encoding Generative Adversarial Networks](https://arxiv.org/abs/1711.08646) 
* iVGAN - [Towards an Understanding of Our World by GANing Videos in the Wild](https://arxiv.org/abs/1711.11453) ([github](https://github.com/bernhard2202/improved-video-gan))
* IWGAN - [On Unifying Deep Generative Models](https://arxiv.org/abs/1706.00550) 
* JointGAN - [JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets](https://arxiv.org/abs/1806.02978) 
* JR-GAN - [JR-GAN: Jacobian Regularization for Generative Adversarial Networks](https://arxiv.org/abs/1806.09235) 
* KBGAN - [KBGAN: Adversarial Learning for Knowledge Graph Embeddings](https://arxiv.org/abs/1711.04071) 
* KGAN - [KGAN: How to Break The Minimax Game in GAN](https://arxiv.org/abs/1711.01744) 
* l-GAN - [Representation Learning and Adversarial Generation of 3D Point Clouds](https://arxiv.org/abs/1707.02392) 
* LAC-GAN - [Grounded Language Understanding for Manipulation Instructions Using GAN-Based Classification](https://arxiv.org/abs/1801.05096) 
* LAGAN - [Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics Synthesis](https://arxiv.org/abs/1701.05927) 
* LAPGAN - [Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks](https://arxiv.org/abs/1506.05751) ([github](https://github.com/facebook/eyescream))
* LB-GAN - [Load Balanced GANs for Multi-view Face Image Synthesis](http://arxiv.org/abs/1802.07447) 
* LBT - [Learning Implicit Generative Models by Teaching Explicit Ones](https://arxiv.org/abs/1807.03870) 
* LCC-GAN - [Adversarial Learning with Local Coordinate Coding](https://arxiv.org/abs/1806.04895) 
* LD-GAN - [Linear Discriminant Generative Adversarial Networks](https://arxiv.org/abs/1707.07831) 
* LDAN - [Label Denoising Adversarial Network (LDAN) for Inverse Lighting of Face Images](https://arxiv.org/abs/1709.01993) 
* LeakGAN - [Long Text Generation via Adversarial Training with Leaked Information](https://arxiv.org/abs/1709.08624) 
* LeGAN - [Likelihood Estimation for Generative Adversarial Networks](https://arxiv.org/abs/1707.07530) 
* LGAN - [Global versus Localized Generative Adversarial Nets](https://arxiv.org/abs/1711.06020) 
* Lipizzaner - [Towards Distributed Coevolutionary GANs](https://arxiv.org/abs/1807.08194) 
* LR-GAN - [LR-GAN: Layered Recursive Generative Adversarial Networks for Image Generation](https://arxiv.org/abs/1703.01560v1) 
* LS-GAN - [Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities](https://arxiv.org/abs/1701.06264) 
* LSGAN - [Least Squares Generative Adversarial Networks](https://arxiv.org/abs/1611.04076v3) 
* M-AAE - [Mask-aware Photorealistic Face Attribute Manipulation](https://arxiv.org/abs/1804.08882) 
* MAD-GAN - [Multi-Agent Diverse Generative Adversarial Networks](https://arxiv.org/abs/1704.02906) 
* MAGAN - [MAGAN: Margin Adaptation for Generative Adversarial Networks](https://arxiv.org/abs/1704.03817v1) 
* MAGAN - [MAGAN: Aligning Biological Manifolds](https://arxiv.org/abs/1803.00385) 
* MalGAN - [Generating Adversarial Malware Examples for Black-Box Attacks Based on GAN](https://arxiv.org/abs/1702.05983v1) 
* MaliGAN - [Maximum-Likelihood Augmented Discrete Generative Adversarial Networks](https://arxiv.org/abs/1702.07983) 
* manifold-WGAN - [Manifold-valued Image Generation with Wasserstein Adversarial Networks](https://arxiv.org/abs/1712.01551) 
* MARTA-GAN - [Deep Unsupervised Representation Learning for Remote Sensing Images](https://arxiv.org/abs/1612.08879) 
* MaskGAN - [MaskGAN: Better Text Generation via Filling in the ______ ](https://arxiv.org/abs/1801.07736 ) 
* MC-GAN - [Multi-Content GAN for Few-Shot Font Style Transfer](https://arxiv.org/abs/1712.00516) ([github](https://github.com/azadis/MC-GAN))
