Deep Learning::Redes Adversárias & Neural Style Transfer

Nesta página vamos tratar de redes neurais convolucionais dirigidas à podução de efeitos artísticos. Temos duas categorias de funções e, conseqüentemente, duas arquiteturas de rede distintas e que usam conseitos distintos:

1. Transferência de valores de pixels a objetos semanticamente correlatos: Redes Gerativas Adverárias (GANs – Adversarial Generative Networks) e
2. Transferência de elementos de estilo de uma imagem à outra: Redes para Transferência Neural de Estilos (NST – Neural Style Tranfer)

GANs e outras Redes Gerativas

As redes gerativas implementam aprendizado não supervisionado, diferentemente dos outros modelos vistos neste site. Divide-se em três grupos:

• Supõem modelos de probabilidade com densidade explícita e tratável: PixelRNN e PixelCNN (não possuem grande significado prático e não vamos abordar aqui)
• Supõem modelos de probabilidade com densidade explícita, originalmente intratáveis, mas que possuem solução aproximada através de uma CNN: Autocodificadores Variacionais
• Supõem modelos de probabilidade com densidade implícita:  GANs (Redes Gerativas Adversárias)

Este tipo de rede ficou conhecido por causa de efeitos de transferência de uma imagem sobre outra, usados em aplicações como DeepFake. Adiante um vídeo que demonstra esta capacidade, que foi produzido utilizando-se um Autocodificador Variacional:

• Towards Data Science::Variational Autoencoders Explained in Detail

Outra aplicação de GAN é deblurring:

Tutoriais de GAN

1. Tutorial básico, em linguagem coloquial,  deixa um pouco a desejar: Towards Data Science – Demystifying Generative Adversarial Networks (Keras + TensorFlow e MNIST)
2. GAN with Keras: Application to Image Deblurring
3. Towards Data Science::Your Complete Beginners Guide to Generative Adversarial Networks (ultraresumido…)
4. Towards Data Science::CycleGAN: Learning to Translate Images (Without Paired Training Data)
5. CycleGAN & pix2pix: Image-to-Image Translation with Conditional Adversarial Nets (Implementações em TensorFlow, Keras e Chainer)
6. Towards Data Science::GAN — Ways to improve GAN performance

Links: GANs

1. Artigo no Git (2018): High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs – Ting-Chun Wang Ming-Yu Liu Jun-Yan Zhu Andrew Tao Jan Kautz1 Bryan Catanzaro
   1. Artigo no arXiv: High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs – Ting-Chun Wang, Ming-Yu Liu, Jun-Yan Zhu, Andrew Tao, Jan Kautz, Bryan Catanzaro 
2. pix2pixHD – Pytorch implementation of photorealistic image-to-image translation. It can be used for turning semantic label maps into photo-realistic images or synthesizing portraits from face label maps. 
3. deblur-gan – Keras implementation of the paper DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks – https://github.com/RaphaelMeudec/deblur-gan
4. DeblurGAN – Pytorch implementation of the paper DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks – https://github.com/KupynOrest/DeblurGAN
5. Microscope Image Focus Quality Classifier – https://github.com/google/microscopeimagequality
   1. Paper: Assessing microscope image focus quality with deep learning – https://link.springer.com/content/pdf/10.1186/s12859-018-2087-4.pdf
6. Paper: Image Quality Assessment Guided Deep Neural Networks Training – https://arxiv.org/pdf/1708.03880.pdf
7. Tensorflow implementation of pix2pix. Learns a mapping from input images to output images – https://github.com/affinelayer/pix2pix-tensorflow
8. CycleGAN and pix2pix in PyTorch – https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix
9. Deephunt::The GAN Zoo – A list of all named GANs! (Material muito completo de Avinash Hindupur com lista comentada muito completa de GANs)
10. OpenAI::Generative Models – Four projects that share a common theme of enhancing or using generative models
11. GAN hacks::How to Train a GAN? Tips and tricks to make GANs work
12. Medium: DOGNET: can an AI model fool a human?
13. Towards Data Science::Not just another GAN paper — SAGAN (Descreve Self- Attention Generative Adversarial Networks)

Para uma lista das 500+ veja GAN abaixo.

Links: GANs para Superresolução

Outra aplicação de GANs é superresolução: você tem uma imagem ruim e melhora a qualidade dele criando uma imagem artificial usando o resultado informações provenientes do aprendizado da GAN de um outro conjunto de imagens do mesmo tipo (Ground Truths).

1. Medium::GAN — Super Resolution GAN (SRGAN)
2. https://github.com/tensorlayer/srgan
3. Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
4. ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
5. Generative adversarial network (GAN) enabled on-chip contact microscopy
6. Super resolution with Generative Adversarial Networks – Stanford CS231n 2017

Exemplos de Aplicação

1. Medium::Machine Learning Generated Artwork Auctions Off for $ 432,500
   
2. Towards Data Science: Drawing Anime Girls With Deep Learning
   
3. neurohive.io::Facial Surface and Texture Synthesis via GAN
4. goodaudience::Vid2Vid — Conditional GANs for Video-to-Video Synthesis
   1. versão em neurohive.io: https://neurohive.io/en/state-of-the-art/vid2vid-conditional-gans-for-video-to-video-synthesis/
   2. Git::https://tcwang0509.github.io/vid2vid/ (Pytorch)

Datasets

1. GoPro Large

Neural Style Transfer

NST é uma técnica onde se trabalha uma imagem de entrada, uma imagem de conteúdo,  e uma imagem de referência de estilo. A imagem de entrada costuma ser, inicialmente, uma cópia da imagem de conteúdo. O objetivo é para iterativamente aplicar o estilo da imagem de referência de estilo à imagem de entrada, gerando uma nova imagem de saída, com o conteúdo da imagem de entrada e o estilo da imagem de referência de estilo.

Os efeitos finais são similares à transferência video-a-video ou iamgem-a-imagem em GANs, mas o princípio envolvido nas CNNs usadas é diferente.

O diagrama abaixo mostra  esquematicamente o processo:

Nesta rede foi usada uma VGG19 pré-treinada como extrator de características. A animação adiante mostra o processo iterativo de aplicação de estilo:

Este conteúdo foi extraído de Turning G.O.T. Characters into White Walkers.