* MC-GAN - [MC-GAN: Multi-conditional Generative Adversarial Network for Image Synthesis](https://arxiv.org/abs/1805.01123) 
* McGAN - [McGan: Mean and Covariance Feature Matching GAN](https://arxiv.org/abs/1702.08398v1) 
* MD-GAN - [Learning to Generate Time-Lapse Videos Using Multi-Stage Dynamic Generative Adversarial Networks](https://arxiv.org/abs/1709.07592) 
* MDGAN - [Mode Regularized Generative Adversarial Networks](https://arxiv.org/abs/1612.02136) 
* MedGAN - [Generating Multi-label Discrete Electronic Health Records using Generative Adversarial Networks](https://arxiv.org/abs/1703.06490v1) 
* MedGAN - [MedGAN: Medical Image Translation using GANs](https://arxiv.org/abs/1806.06397) 
* MEGAN - [MEGAN: Mixture of Experts of Generative Adversarial Networks for Multimodal Image Generation](https://arxiv.org/abs/1805.02481) 
* MelanoGAN - [MelanoGANs: High Resolution Skin Lesion Synthesis with GANs](https://arxiv.org/abs/1804.04338) 
* memoryGAN - [Memorization Precedes Generation: Learning Unsupervised GANs with Memory Networks](https://arxiv.org/abs/1803.01500) 
* MeRGAN - [Memory Replay GANs: learning to generate images from new categories without forgetting](https://arxiv.org/abs/1809.02058) 
* MGAN - [Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks](https://arxiv.org/abs/1604.04382) ([github](https://github.com/chuanli11/MGANs))
* MGGAN - [Multi-Generator Generative Adversarial Nets](https://arxiv.org/abs/1708.02556) 
* MGGAN - [MGGAN: Solving Mode Collapse using Manifold Guided Training](https://arxiv.org/abs/1804.04391) 
* MIL-GAN - [Multimodal Storytelling via Generative Adversarial Imitation Learning](https://arxiv.org/abs/1712.01455) 
* MinLGAN - [Anomaly Detection via Minimum Likelihood Generative Adversarial Networks](https://arxiv.org/abs/1808.00200) 
* MIX+GAN - [Generalization and Equilibrium in Generative Adversarial Nets (GANs)](https://arxiv.org/abs/1703.00573v3) 
* MIXGAN - [MIXGAN: Learning Concepts from Different Domains for Mixture Generation](https://arxiv.org/abs/1807.01659) 
* MLGAN - [Metric Learning-based Generative Adversarial Network](https://arxiv.org/abs/1711.02792) 
* MMC-GAN - [A Multimodal Classifier Generative Adversarial Network for Carry and Place Tasks from Ambiguous Language Instructions](https://arxiv.org/abs/1806.03847) 
* MMD-GAN - [MMD GAN: Towards Deeper Understanding of Moment Matching Network](https://arxiv.org/abs/1705.08584) ([github](https://github.com/dougalsutherland/opt-mmd))
* MMGAN - [MMGAN: Manifold Matching Generative Adversarial Network for Generating Images](https://arxiv.org/abs/1707.08273) 
* MoCoGAN - [MoCoGAN: Decomposing Motion and Content for Video Generation](https://arxiv.org/abs/1707.04993) ([github](https://github.com/sergeytulyakov/mocogan))
* Modified GAN-CLS - [Generate the corresponding Image from Text Description using Modified GAN-CLS Algorithm](https://arxiv.org/abs/1806.11302) 
* ModularGAN - [Modular Generative Adversarial Networks](https://arxiv.org/abs/1804.03343) 
* MolGAN - [MolGAN: An implicit generative model for small molecular graphs](https://arxiv.org/abs/1805.11973) 
* MPM-GAN - [Message Passing Multi-Agent GANs](https://arxiv.org/abs/1612.01294) 
* MS-GAN - [Temporal Coherency based Criteria for Predicting Video Frames using Deep Multi-stage Generative Adversarial Networks](http://papers.nips.cc/paper/7014-temporal-coherency-based-criteria-for-predicting-video-frames-using-deep-multi-stage-generative-adversarial-networks) 
* MTGAN - [MTGAN: Speaker Verification through Multitasking Triplet Generative Adversarial Networks](https://arxiv.org/abs/1803.09059) 
* MuseGAN - [MuseGAN: Symbolic-domain Music Generation and Accompaniment with Multi-track Sequential Generative Adversarial Networks](https://arxiv.org/abs/1709.06298) 
* MV-BiGAN - [Multi-view Generative Adversarial Networks](https://arxiv.org/abs/1611.02019v1) 
* N2RPP - [N2RPP: An Adversarial Network to Rebuild Plantar Pressure for ACLD Patients](https://arxiv.org/abs/1805.02825) 
* NAN - [Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human Parsing](https://arxiv.org/abs/1804.03287) 
* NCE-GAN - [Dihedral angle prediction using generative adversarial networks](https://arxiv.org/abs/1803.10996) 
* ND-GAN - [Novelty Detection with GAN](https://arxiv.org/abs/1802.10560) 
* NetGAN - [NetGAN: Generating Graphs via Random Walks](https://arxiv.org/abs/1803.00816) 
* OCAN - [One-Class Adversarial Nets for Fraud Detection](https://arxiv.org/abs/1803.01798) 
* OptionGAN - [OptionGAN: Learning Joint Reward-Policy Options using Generative Adversarial Inverse Reinforcement Learning](https://arxiv.org/abs/1709.06683) 
* ORGAN - [Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models ](https://arxiv.org/abs/1705.10843) 
* ORGAN - [3D Reconstruction of Incomplete Archaeological Objects Using a Generative Adversary Network](https://arxiv.org/abs/1711.06363) 
* OT-GAN - [Improving GANs Using Optimal Transport](https://arxiv.org/abs/1803.05573) 
* PacGAN - [PacGAN: The power of two samples in generative adversarial networks](https://arxiv.org/abs/1712.04086) 
* PAN - [Perceptual Adversarial Networks for Image-to-Image Transformation](https://arxiv.org/abs/1706.09138) 
* PassGAN - [PassGAN: A Deep Learning Approach for Password Guessing](https://arxiv.org/abs/1709.00440) 
* PD-WGAN - [Primal-Dual Wasserstein GAN](https://arxiv.org/abs/1805.09575) 
* Perceptual GAN - [Perceptual Generative Adversarial Networks for Small Object Detection](https://arxiv.org/abs/1706.05274) 
* PGAN - [Probabilistic Generative Adversarial Networks](https://arxiv.org/abs/1708.01886) 
* PGD-GAN - [Solving Linear Inverse Problems Using GAN Priors: An Algorithm with Provable Guarantees](https://arxiv.org/abs/1802.08406) 
* PGGAN - [Patch-Based Image Inpainting with Generative Adversarial Networks](https://arxiv.org/abs/1803.07422) 
* PIONEER - [Pioneer Networks: Progressively Growing Generative Autoencoder](https://arxiv.org/abs/1807.03026) 
* Pip-GAN - [Pipeline Generative Adversarial Networks for Facial Images Generation with Multiple Attributes](https://arxiv.org/abs/1711.10742) 
* pix2pix - [Image-to-Image Translation with Conditional Adversarial Networks](https://arxiv.org/abs/1611.07004) ([github](https://github.com/phillipi/pix2pix))
* pix2pixHD - [High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs](https://arxiv.org/abs/1711.11585) ([github](https://github.com/NVIDIA/pix2pixHD))
* PixelGAN - [PixelGAN Autoencoders](https://arxiv.org/abs/1706.00531) 
* PM-GAN - [PM-GANs: Discriminative Representation Learning for Action Recognition Using Partial-modalities](https://arxiv.org/abs/1804.06248) 
* PN-GAN - [Pose-Normalized Image Generation for Person Re-identification](https://arxiv.org/abs/1712.02225) 
* POGAN - [Perceptually Optimized Generative Adversarial Network for Single Image Dehazing](https://arxiv.org/abs/1805.01084) 
* Pose-GAN - [The Pose Knows: Video Forecasting by Generating Pose Futures](https://arxiv.org/abs/1705.00053) 
* PP-GAN - [Privacy-Protective-GAN for Face De-identification](https://arxiv.org/abs/1806.08906) 
* PPAN - [Privacy-Preserving Adversarial Networks](https://arxiv.org/abs/1712.07008) 
* PPGN - [Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space](https://arxiv.org/abs/1612.00005) 
* PrGAN - [3D Shape Induction from 2D Views of Multiple Objects](https://arxiv.org/abs/1612.05872) 