Tutoriais e Explanações de Neural Style Transfer

1. Neural Style Transfer: A Review (2018) – Yongcheng Jing, Yezhou Yang, Zunlei Feng, Jingwen Ye, Yizhou Yu, Mingli Song
2. Medium::Turning G.O.T. Characters into White Walkers — Exploring Neural Style Transfer (Tutorial com PyTorch)
3. Medium::Neural Artistic Style Transfer: A Comprehensive Look (Tutorial com PyTorch)
4. Medium::Neural Style Transfer: Creating Art with Deep Learning using tf.keras and eager execution (Tutorial com TensorFlow puro)
5. pyimagesearch::Neural Style Transfer with OpenCV (Tutorial com o pacote DNN do OpenCV)
6. Towards Data Science::A brief introduction to Neural Style Transfer

Recursos para usar NST Online

1. Deep Style – Using deep learning for artistic style transfer – A simple, scalable API for machine intelligence
2. AI Painter – See your photo turned into artwork in seconds! – Neural Network Powered Photo to Painting
3. deepart.io::Turn your photos into art – Repaint your picture in the style of your favorite artist

Recursos no GitHub e no arXiv

GAN

1. 3D-ED-GAN – Shape Inpainting using 3D Generative Adversarial Network and Recurrent Convolutional Networks
2. 3D-GAN – Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling (github)
3. 3D-IWGAN – Improved Adversarial Systems for 3D Object Generation and Reconstruction (github)
4. 3D-PhysNet – 3D-PhysNet: Learning the Intuitive Physics of Non-Rigid Object Deformations
5. 3D-RecGAN – 3D Object Reconstruction from a Single Depth View with Adversarial Learning (github)
6. ABC-GAN – ABC-GAN: Adaptive Blur and Control for improved training stability of Generative Adversarial Networks (github)
7. ABC-GAN – GANs for LIFE: Generative Adversarial Networks for Likelihood Free Inference
8. AC-GAN – Conditional Image Synthesis With Auxiliary Classifier GANs
9. acGAN – Face Aging With Conditional Generative Adversarial Networks
10. ACGAN – Coverless Information Hiding Based on Generative adversarial networks
11. acGAN – On-line Adaptative Curriculum Learning for GANs
12. ACtuAL – ACtuAL: Actor-Critic Under Adversarial Learning
13. AdaGAN – AdaGAN: Boosting Generative Models
14. Adaptive GAN – Customizing an Adversarial Example Generator with Class-Conditional GANs
15. AdvEntuRe – AdvEntuRe: Adversarial Training for Textual Entailment with Knowledge-Guided Examples
16. AdvGAN – Generating adversarial examples with adversarial networks
17. AE-GAN – AE-GAN: adversarial eliminating with GAN
18. AE-OT – Latent Space Optimal Transport for Generative Models
19. AEGAN – Learning Inverse Mapping by Autoencoder based Generative Adversarial Nets
20. AF-DCGAN – AF-DCGAN: Amplitude Feature Deep Convolutional GAN for Fingerprint Construction in Indoor Localization System
21. AffGAN – Amortised MAP Inference for Image Super-resolution
22. AIM – Generating Informative and Diverse Conversational Responses via Adversarial Information Maximization
23. AL-CGAN – Learning to Generate Images of Outdoor Scenes from Attributes and Semantic Layouts
24. ALI – Adversarially Learned Inference (github)
25. AlignGAN – AlignGAN: Learning to Align Cross-Domain Images with Conditional Generative Adversarial Networks
26. AlphaGAN – AlphaGAN: Generative adversarial networks for natural image matting
27. AM-GAN – Activation Maximization Generative Adversarial Nets
28. AmbientGAN – AmbientGAN: Generative models from lossy measurements (github)
29. AMC-GAN – Video Prediction with Appearance and Motion Conditions
30. AnoGAN – Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery
31. APD – Adversarial Distillation of Bayesian Neural Network Posteriors
32. APE-GAN – APE-GAN: Adversarial Perturbation Elimination with GAN
33. ARAE – Adversarially Regularized Autoencoders for Generating Discrete Structures (github)
34. ARDA – Adversarial Representation Learning for Domain Adaptation
35. ARIGAN – ARIGAN: Synthetic Arabidopsis Plants using Generative Adversarial Network
36. ArtGAN – ArtGAN: Artwork Synthesis with Conditional Categorial GANs
37. ASDL-GAN – Automatic Steganographic Distortion Learning Using a Generative Adversarial Network
38. ATA-GAN – Attention-Aware Generative Adversarial Networks (ATA-GANs)
39. Attention-GAN – Attention-GAN for Object Transfiguration in Wild Images
40. AttGAN – Arbitrary Facial Attribute Editing: Only Change What You Want (github)
41. AttnGAN – AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks (github)
42. AVID – AVID: Adversarial Visual Irregularity Detection
43. B-DCGAN – B-DCGAN:Evaluation of Binarized DCGAN for FPGA
44. b-GAN – Generative Adversarial Nets from a Density Ratio Estimation Perspective
45. BAGAN – BAGAN: Data Augmentation with Balancing GAN
46. Bayesian GAN – Deep and Hierarchical Implicit Models
47. Bayesian GAN – Bayesian GAN (github)
48. BCGAN – Bayesian Conditional Generative Adverserial Networks
49. BCGAN – Bidirectional Conditional Generative Adversarial networks
50. BEAM – Boltzmann Encoded Adversarial Machines
51. BEGAN – BEGAN: Boundary Equilibrium Generative Adversarial Networks
52. BEGAN-CS – Escaping from Collapsing Modes in a Constrained Space
53. Bellman GAN – Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN
54. BGAN – Binary Generative Adversarial Networks for Image Retrieval (github)
55. Bi-GAN – Autonomously and Simultaneously Refining Deep Neural Network Parameters by a Bi-Generative Adversarial Network Aided Genetic Algorithm
56. BicycleGAN – Toward Multimodal Image-to-Image Translation (github)
57. BiGAN – Adversarial Feature Learning
58. BinGAN – BinGAN: Learning Compact Binary Descriptors with a Regularized GAN
59. BourGAN – BourGAN: Generative Networks with Metric Embeddings
60. BranchGAN – Branched Generative Adversarial Networks for Multi-Scale Image Manifold Learning
61. BRE – Improving GAN Training via Binarized Representation Entropy (BRE) Regularization (github)
62. BridgeGAN – Generative Adversarial Frontal View to Bird View Synthesis
63. BS-GAN – Boundary-Seeking Generative Adversarial Networks
64. BubGAN – BubGAN: Bubble Generative Adversarial Networks for Synthesizing Realistic Bubbly Flow Images
65. BWGAN – Banach Wasserstein GAN
66. C-GAN – Face Aging with Contextual Generative Adversarial Nets
67. C-RNN-GAN – C-RNN-GAN: Continuous recurrent neural networks with adversarial training (github)
68. CA-GAN – Composition-aided Sketch-realistic Portrait Generation
69. CaloGAN – CaloGAN: Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks (github)
70. CAN – CAN: Creative Adversarial Networks, Generating Art by Learning About Styles and Deviating from Style Norms
71. CapsGAN – CapsGAN: Using Dynamic Routing for Generative Adversarial Networks
72. CapsuleGAN – CapsuleGAN: Generative Adversarial Capsule Network
73. CatGAN – Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks
74. CatGAN – CatGAN: Coupled Adversarial Transfer for Domain Generation
75. CausalGAN – CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training
76. CC-GAN – Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks (github)
77. cd-GAN – Conditional Image-to-Image Translation
78. CDcGAN – Simultaneously Color-Depth Super-Resolution with Conditional Generative Adversarial Network
79. CE-GAN – Deep Learning for Imbalance Data Classification using Class Expert Generative Adversarial Network
80. CFG-GAN – Composite Functional Gradient Learning of Generative Adversarial Models
81. CGAN – Conditional Generative Adversarial Nets
82. CGAN – Controllable Generative Adversarial Network
83. Chekhov GAN – An Online Learning Approach to Generative Adversarial Networks
84. ciGAN – Conditional Infilling GANs for Data Augmentation in Mammogram Classification
85. CinCGAN – Unsupervised Image Super-Resolution using Cycle-in-Cycle Generative Adversarial Networks
86. CipherGAN – Unsupervised Cipher Cracking Using Discrete GANs
87. ClusterGAN – ClusterGAN : Latent Space Clustering in Generative Adversarial Networks
88. CM-GAN – CM-GANs: Cross-modal Generative Adversarial Networks for Common Representation Learning
89. CoAtt-GAN – Are You Talking to Me? Reasoned Visual Dialog Generation through Adversarial Learning
90. CoGAN – Coupled Generative Adversarial Networks
91. ComboGAN – ComboGAN: Unrestrained Scalability for Image Domain Translation (github)
92. ConceptGAN – Learning Compositional Visual Concepts with Mutual Consistency
93. Conditional cycleGAN – Conditional CycleGAN for Attribute Guided Face Image Generation
94. constrast-GAN – Generative Semantic Manipulation with Contrasting GAN
95. Context-RNN-GAN – Contextual RNN-GANs for Abstract Reasoning Diagram Generation
96. CorrGAN – Correlated discrete data generation using adversarial training
97. Coulomb GAN – Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields
98. Cover-GAN – Generative Steganography with Kerckhoffs’ Principle based on Generative Adversarial Networks
99. cowboy – Defending Against Adversarial Attacks by Leveraging an Entire GAN
100. CR-GAN – CR-GAN: Learning Complete Representations for Multi-view Generation
101. Cramèr GAN – The Cramer Distance as a Solution to Biased Wasserstein Gradients
102. Cross-GAN – Crossing Generative Adversarial Networks for Cross-View Person Re-identification
103. crVAE-GAN – Channel-Recurrent Variational Autoencoders
104. CS-GAN – Improving Neural Machine Translation with Conditional Sequence Generative Adversarial Nets
105. CSG – Speech-Driven Expressive Talking Lips with Conditional Sequential Generative Adversarial Networks
106. CT-GAN – CT-GAN: Conditional Transformation Generative Adversarial Network for Image Attribute Modification
107. CVAE-GAN – CVAE-GAN: Fine-Grained Image Generation through Asymmetric Training
108. CycleGAN – Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks (github)
109. D-GAN – Differential Generative Adversarial Networks: Synthesizing Non-linear Facial Variations with Limited Number of Training Data
110. D-WCGAN – I-vector Transformation Using Conditional Generative Adversarial Networks for Short Utterance Speaker Verification
111. D2GAN – Dual Discriminator Generative Adversarial Nets
112. D2IA-GAN – Tagging like Humans: Diverse and Distinct Image Annotation
113. DA-GAN – DA-GAN: Instance-level Image Translation by Deep Attention Generative Adversarial Networks (with Supplementary Materials)
114. DADA – DADA: Deep Adversarial Data Augmentation for Extremely Low Data Regime Classification
115. DAGAN – Data Augmentation Generative Adversarial Networks
116. DAN – Distributional Adversarial Networks
117. DBLRGAN – Adversarial Spatio-Temporal Learning for Video Deblurring
118. DCGAN – Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks (github)
119. DE-GAN – Generative Adversarial Networks with Decoder-Encoder Output Noise
120. DeblurGAN – DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks (github)
121. DeepFD – Learning to Detect Fake Face Images in the Wild
122. Defense-GAN – Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models (github)
123. Defo-Net – Defo-Net: Learning Body Deformation using Generative Adversarial Networks
124. DeliGAN – DeLiGAN : Generative Adversarial Networks for Diverse and Limited Data (github)
125. DF-GAN – Learning Disentangling and Fusing Networks for Face Completion Under Structured Occlusions
126. DialogWAE – DialogWAE: Multimodal Response Generation with Conditional Wasserstein Auto-Encoder
127. DiscoGAN – Learning to Discover Cross-Domain Relations with Generative Adversarial Networks
128. DistanceGAN – One-Sided Unsupervised Domain Mapping
129. DM-GAN – Dual Motion GAN for Future-Flow Embedded Video Prediction
130. DMGAN – Disconnected Manifold Learning for Generative Adversarial Networks
131. DNA-GAN – DNA-GAN: Learning Disentangled Representations from Multi-Attribute Images
132. DOPING – DOPING: Generative Data Augmentation for Unsupervised Anomaly Detection with GAN
133. dp-GAN – Differentially Private Releasing via Deep Generative Model
134. DP-GAN – DP-GAN: Diversity-Promoting Generative Adversarial Network for Generating Informative and Diversified Text