* ProGanSR - [A Fully Progressive Approach to Single-Image Super-Resolution](https://arxiv.org/abs/1804.02900) 
* Progressive GAN - [Progressive Growing of GANs for Improved Quality, Stability, and Variation](https://arxiv.org/abs/1710.10196) ([github](https://github.com/tkarras/progressive_growing_of_gans))
* PS-GAN - [Pedestrian-Synthesis-GAN: Generating Pedestrian Data in Real Scene and Beyond](https://arxiv.org/abs/1804.02047) 
* PSGAN - [Learning Texture Manifolds with the Periodic Spatial GAN](http://arxiv.org/abs/1705.06566) 
* PSGAN - [PSGAN: A Generative Adversarial Network for Remote Sensing Image Pan-Sharpening](https://arxiv.org/abs/1805.03371) 
* PS²-GAN - [High-Quality Facial Photo-Sketch Synthesis Using Multi-Adversarial Networks](https://arxiv.org/abs/1710.10182) 
* RadialGAN - [RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks ](http://arxiv.org/abs/1802.06403) 
* RaGAN - [The relativistic discriminator: a key element missing from standard GAN](https://arxiv.org/abs/1807.00734) 
* RAN - [RAN4IQA: Restorative Adversarial Nets for No-Reference Image Quality Assessment](https://arxiv.org/abs/1712.05444) ([github]())
* RankGAN - [Adversarial Ranking for Language Generation ](https://arxiv.org/abs/1705.11001) 
* RCGAN - [Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs](https://arxiv.org/abs/1706.02633) 
* ReConNN - [Reconstruction of Simulation-Based Physical Field with Limited Samples by Reconstruction Neural Network](https://arxiv.org/abs/1805.00528) 
* Recycle-GAN - [Recycle-GAN: Unsupervised Video Retargeting](https://arxiv.org/abs/1808.05174) 
* RefineGAN - [Compressed Sensing MRI Reconstruction with Cyclic Loss in Generative Adversarial Networks](https://arxiv.org/abs/1709.00753) 
* ReGAN - [ReGAN: RE[LAX|BAR|INFORCE] based Sequence Generation using GANs](https://arxiv.org/abs/1805.02788) ([github](https://github.com/TalkToTheGAN/REGAN))
* RegCGAN - [Unpaired Multi-Domain Image Generation via Regularized Conditional GANs](https://arxiv.org/abs/1805.02456) 
* RenderGAN - [RenderGAN: Generating Realistic Labeled Data](https://arxiv.org/abs/1611.01331) 
* Resembled GAN - [Resembled Generative Adversarial Networks: Two Domains with Similar Attributes](https://arxiv.org/abs/1807.00947) 
* ResGAN - [Generative Adversarial Network based on Resnet for Conditional Image Restoration](https://arxiv.org/abs/1707.04881) 
* RNN-WGAN - [Language Generation with Recurrent Generative Adversarial Networks without Pre-training](https://arxiv.org/abs/1706.01399) ([github](https://github.com/amirbar/rnn.wgan))
* RoCGAN - [Robust Conditional Generative Adversarial Networks](https://arxiv.org/abs/1805.08657) 
* RPGAN - [Stabilizing GAN Training with Multiple Random Projections](https://arxiv.org/abs/1705.07831) ([github](https://github.com/ayanc/rpgan))
* RTT-GAN - [Recurrent Topic-Transition GAN for Visual Paragraph Generation](https://arxiv.org/abs/1703.07022v2) 
* RWGAN - [Relaxed Wasserstein with Applications to GANs](https://arxiv.org/abs/1705.07164) 
* SAD-GAN - [SAD-GAN: Synthetic Autonomous Driving using Generative Adversarial Networks](https://arxiv.org/abs/1611.08788v1) 
* SAGA - [Generative Adversarial Learning for Spectrum Sensing](https://arxiv.org/abs/1804.00709) 
* SAGAN - [Self-Attention Generative Adversarial Networks](https://arxiv.org/abs/1805.08318) 
* SalGAN - [SalGAN: Visual Saliency Prediction with Generative Adversarial Networks](https://arxiv.org/abs/1701.01081) ([github](https://github.com/imatge-upc/saliency-salgan-2017))
* SAM - [Sample-Efficient Imitation Learning via Generative Adversarial Nets](https://arxiv.org/abs/1809.02064) 
* sAOG - [Deep Structured Generative Models](https://arxiv.org/abs/1807.03877) 
* SAR-GAN - [Generating High Quality Visible Images from SAR Images Using CNNs](https://arxiv.org/abs/1802.10036) 
* SBADA-GAN - [From source to target and back: symmetric bi-directional adaptive GAN](https://arxiv.org/abs/1705.08824) 
* ScarGAN - [ScarGAN: Chained Generative Adversarial Networks to Simulate Pathological Tissue on Cardiovascular MR Scans](https://arxiv.org/abs/1808.04500) 
* SCH-GAN - [SCH-GAN: Semi-supervised Cross-modal Hashing by Generative Adversarial Network ](https://arxiv.org/abs/1802.02488 ) 
* SD-GAN - [Semantically Decomposing the Latent Spaces of Generative Adversarial Networks](https://arxiv.org/abs/1705.07904) 
* Sdf-GAN - [Sdf-GAN: Semi-supervised Depth Fusion with Multi-scale Adversarial Networks](https://arxiv.org/abs/1803.06657) 
* SEGAN - [SEGAN: Speech Enhancement Generative Adversarial Network](https://arxiv.org/abs/1703.09452v1) 
* SeGAN - [SeGAN: Segmenting and Generating the Invisible](https://arxiv.org/abs/1703.10239) 
* SegAN - [SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation](https://arxiv.org/abs/1706.01805) 
* Sem-GAN - [Sem-GAN: Semantically-Consistent Image-to-Image Translation](https://arxiv.org/abs/1807.04409) 
* SeqGAN - [SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient](https://arxiv.org/abs/1609.05473v5) ([github](https://github.com/LantaoYu/SeqGAN))
* SeUDA - [Semantic-Aware Generative Adversarial Nets for Unsupervised Domain Adaptation in Chest X-ray Segmentation](https://arxiv.org/abs/1806.00600) 
* SG-GAN - [Semantic-aware Grad-GAN for Virtual-to-Real Urban Scene Adaption](https://arxiv.org/abs/1801.01726) ([github](https://github.com/Peilun-Li/SG-GAN))
* SG-GAN - [Sparsely Grouped Multi-task Generative Adversarial Networks for Facial Attribute Manipulation](https://arxiv.org/abs/1805.07509) 
* SGAN - [Texture Synthesis with Spatial Generative Adversarial Networks](https://arxiv.org/abs/1611.08207) 
* SGAN - [Stacked Generative Adversarial Networks](https://arxiv.org/abs/1612.04357v4) ([github](https://github.com/xunhuang1995/SGAN))
* SGAN - [Steganographic Generative Adversarial Networks](https://arxiv.org/abs/1703.05502) 
* SGAN - [SGAN: An Alternative Training of Generative Adversarial Networks](https://arxiv.org/abs/1712.02330) 
* SGAN - [CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement](https://arxiv.org/abs/1807.07144) 
* sGAN  - [Generative Adversarial Training for MRA Image Synthesis Using Multi-Contrast MRI](https://arxiv.org/abs/1804.04366) 
* SiftingGAN - [SiftingGAN: Generating and Sifting Labeled Samples to Improve the Remote Sensing Image Scene Classification Baseline in vitro](https://arxiv.org/abs/1809.04985) 
* SiGAN - [SiGAN: Siamese Generative Adversarial Network for Identity-Preserving Face Hallucination](https://arxiv.org/abs/1807.08370) 
* SimGAN - [Learning from Simulated and Unsupervised Images through Adversarial Training](https://arxiv.org/abs/1612.07828) 
* SisGAN - [Semantic Image Synthesis via Adversarial Learning](https://arxiv.org/abs/1707.06873) 
* Sketcher-Refiner GAN - [Learning Myelin Content in Multiple Sclerosis from Multimodal MRI through Adversarial Training](https://arxiv.org/abs/1804.08039) 
* SketchGAN - [Adversarial Training For Sketch Retrieval](https://arxiv.org/abs/1607.02748) 
* SketchyGAN - [SketchyGAN: Towards Diverse and Realistic Sketch to Image Synthesis](https://arxiv.org/abs/1801.02753) 
* Skip-Thought GAN - [Generating Text through Adversarial Training using Skip-Thought Vectors](https://arxiv.org/abs/1808.08703) 
* SL-GAN - [Semi-Latent GAN: Learning to generate and modify facial images from attributes](https://arxiv.org/abs/1704.02166) 
* SLSR - [Sparse Label Smoothing for Semi-supervised Person Re-Identification](https://arxiv.org/abs/1809.04976) 