135. DPGAN – Differentially Private Generative Adversarial Network
136. DR-GAN – Representation Learning by Rotating Your Faces
137. DRAGAN – How to Train Your DRAGAN (github)
138. Dropout-GAN – Dropout-GAN: Learning from a Dynamic Ensemble of Discriminators
139. DRPAN – Discriminative Region Proposal Adversarial Networks for High-Quality Image-to-Image Translation
140. DSH-GAN – Deep Semantic Hashing with Generative Adversarial Networks
141. DSP-GAN – Depth Structure Preserving Scene Image Generation
142. DTLC-GAN – Generative Adversarial Image Synthesis with Decision Tree Latent Controller
143. DTN – Unsupervised Cross-Domain Image Generation
144. DTR-GAN – DTR-GAN: Dilated Temporal Relational Adversarial Network for Video Summarization
145. DualGAN – DualGAN: Unsupervised Dual Learning for Image-to-Image Translation
146. Dualing GAN – Dualing GANs
147. DVGAN – Human Motion Modeling using DVGANs
148. Dynamics Transfer GAN – Dynamics Transfer GAN: Generating Video by Transferring Arbitrary Temporal Dynamics from a Source Video to a Single Target Image
149. E-GAN – Evolutionary Generative Adversarial Networks
150. EAR – Generative Model for Heterogeneous Inference
151. EBGAN – Energy-based Generative Adversarial Network
152. ecGAN – eCommerceGAN : A Generative Adversarial Network for E-commerce
153. ED//GAN – Stabilizing Training of Generative Adversarial Networks through Regularization
154. Editable GAN – Editable Generative Adversarial Networks: Generating and Editing Faces Simultaneously
155. EGAN – Enhanced Experience Replay Generation for Efficient Reinforcement Learning
156. EL-GAN – EL-GAN: Embedding Loss Driven Generative Adversarial Networks for Lane Detection
157. ELEGANT – ELEGANT: Exchanging Latent Encodings with GAN for Transferring Multiple Face Attributes
158. EnergyWGAN – Energy-relaxed Wassertein GANs (EnergyWGAN): Towards More Stable and High Resolution Image Generation
159. ESRGAN – ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
160. ExGAN – Eye In-Painting with Exemplar Generative Adversarial Networks
161. ExposureGAN – Exposure: A White-Box Photo Post-Processing Framework (github)
162. ExprGAN – ExprGAN: Facial Expression Editing with Controllable Expression Intensity
163. f-CLSWGAN – Feature Generating Networks for Zero-Shot Learning
164. f-GAN – f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization
165. FairGAN – FairGAN: Fairness-aware Generative Adversarial Networks
166. Fairness GAN – Fairness GAN
167. FakeGAN – Detecting Deceptive Reviews using Generative Adversarial Networks
168. FBGAN – Feedback GAN (FBGAN) for DNA: a Novel Feedback-Loop Architecture for Optimizing Protein Functions
169. FBGAN – Featurized Bidirectional GAN: Adversarial Defense via Adversarially Learned Semantic Inference
170. FC-GAN – Fast-converging Conditional Generative Adversarial Networks for Image Synthesis
171. FF-GAN – Towards Large-Pose Face Frontalization in the Wild
172. FGGAN – Adversarial Learning for Fine-grained Image Search
173. Fictitious GAN – Fictitious GAN: Training GANs with Historical Models
174. FIGAN – Frame Interpolation with Multi-Scale Deep Loss Functions and Generative Adversarial Networks
175. Fila-GAN – Synthesizing Filamentary Structured Images with GANs
176. First Order GAN – First Order Generative Adversarial Networks (github)
177. Fisher GAN – Fisher GAN
178. Flow-GAN – Flow-GAN: Bridging implicit and prescribed learning in generative models
179. FrankenGAN – rankenGAN: Guided Detail Synthesis for Building Mass-Models Using Style-Synchonized GANs
180. FSEGAN – Exploring Speech Enhancement with Generative Adversarial Networks for Robust Speech Recognition
181. FTGAN – Hierarchical Video Generation from Orthogonal Information: Optical Flow and Texture
182. FusedGAN – Semi-supervised FusedGAN for Conditional Image Generation
183. FusionGAN – Learning to Fuse Music Genres with Generative Adversarial Dual Learning
184. FusionGAN – Generating a Fusion Image: One’s Identity and Another’s Shape
185. G2-GAN – Geometry Guided Adversarial Facial Expression Synthesis
186. GAAN – Generative Adversarial Autoencoder Networks
187. GAF – Generative Adversarial Forests for Better Conditioned Adversarial Learning
188. GAGAN – GAGAN: Geometry-Aware Generative Adverserial Networks
189. GAIA – Generative adversarial interpolative autoencoding: adversarial training on latent space interpolations encourage convex latent distributions
190. GAIN – GAIN: Missing Data Imputation using Generative Adversarial Nets
191. GAMN – Generative Adversarial Mapping Networks
192. GAN – Generative Adversarial Networks (github)
193. GAN Lab – GAN Lab: Understanding Complex Deep Generative Models using Interactive Visual Experimentation
194. GAN Q-learning – GAN Q-learning
195. GAN-AD – Anomaly Detection with Generative Adversarial Networks for Multivariate Time Series
196. GAN-ATV – A Novel Approach to Artistic Textual Visualization via GAN
197. GAN-CLS – Generative Adversarial Text to Image Synthesis (github)
198. GAN-RS – Towards Qualitative Advancement of Underwater Machine Vision with Generative Adversarial Networks
199. GAN-SD – Virtual-Taobao: Virtualizing Real-world Online Retail Environment for Reinforcement Learning
200. GAN-sep – GANs for Biological Image Synthesis (github)
201. GAN-VFS – Generative Adversarial Network-based Synthesis of Visible Faces from Polarimetric Thermal Faces
202. GAN-Word2Vec – Adversarial Training of Word2Vec for Basket Completion
203. GANAX – GANAX: A Unified MIMD-SIMD Acceleration for Generative Adversarial Networks
204. GANCS – Deep Generative Adversarial Networks for Compressed Sensing Automates MRI
205. GANDI – Guiding the search in continuous state-action spaces by learning an action sampling distribution from off-target samples
206. GANG – GANGs: Generative Adversarial Network Games
207. GANG – Beyond Local Nash Equilibria for Adversarial Networks
208. GANosaic – GANosaic: Mosaic Creation with Generative Texture Manifolds