* SN-DCGAN - [Generative Adversarial Networks for Unsupervised Object Co-localization](https://arxiv.org/abs/1806.00236) 
* SN-GAN - [Spectral Normalization for Generative Adversarial Networks](https://drive.google.com/file/d/0B8HZ50DPgR3eSVV6YlF3XzQxSjQ/view) ([github](https://github.com/pfnet-research/chainer-gan-lib))
* SN-PatchGAN - [Free-Form Image Inpainting with Gated Convolution](https://arxiv.org/abs/1806.03589) 
* Sobolev GAN - [Sobolev GAN](https://arxiv.org/abs/1711.04894) 
* Social GAN - [Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks](https://arxiv.org/abs/1803.10892) 
* Softmax GAN - [Softmax GAN](https://arxiv.org/abs/1704.06191) 
* SoPhie - [SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints](https://arxiv.org/abs/1806.01482) 
* speech-driven animation GAN - [End-to-End Speech-Driven Facial Animation with Temporal GANs](https://arxiv.org/abs/1805.09313) 
* Spike-GAN - [Synthesizing realistic neural population activity patterns using Generative Adversarial Networks](https://arxiv.org/abs/1803.00338) 
* Splitting GAN - [Class-Splitting Generative Adversarial Networks](https://arxiv.org/abs/1709.07359) 
* SR-CNN-VAE-GAN - [Semi-Recurrent CNN-based VAE-GAN for Sequential Data Generation](https://arxiv.org/abs/1806.00509) ([github](https://github.com/makbari7/SR-CNN-VAE-GAN))
* SRGAN - [Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network](https://arxiv.org/abs/1609.04802) 
* SRPGAN - [SRPGAN: Perceptual Generative Adversarial Network for Single Image Super Resolution](https://arxiv.org/abs/1712.05927) 
* SS-GAN - [Semi-supervised Conditional GANs](https://arxiv.org/abs/1708.05789) 
* ss-InfoGAN - [Guiding InfoGAN with Semi-Supervision](https://arxiv.org/abs/1707.04487) 
* SSGAN - [SSGAN: Secure Steganography Based on Generative Adversarial Networks](https://arxiv.org/abs/1707.01613) 
* SSL-GAN - [Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks](https://arxiv.org/abs/1611.06430v1) 
* ST-CGAN - [Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal](https://arxiv.org/abs/1712.02478) 
* ST-GAN - [Style Transfer Generative Adversarial Networks: Learning to Play Chess Differently](https://arxiv.org/abs/1702.06762) 
* ST-GAN - [ST-GAN: Spatial Transformer Generative Adversarial Networks for Image Compositing](https://arxiv.org/abs/1803.01837) 
* StackGAN - [StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks](https://arxiv.org/abs/1612.03242v1) ([github](https://github.com/hanzhanggit/StackGAN))
* StainGAN - [StainGAN: Stain Style Transfer for Digital Histological Images](https://arxiv.org/abs/1804.01601) 
* StarGAN - [StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation](https://arxiv.org/abs/1711.09020) ([github](https://github.com/yunjey/StarGAN))
* StarGAN-VC - [StarGAN-VC: Non-parallel many-to-many voice conversion with star generative adversarial networks ](https://arxiv.org/abs/1806.02169) 
* SteinGAN - [Learning Deep Energy Models: Contrastive Divergence vs. Amortized MLE](https://arxiv.org/abs/1707.00797) 
* StepGAN - [Improving Conditional Sequence Generative Adversarial Networks by Stepwise Evaluation](https://arxiv.org/abs/1808.05599) 
* Super-FAN - [Super-FAN: Integrated facial landmark localization and super-resolution of real-world low resolution faces in arbitrary poses with GANs](https://arxiv.org/abs/1712.02765) 
* SVSGAN - [SVSGAN: Singing Voice Separation via Generative Adversarial Network](https://arxiv.org/abs/1710.11428) 
* SWGAN - [Solving Approximate Wasserstein GANs to Stationarity](https://arxiv.org/abs/1802.08249) 
* SyncGAN - [SyncGAN: Synchronize the Latent Space of Cross-modal Generative Adversarial Networks](https://arxiv.org/abs/1804.00410) 