209. GANVO – GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks
210. GAP – Context-Aware Generative Adversarial Privacy
211. GAP – Generative Adversarial Privacy
212. GATS – Sample-Efficient Deep RL with Generative Adversarial Tree Search
213. GAWWN – Learning What and Where to Draw (github)
214. GC-GAN – Geometry-Contrastive Generative Adversarial Network for Facial Expression Synthesis
215. GcGAN – Geometry-Consistent Adversarial Networks for One-Sided Unsupervised Domain Mapping
216. GeneGAN – GeneGAN: Learning Object Transfiguration and Attribute Subspace from Unpaired Data (github)
217. GeoGAN – Generating Instance Segmentation Annotation by Geometry-guided GAN
218. Geometric GAN – Geometric GAN
219. GIN – Generative Invertible Networks (GIN): Pathophysiology-Interpretable Feature Mapping and Virtual Patient Generation
220. GLCA-GAN – Global and Local Consistent Age Generative Adversarial Networks
221. GM-GAN – Gaussian Mixture Generative Adversarial Networks for Diverse Datasets, and the Unsupervised Clustering of Images
222. GMAN – Generative Multi-Adversarial Networks
223. GMM-GAN – Towards Understanding the Dynamics of Generative Adversarial Networks
224. GoGAN – Gang of GANs: Generative Adversarial Networks with Maximum Margin Ranking
225. GONet – GONet: A Semi-Supervised Deep Learning Approach For Traversability Estimation
226. GP-GAN – GP-GAN: Towards Realistic High-Resolution Image Blending (github)
227. GP-GAN – GP-GAN: Gender Preserving GAN for Synthesizing Faces from Landmarks
228. GPU – A generative adversarial framework for positive-unlabeled classification
229. GRAN – Generating images with recurrent adversarial networks (github)
230. Graphical-GAN – Graphical Generative Adversarial Networks
231. GraphSGAN – Semi-supervised Learning on Graphs with Generative Adversarial Nets
232. GraspGAN – Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping
233. GT-GAN – Deep Graph Translation
234. HAN – Chinese Typeface Transformation with Hierarchical Adversarial Network
235. HAN – Bidirectional Learning for Robust Neural Networks
236. HiGAN – Exploiting Images for Video Recognition with Hierarchical Generative Adversarial Networks
237. HP-GAN – HP-GAN: Probabilistic 3D human motion prediction via GAN
238. HR-DCGAN – High-Resolution Deep Convolutional Generative Adversarial Networks
239. hredGAN – Multi-turn Dialogue Response Generation in an Adversarial Learning framework
240. IAN – Neural Photo Editing with Introspective Adversarial Networks (github)
241. IcGAN – Invertible Conditional GANs for image editing (github)
242. ID-CGAN – Image De-raining Using a Conditional Generative Adversarial Network
243. IdCycleGAN – Face Translation between Images and Videos using Identity-aware CycleGAN
244. IFcVAEGAN – Conditional Autoencoders with Adversarial Information Factorization
245. iGAN – Generative Visual Manipulation on the Natural Image Manifold (github)
246. IGMM-GAN – Coupled IGMM-GANs for deep multimodal anomaly detection in human mobility data
247. Improved GAN – Improved Techniques for Training GANs (github)
248. In2I – In2I : Unsupervised Multi-Image-to-Image Translation Using Generative Adversarial Networks
249. InfoGAN – InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets (github)
250. IntroVAE – IntroVAE: Introspective Variational Autoencoders for Photographic Image Synthesis
251. IR2VI – IR2VI: Enhanced Night Environmental Perception by Unsupervised Thermal Image Translation
252. IRGAN – IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval models
253. IRGAN – Generative Adversarial Nets for Information Retrieval: Fundamentals and Advances
254. ISGAN – Invisible Steganography via Generative Adversarial Network
255. ISP-GPM – Inner Space Preserving Generative Pose Machine
256. Iterative-GAN – Two Birds with One Stone: Iteratively Learn Facial Attributes with GANs (github)
257. IterGAN – IterGANs: Iterative GANs to Learn and Control 3D Object Transformation
258. IVE-GAN – IVE-GAN: Invariant Encoding Generative Adversarial Networks
259. iVGAN – Towards an Understanding of Our World by GANing Videos in the Wild (github)
260. IWGAN – On Unifying Deep Generative Models
261. JointGAN – JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets
262. JR-GAN – JR-GAN: Jacobian Regularization for Generative Adversarial Networks
263. KBGAN – KBGAN: Adversarial Learning for Knowledge Graph Embeddings
264. KGAN – KGAN: How to Break The Minimax Game in GAN
265. l-GAN – Representation Learning and Adversarial Generation of 3D Point Clouds
266. LAC-GAN – Grounded Language Understanding for Manipulation Instructions Using GAN-Based Classification
267. LAGAN – Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics Synthesis
268. LAPGAN – Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks (github)
269. LB-GAN – Load Balanced GANs for Multi-view Face Image Synthesis
270. LBT – Learning Implicit Generative Models by Teaching Explicit Ones
271. LCC-GAN – Adversarial Learning with Local Coordinate Coding
272. LD-GAN – Linear Discriminant Generative Adversarial Networks
273. LDAN – Label Denoising Adversarial Network (LDAN) for Inverse Lighting of Face Images
274. LeakGAN – Long Text Generation via Adversarial Training with Leaked Information
275. LeGAN – Likelihood Estimation for Generative Adversarial Networks
276. LGAN – Global versus Localized Generative Adversarial Nets
277. Lipizzaner – Towards Distributed Coevolutionary GANs
278. LR-GAN – LR-GAN: Layered Recursive Generative Adversarial Networks for Image Generation
279. LS-GAN – Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities
280. LSGAN – Least Squares Generative Adversarial Networks
281. M-AAE – Mask-aware Photorealistic Face Attribute Manipulation
282. MAD-GAN – Multi-Agent Diverse Generative Adversarial Networks
283. MAGAN – MAGAN: Margin Adaptation for Generative Adversarial Networks
284. MAGAN – MAGAN: Aligning Biological Manifolds
285. MalGAN – Generating Adversarial Malware Examples for Black-Box Attacks Based on GAN