* S^2GAN - [Generative Image Modeling using Style and Structure Adversarial Networks](https://arxiv.org/abs/1603.05631v2) 
* T2Net - [T2Net: Synthetic-to-Realistic Translation for Solving Single-Image Depth Estimation Tasks](https://arxiv.org/abs/1808.01454) 
* table-GAN - [Data Synthesis based on Generative Adversarial Networks](https://arxiv.org/abs/1806.03384) 
* TAC-GAN - [TAC-GAN - Text Conditioned Auxiliary Classifier Generative Adversarial Network](https://arxiv.org/abs/1703.06412v2) ([github](https://github.com/dashayushman/TAC-GAN))
* TAN - [Outline Colorization through Tandem Adversarial Networks](https://arxiv.org/abs/1704.08834) 
* tcGAN - [Cross-modal Hallucination for Few-shot Fine-grained Recognition](https://arxiv.org/abs/1806.05147) 
* TD-GAN - [Task Driven Generative Modeling for Unsupervised Domain Adaptation: Application to X-ray Image Segmentation](https://arxiv.org/abs/1806.07201) 
* tempCycleGAN - [Improving Surgical Training Phantoms by Hyperrealism: Deep Unpaired Image-to-Image Translation from Real Surgeries](https://arxiv.org/abs/1806.03627) 
* tempoGAN - [tempoGAN: A Temporally Coherent, Volumetric GAN for Super-resolution Fluid Flow](https://arxiv.org/abs/1801.09710) 
* TequilaGAN - [TequilaGAN: How to easily identify GAN samples](https://arxiv.org/abs/1807.04919) 
* Text2Shape - [Text2Shape: Generating Shapes from Natural Language by Learning Joint Embeddings](https://arxiv.org/abs/1803.08495) 
* textGAN - [Generating Text via Adversarial Training](https://zhegan27.github.io/Papers/textGAN_nips2016_workshop.pdf) 
* TextureGAN - [TextureGAN: Controlling Deep Image Synthesis with Texture Patches](https://arxiv.org/abs/1706.02823) 
* TGAN - [Temporal Generative Adversarial Nets](https://arxiv.org/abs/1611.06624v1) 
* TGAN - [Tensorizing Generative Adversarial Nets](https://arxiv.org/abs/1710.10772) 
* TGAN - [Tensor-Generative Adversarial Network with Two-dimensional Sparse Coding: Application to Real-time Indoor Localization](https://arxiv.org/abs/1711.02666) 
* TGANs-C - [To Create What You Tell: Generating Videos from Captions](https://arxiv.org/abs/1804.08264) 
* tiny-GAN - [Analysis of Nonautonomous Adversarial Systems](https://arxiv.org/abs/1803.05045) 
* TP-GAN - [Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis](https://arxiv.org/abs/1704.04086) 
* TreeGAN - [TreeGAN: Syntax-Aware Sequence Generation with Generative Adversarial Networks](https://arxiv.org/abs/1808.07582) 
* Triple-GAN - [Triple Generative Adversarial Nets](https://arxiv.org/abs/1703.02291v2) 
* tripletGAN - [TripletGAN: Training Generative Model with Triplet Loss](https://arxiv.org/abs/1711.05084) 
* TV-GAN - [TV-GAN: Generative Adversarial Network Based Thermal to Visible Face Recognition](https://arxiv.org/abs/1712.02514) 
* Twin-GAN - [Twin-GAN -- Unpaired Cross-Domain Image Translation with Weight-Sharing GANs](https://arxiv.org/abs/1809.00946) 
* UGACH - [Unsupervised Generative Adversarial Cross-modal Hashing](https://arxiv.org/abs/1712.00358) 
* UGAN - [Enhancing Underwater Imagery using Generative Adversarial Networks](https://arxiv.org/abs/1801.04011) 
* Unim2im - [Unsupervised Image-to-Image Translation with Generative Adversarial Networks ](https://arxiv.org/abs/1701.02676) ([github](http://github.com/zsdonghao/Unsup-Im2Im))
* UNIT - [Unsupervised Image-to-image Translation Networks](https://arxiv.org/abs/1703.00848) ([github](https://github.com/mingyuliutw/UNIT))
* Unrolled GAN - [Unrolled Generative Adversarial Networks](https://arxiv.org/abs/1611.02163) ([github](https://github.com/poolio/unrolled_gan))
* UT-SCA-GAN - [Spatial Image Steganography Based on Generative Adversarial Network](https://arxiv.org/abs/1804.07939) 