286. MaliGAN – Maximum-Likelihood Augmented Discrete Generative Adversarial Networks
287. manifold-WGAN – Manifold-valued Image Generation with Wasserstein Adversarial Networks
288. MARTA-GAN – Deep Unsupervised Representation Learning for Remote Sensing Images
289. MaskGAN – MaskGAN: Better Text Generation via Filling in the ______
290. MC-GAN – Multi-Content GAN for Few-Shot Font Style Transfer (github)
291. MC-GAN – MC-GAN: Multi-conditional Generative Adversarial Network for Image Synthesis
292. McGAN – McGan: Mean and Covariance Feature Matching GAN
293. MD-GAN – Learning to Generate Time-Lapse Videos Using Multi-Stage Dynamic Generative Adversarial Networks
294. MDGAN – Mode Regularized Generative Adversarial Networks
295. MedGAN – Generating Multi-label Discrete Electronic Health Records using Generative Adversarial Networks
296. MedGAN – MedGAN: Medical Image Translation using GANs
297. MEGAN – MEGAN: Mixture of Experts of Generative Adversarial Networks for Multimodal Image Generation
298. MelanoGAN – MelanoGANs: High Resolution Skin Lesion Synthesis with GANs
299. memoryGAN – Memorization Precedes Generation: Learning Unsupervised GANs with Memory Networks
300. MeRGAN – Memory Replay GANs: learning to generate images from new categories without forgetting
301. MGAN – Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks (github)
302. MGGAN – Multi-Generator Generative Adversarial Nets
303. MGGAN – MGGAN: Solving Mode Collapse using Manifold Guided Training
304. MIL-GAN – Multimodal Storytelling via Generative Adversarial Imitation Learning
305. MinLGAN – Anomaly Detection via Minimum Likelihood Generative Adversarial Networks
306. MIX+GAN – Generalization and Equilibrium in Generative Adversarial Nets (GANs)
307. MIXGAN – MIXGAN: Learning Concepts from Different Domains for Mixture Generation
308. MLGAN – Metric Learning-based Generative Adversarial Network
309. MMC-GAN – A Multimodal Classifier Generative Adversarial Network for Carry and Place Tasks from Ambiguous Language Instructions
310. MMD-GAN – MMD GAN: Towards Deeper Understanding of Moment Matching Network (github)
311. MMGAN – MMGAN: Manifold Matching Generative Adversarial Network for Generating Images
312. MoCoGAN – MoCoGAN: Decomposing Motion and Content for Video Generation (github)
313. Modified GAN-CLS – Generate the corresponding Image from Text Description using Modified GAN-CLS Algorithm
314. ModularGAN – Modular Generative Adversarial Networks
315. MolGAN – MolGAN: An implicit generative model for small molecular graphs
316. MPM-GAN – Message Passing Multi-Agent GANs
317. MS-GAN – Temporal Coherency based Criteria for Predicting Video Frames using Deep Multi-stage Generative Adversarial Networks
318. MTGAN – MTGAN: Speaker Verification through Multitasking Triplet Generative Adversarial Networks
319. MuseGAN – MuseGAN: Symbolic-domain Music Generation and Accompaniment with Multi-track Sequential Generative Adversarial Networks
320. MV-BiGAN – Multi-view Generative Adversarial Networks
321. N2RPP – N2RPP: An Adversarial Network to Rebuild Plantar Pressure for ACLD Patients
322. NAN – Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human Parsing
323. NCE-GAN – Dihedral angle prediction using generative adversarial networks
324. ND-GAN – Novelty Detection with GAN
325. NetGAN – NetGAN: Generating Graphs via Random Walks
326. OCAN – One-Class Adversarial Nets for Fraud Detection
327. OptionGAN – OptionGAN: Learning Joint Reward-Policy Options using Generative Adversarial Inverse Reinforcement Learning
328. ORGAN – Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models
329. ORGAN – 3D Reconstruction of Incomplete Archaeological Objects Using a Generative Adversary Network
330. OT-GAN – Improving GANs Using Optimal Transport
331. PacGAN – PacGAN: The power of two samples in generative adversarial networks
332. PAN – Perceptual Adversarial Networks for Image-to-Image Transformation
333. PassGAN – PassGAN: A Deep Learning Approach for Password Guessing
334. PD-WGAN – Primal-Dual Wasserstein GAN
335. Perceptual GAN – Perceptual Generative Adversarial Networks for Small Object Detection
336. PGAN – Probabilistic Generative Adversarial Networks
337. PGD-GAN – Solving Linear Inverse Problems Using GAN Priors: An Algorithm with Provable Guarantees
338. PGGAN – Patch-Based Image Inpainting with Generative Adversarial Networks
339. PIONEER – Pioneer Networks: Progressively Growing Generative Autoencoder
340. Pip-GAN – Pipeline Generative Adversarial Networks for Facial Images Generation with Multiple Attributes
341. pix2pix – Image-to-Image Translation with Conditional Adversarial Networks (github)
342. pix2pixHD – High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs (github)
343. PixelGAN – PixelGAN Autoencoders
344. PM-GAN – PM-GANs: Discriminative Representation Learning for Action Recognition Using Partial-modalities
345. PN-GAN – Pose-Normalized Image Generation for Person Re-identification
346. POGAN – Perceptually Optimized Generative Adversarial Network for Single Image Dehazing
347. Pose-GAN – The Pose Knows: Video Forecasting by Generating Pose Futures
348. PP-GAN – Privacy-Protective-GAN for Face De-identification
349. PPAN – Privacy-Preserving Adversarial Networks
350. PPGN – Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space
351. PrGAN – 3D Shape Induction from 2D Views of Multiple Objects
352. ProGanSR – A Fully Progressive Approach to Single-Image Super-Resolution
353. Progressive GAN – Progressive Growing of GANs for Improved Quality, Stability, and Variation (github)
354. PS-GAN – Pedestrian-Synthesis-GAN: Generating Pedestrian Data in Real Scene and Beyond
355. PSGAN – Learning Texture Manifolds with the Periodic Spatial GAN
356. PSGAN – PSGAN: A Generative Adversarial Network for Remote Sensing Image Pan-Sharpening
357. PS²-GAN – High-Quality Facial Photo-Sketch Synthesis Using Multi-Adversarial Networks
358. RadialGAN – RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks
359. RaGAN – The relativistic discriminator: a key element missing from standard GAN
360. RAN – RAN4IQA: Restorative Adversarial Nets for No-Reference Image Quality Assessment (github)
361. RankGAN – Adversarial Ranking for Language Generation
362. RCGAN – Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs
363. ReConNN – Reconstruction of Simulation-Based Physical Field with Limited Samples by Reconstruction Neural Network
364. Recycle-GAN – Recycle-GAN: Unsupervised Video Retargeting
365. RefineGAN – Compressed Sensing MRI Reconstruction with Cyclic Loss in Generative Adversarial Networks
366. ReGAN – ReGAN: RE[LAX|BAR|INFORCE] based Sequence Generation using GANs (github)
367. RegCGAN – Unpaired Multi-Domain Image Generation via Regularized Conditional GANs
368. RenderGAN – RenderGAN: Generating Realistic Labeled Data
369. Resembled GAN – Resembled Generative Adversarial Networks: Two Domains with Similar Attributes
370. ResGAN – Generative Adversarial Network based on Resnet for Conditional Image Restoration
371. RNN-WGAN – Language Generation with Recurrent Generative Adversarial Networks without Pre-training (github)
372. RoCGAN – Robust Conditional Generative Adversarial Networks
373. RPGAN – Stabilizing GAN Training with Multiple Random Projections (github)
374. RTT-GAN – Recurrent Topic-Transition GAN for Visual Paragraph Generation
375. RWGAN – Relaxed Wasserstein with Applications to GANs
376. SAD-GAN – SAD-GAN: Synthetic Autonomous Driving using Generative Adversarial Networks
377. SAGA – Generative Adversarial Learning for Spectrum Sensing
378. SAGAN – Self-Attention Generative Adversarial Networks
379. SalGAN – SalGAN: Visual Saliency Prediction with Generative Adversarial Networks (github)
380. SAM – Sample-Efficient Imitation Learning via Generative Adversarial Nets
381. sAOG – Deep Structured Generative Models
382. SAR-GAN – Generating High Quality Visible Images from SAR Images Using CNNs
383. SBADA-GAN – From source to target and back: symmetric bi-directional adaptive GAN
384. ScarGAN – ScarGAN: Chained Generative Adversarial Networks to Simulate Pathological Tissue on Cardiovascular MR Scans
385. SCH-GAN – SCH-GAN: Semi-supervised Cross-modal Hashing by Generative Adversarial Network
386. SD-GAN – Semantically Decomposing the Latent Spaces of Generative Adversarial Networks
387. Sdf-GAN – Sdf-GAN: Semi-supervised Depth Fusion with Multi-scale Adversarial Networks
388. SEGAN – SEGAN: Speech Enhancement Generative Adversarial Network
389. SeGAN – SeGAN: Segmenting and Generating the Invisible
390. SegAN – SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation
391. Sem-GAN – Sem-GAN: Semantically-Consistent Image-to-Image Translation
392. SeqGAN – SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient (github)
393. SeUDA – Semantic-Aware Generative Adversarial Nets for Unsupervised Domain Adaptation in Chest X-ray Segmentation
394. SG-GAN – Semantic-aware Grad-GAN for Virtual-to-Real Urban Scene Adaption (github)
395. SG-GAN – Sparsely Grouped Multi-task Generative Adversarial Networks for Facial Attribute Manipulation
396. SGAN – Texture Synthesis with Spatial Generative Adversarial Networks
397. SGAN – Stacked Generative Adversarial Networks (github)
398. SGAN – Steganographic Generative Adversarial Networks
399. SGAN – SGAN: An Alternative Training of Generative Adversarial Networks
400. SGAN – CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement
401. sGAN – Generative Adversarial Training for MRA Image Synthesis Using Multi-Contrast MRI
402. SiftingGAN – SiftingGAN: Generating and Sifting Labeled Samples to Improve the Remote Sensing Image Scene Classification Baseline in vitro
403. SiGAN – SiGAN: Siamese Generative Adversarial Network for Identity-Preserving Face Hallucination
404. SimGAN – Learning from Simulated and Unsupervised Images through Adversarial Training
405. SisGAN – Semantic Image Synthesis via Adversarial Learning
406. Sketcher-Refiner GAN – Learning Myelin Content in Multiple Sclerosis from Multimodal MRI through Adversarial Training
407. SketchGAN – Adversarial Training For Sketch Retrieval
408. SketchyGAN – SketchyGAN: Towards Diverse and Realistic Sketch to Image Synthesis
409. Skip-Thought GAN – Generating Text through Adversarial Training using Skip-Thought Vectors
410. SL-GAN – Semi-Latent GAN: Learning to generate and modify facial images from attributes
411. SLSR – Sparse Label Smoothing for Semi-supervised Person Re-Identification
412. SN-DCGAN – Generative Adversarial Networks for Unsupervised Object Co-localization
413. SN-GAN – Spectral Normalization for Generative Adversarial Networks (github)
414. SN-PatchGAN – Free-Form Image Inpainting with Gated Convolution
415. Sobolev GAN – Sobolev GAN
416. Social GAN – Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks
417. Softmax GAN – Softmax GAN
418. SoPhie – SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints
419. speech-driven animation GAN – End-to-End Speech-Driven Facial Animation with Temporal GANs
420. Spike-GAN – Synthesizing realistic neural population activity patterns using Generative Adversarial Networks
421. Splitting GAN – Class-Splitting Generative Adversarial Networks
422. SR-CNN-VAE-GAN – Semi-Recurrent CNN-based VAE-GAN for Sequential Data Generation (github)
423. SRGAN – Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
424. SRPGAN – SRPGAN: Perceptual Generative Adversarial Network for Single Image Super Resolution
425. SS-GAN – Semi-supervised Conditional GANs
426. ss-InfoGAN – Guiding InfoGAN with Semi-Supervision
427. SSGAN – SSGAN: Secure Steganography Based on Generative Adversarial Networks
428. SSL-GAN – Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks
429. ST-CGAN – Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal
430. ST-GAN – Style Transfer Generative Adversarial Networks: Learning to Play Chess Differently
431. ST-GAN – ST-GAN: Spatial Transformer Generative Adversarial Networks for Image Compositing