* UV-GAN - [UV-GAN: Adversarial Facial UV Map Completion for Pose-invariant Face Recognition](https://arxiv.org/abs/1712.04695) 
* VA-GAN - [Visual Feature Attribution using Wasserstein GANs](https://arxiv.org/abs/1711.08998) 
* VAC+GAN  - [Versatile Auxiliary Classifier with Generative Adversarial Network (VAC+GAN), Multi Class Scenarios](https://arxiv.org/abs/1806.07751) 
* VAE-GAN - [Autoencoding beyond pixels using a learned similarity metric](https://arxiv.org/abs/1512.09300) 
* VariGAN - [Multi-View Image Generation from a Single-View](https://arxiv.org/abs/1704.04886) 
* VAW-GAN - [Voice Conversion from Unaligned Corpora using Variational Autoencoding Wasserstein Generative Adversarial Networks](https://arxiv.org/abs/1704.00849) 
* VEEGAN - [VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning](https://arxiv.org/abs/1705.07761) ([github](https://github.com/akashgit/VEEGAN))
* VGAN - [Generating Videos with Scene Dynamics](https://arxiv.org/abs/1609.02612) ([github](https://github.com/cvondrick/videogan))
* VGAN - [Generative Adversarial Networks as Variational Training of Energy Based Models](https://arxiv.org/abs/1611.01799) ([github](https://github.com/Shuangfei/vgan))
* VGAN - [Text Generation Based on Generative Adversarial Nets with Latent Variable](https://arxiv.org/abs/1712.00170) 
* ViGAN - [Image Generation and Editing with Variational Info Generative Adversarial Networks](https://arxiv.org/abs/1701.04568v1) 
* VIGAN - [VIGAN: Missing View Imputation with Generative Adversarial Networks](https://arxiv.org/abs/1708.06724) 
* VoiceGAN - [Voice Impersonation using Generative Adversarial Networks ](http://arxiv.org/abs/1802.06840) 
* VOS-GAN - [VOS-GAN: Adversarial Learning of Visual-Temporal Dynamics for Unsupervised Dense Prediction in Videos](https://arxiv.org/abs/1803.09092) 
* VRAL - [Variance Regularizing Adversarial Learning](https://arxiv.org/abs/1707.00309) 
* WaterGAN - [WaterGAN: Unsupervised Generative Network to Enable Real-time Color Correction of Monocular Underwater Images](https://arxiv.org/abs/1702.07392v1) 
* WaveGAN - [Synthesizing Audio with Generative Adversarial Networks ](https://arxiv.org/abs/1802.04208) 
* WaveletGLCA-GAN - [Global and Local Consistent Wavelet-domain Age Synthesis](https://arxiv.org/abs/1809.07764) 
* weGAN - [Generative Adversarial Nets for Multiple Text Corpora](https://arxiv.org/abs/1712.09127) 
* WGAN - [Wasserstein GAN](https://arxiv.org/abs/1701.07875v2) ([github](https://github.com/martinarjovsky/WassersteinGAN))
* WGAN-CLS - [Text to Image Synthesis Using Generative Adversarial Networks](https://arxiv.org/abs/1805.00676) 
* WGAN-GP - [Improved Training of Wasserstein GANs](https://arxiv.org/abs/1704.00028) ([github](https://github.com/igul222/improved_wgan_training))
* WGAN-L1 - [Subsampled Turbulence Removal Network](https://arxiv.org/abs/1807.04418) 
* WS-GAN - [Weakly Supervised Generative Adversarial Networks for 3D Reconstruction ](https://arxiv.org/abs/1705.10904) 
* X-GANs - [X-GANs: Image Reconstruction Made Easy for Extreme Cases](https://arxiv.org/abs/1808.04432) 
* XGAN - [XGAN: Unsupervised Image-to-Image Translation for many-to-many Mappings](https://arxiv.org/abs/1711.05139) 
* ZipNet-GAN - [ZipNet-GAN: Inferring Fine-grained Mobile Traffic Patterns via a Generative Adversarial Neural Network](https://arxiv.org/abs/1711.02413) 
* α-GAN - [Variational Approaches for Auto-Encoding Generative Adversarial Networks](https://arxiv.org/abs/1706.04987) ([github](https://github.com/victor-shepardson/alpha-GAN))
* β-GAN - [Annealed Generative Adversarial Networks](https://arxiv.org/abs/1705.07505) 
* Δ-GAN - [Triangle Generative Adversarial Networks](https://arxiv.org/abs/1709.06548)