432. StackGAN – StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks (github)
433. StainGAN – StainGAN: Stain Style Transfer for Digital Histological Images
434. StarGAN – StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation (github)
435. StarGAN-VC – StarGAN-VC: Non-parallel many-to-many voice conversion with star generative adversarial networks
436. SteinGAN – Learning Deep Energy Models: Contrastive Divergence vs. Amortized MLE
437. StepGAN – Improving Conditional Sequence Generative Adversarial Networks by Stepwise Evaluation
438. Super-FAN – Super-FAN: Integrated facial landmark localization and super-resolution of real-world low resolution faces in arbitrary poses with GANs
439. SVSGAN – SVSGAN: Singing Voice Separation via Generative Adversarial Network
440. SWGAN – Solving Approximate Wasserstein GANs to Stationarity
441. SyncGAN – SyncGAN: Synchronize the Latent Space of Cross-modal Generative Adversarial Networks
442. S^2GAN – Generative Image Modeling using Style and Structure Adversarial Networks
443. T2Net – T2Net: Synthetic-to-Realistic Translation for Solving Single-Image Depth Estimation Tasks
444. table-GAN – Data Synthesis based on Generative Adversarial Networks
445. TAC-GAN – TAC-GAN – Text Conditioned Auxiliary Classifier Generative Adversarial Network (github)
446. TAN – Outline Colorization through Tandem Adversarial Networks
447. tcGAN – Cross-modal Hallucination for Few-shot Fine-grained Recognition
448. TD-GAN – Task Driven Generative Modeling for Unsupervised Domain Adaptation: Application to X-ray Image Segmentation
449. tempCycleGAN – Improving Surgical Training Phantoms by Hyperrealism: Deep Unpaired Image-to-Image Translation from Real Surgeries
450. tempoGAN – tempoGAN: A Temporally Coherent, Volumetric GAN for Super-resolution Fluid Flow
451. TequilaGAN – TequilaGAN: How to easily identify GAN samples
452. Text2Shape – Text2Shape: Generating Shapes from Natural Language by Learning Joint Embeddings
453. textGAN – Generating Text via Adversarial Training
454. TextureGAN – TextureGAN: Controlling Deep Image Synthesis with Texture Patches
455. TGAN – Temporal Generative Adversarial Nets
456. TGAN – Tensorizing Generative Adversarial Nets
457. TGAN – Tensor-Generative Adversarial Network with Two-dimensional Sparse Coding: Application to Real-time Indoor Localization
458. TGANs-C – To Create What You Tell: Generating Videos from Captions
459. tiny-GAN – Analysis of Nonautonomous Adversarial Systems
460. TP-GAN – Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis
461. TreeGAN – TreeGAN: Syntax-Aware Sequence Generation with Generative Adversarial Networks
462. Triple-GAN – Triple Generative Adversarial Nets
463. tripletGAN – TripletGAN: Training Generative Model with Triplet Loss
464. TV-GAN – TV-GAN: Generative Adversarial Network Based Thermal to Visible Face Recognition
465. Twin-GAN – Twin-GAN — Unpaired Cross-Domain Image Translation with Weight-Sharing GANs
466. UGACH – Unsupervised Generative Adversarial Cross-modal Hashing
467. UGAN – Enhancing Underwater Imagery using Generative Adversarial Networks
468. Unim2im – Unsupervised Image-to-Image Translation with Generative Adversarial Networks (github)
469. UNIT – Unsupervised Image-to-image Translation Networks (github)
470. Unrolled GAN – Unrolled Generative Adversarial Networks (github)
471. UT-SCA-GAN – Spatial Image Steganography Based on Generative Adversarial Network
472. UV-GAN – UV-GAN: Adversarial Facial UV Map Completion for Pose-invariant Face Recognition
473. VA-GAN – Visual Feature Attribution using Wasserstein GANs
474. VAC+GAN – Versatile Auxiliary Classifier with Generative Adversarial Network (VAC+GAN), Multi Class Scenarios
475. VAE-GAN – Autoencoding beyond pixels using a learned similarity metric
476. VariGAN – Multi-View Image Generation from a Single-View
477. VAW-GAN – Voice Conversion from Unaligned Corpora using Variational Autoencoding Wasserstein Generative Adversarial Networks
478. VEEGAN – VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning (github)
479. VGAN – Generating Videos with Scene Dynamics (github)
480. VGAN – Generative Adversarial Networks as Variational Training of Energy Based Models (github)
481. VGAN – Text Generation Based on Generative Adversarial Nets with Latent Variable
482. ViGAN – Image Generation and Editing with Variational Info Generative Adversarial Networks
483. VIGAN – VIGAN: Missing View Imputation with Generative Adversarial Networks
484. VoiceGAN – Voice Impersonation using Generative Adversarial Networks
485. VOS-GAN – VOS-GAN: Adversarial Learning of Visual-Temporal Dynamics for Unsupervised Dense Prediction in Videos
486. VRAL – Variance Regularizing Adversarial Learning
487. WaterGAN – WaterGAN: Unsupervised Generative Network to Enable Real-time Color Correction of Monocular Underwater Images
488. WaveGAN – Synthesizing Audio with Generative Adversarial Networks
489. WaveletGLCA-GAN – Global and Local Consistent Wavelet-domain Age Synthesis
490. weGAN – Generative Adversarial Nets for Multiple Text Corpora
491. WGAN – Wasserstein GAN (github)
492. WGAN-CLS – Text to Image Synthesis Using Generative Adversarial Networks
493. WGAN-GP – Improved Training of Wasserstein GANs (github)
494. WGAN-L1 – Subsampled Turbulence Removal Network
495. WS-GAN – Weakly Supervised Generative Adversarial Networks for 3D Reconstruction
496. X-GANs – X-GANs: Image Reconstruction Made Easy for Extreme Cases
497. XGAN – XGAN: Unsupervised Image-to-Image Translation for many-to-many Mappings
498. ZipNet-GAN – ZipNet-GAN: Inferring Fine-grained Mobile Traffic Patterns via a Generative Adversarial Neural Network
499. α-GAN – Variational Approaches for Auto-Encoding Generative Adversarial Networks (github)
500. β-GAN – Annealed Generative Adversarial Networks
501. Δ-GAN – Triangle Generative Adversarial Networks

Copyright © 2018 Aldo von Wangenheim/INCoD/Universidade Federal de Santa Catarina