Only awesome is awesome. This is a curation, not a collection.
This list is about what GANs are used for. General GAN papers whose contribution is the model
itself (DCGAN, BEGAN, WGAN, …) are not included as entries — only genuine landmarks make the
short list at the top. Pure theory / loss-function papers are out of scope; diffusion-only work is
out of scope (GAN+diffusion hybrids are fine).
🏷 Legend: 📄 paper · 💻 code · 🌐 project/demo · 🎬 video · 📝 blog
🤝 Contributions welcome — see CONTRIBUTING.md.
🏛 The landmark papers that I respect
| Paper |
Venue |
Year |
Links |
| Generative Adversarial Networks |
NeurIPS |
2014 |
📄 💻 |
| Unsupervised Representation Learning with Deep Convolutional GANs (DCGAN) |
ICLR |
2016 |
📄 💻 |
| Improved Techniques for Training GANs |
NeurIPS |
2016 |
📄 💻 |
| BEGAN: Boundary Equilibrium Generative Adversarial Networks |
— |
2017 |
📄 💻 |
| Training Generative Adversarial Networks with Limited Data (StyleGAN2-ADA) |
NeurIPS |
2020 |
📄 💻 |
| The GAN is dead; long live the GAN! A Modern GAN Baseline (R3GAN) |
NeurIPS |
2024 |
📄 💻 |
Contents
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Applications using GANs
🔤 Font generation
| Title |
Venue |
Year |
Links |
| Learning Chinese Character Style with Conditional GAN (zi2zi) |
— |
2017 |
💻 📝 |
| Artistic Glyph Image Synthesis via One-Stage Few-Shot Learning (AGIS-Net) |
SIGGRAPH Asia |
2019 |
📄 💻 |
| Attribute2Font: Creating Fonts You Want From Attributes |
SIGGRAPH |
2020 |
📄 💻 |
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🎴 Anime character generation
| Title |
Venue |
Year |
Links |
| Towards the Automatic Anime Characters Creation with GANs |
— |
2017 |
📄 |
| AnimeGANv2: Photo to Anime Style Transfer |
— |
2021 |
💻 |
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🎭 Face Stylization
| Title |
Venue |
Year |
Links |
| JoJoGAN: One Shot Face Stylization |
ECCV |
2022 |
📄 💻 |
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🎮 Interactive Image generation
| Title |
Venue |
Year |
Links |
| Generative Visual Manipulation on the Natural Image Manifold (iGAN) |
ECCV |
2016 |
📄 💻 |
| Neural Photo Editing with Introspective Adversarial Networks |
ICLR |
2017 |
📄 💻 |
| Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold (DragGAN) |
SIGGRAPH |
2023 |
📄 💻 |
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🔧 GAN Inversion and Latent Space Editing
| Title |
Venue |
Year |
Links |
| StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery |
ICCV |
2021 |
📄 💻 |
| Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation (pSp) |
CVPR |
2021 |
📄 💻 |
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✍ Text2Image (text to image)
| Title |
Venue |
Year |
Links |
| TAC-GAN: Text Conditioned Auxiliary Classifier GAN |
— |
2017 |
📄 💻 |
| StackGAN: Text to Photo-realistic Image Synthesis with Stacked GANs |
ICCV |
2017 |
📄 💻 |
| Generative Adversarial Text to Image Synthesis |
ICML |
2016 |
📄 💻 💻 |
| Learning What and Where to Draw |
NeurIPS |
2016 |
📄 💻 |
| AttnGAN: Fine-Grained Text to Image Generation with Attentional GANs |
CVPR |
2018 |
📄 💻 |
| GigaGAN: Scaling up GANs for Text-to-Image Synthesis |
CVPR |
2023 |
📄 |
| StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis |
ICML |
2023 |
📄 💻 |
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⚡ Adversarial Diffusion Distillation (GAN-hybrid)
GANs strike back in 2024–2026: adversarial objectives distill slow diffusion samplers into one/few-step image and video generators — where GANs are most alive in 2025–2026.
| Title |
Venue |
Year |
Links |
| UFOGen: You Forward Once Large Scale Text-to-Image Generation via Diffusion GANs |
CVPR |
2024 |
📄 |
| Improved Distribution Matching Distillation for Fast Image Synthesis (DMD2) |
NeurIPS |
2024 |
📄 💻 |
| SANA-Sprint: One-Step Diffusion with Continuous-Time Consistency Distillation |
arXiv |
2025 |
📄 💻 |
| Diffusion Adversarial Post-Training for One-Step Video Generation (Seaweed-APT) |
ICML |
2025 |
📄 🌐 |
| Autoregressive Adversarial Post-Training for Real-Time Interactive Video Generation (Seaweed-APT2) |
NeurIPS |
2025 |
📄 🌐 |
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🧊 3D Object generation
| Title |
Venue |
Year |
Links |
| Parametric 3D Exploration with Stacked Adversarial Networks (pix2vox) |
— |
2016 |
💻 🎬 |
| Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling (3D-GAN) |
NeurIPS |
2016 |
📄 💻 🎬 |
| 3D Shape Induction from 2D Views of Multiple Objects |
— |
2016 |
📄 |
| Fully Convolutional Refined Auto-Encoding GANs for 3D Multi Object Scenes |
— |
2017 |
💻 📝 |
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🌐 3D-aware Image Synthesis
| Title |
Venue |
Year |
Links |
| Efficient Geometry-aware 3D Generative Adversarial Networks (EG3D) |
CVPR |
2022 |
📄 💻 |
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✏ Image Editing
| Title |
Venue |
Year |
Links |
| Invertible Conditional GANs for Image Editing (IcGAN) |
— |
2016 |
📄 💻 |
| Image De-raining Using a Conditional GAN (ID-CGAN) |
— |
2017 |
📄 💻 |
| DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks |
CVPR |
2018 |
📄 💻 |
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👴 Face Aging
| Title |
Venue |
Year |
Links |
| Age Progression/Regression by Conditional Adversarial Autoencoder (CAAE) |
CVPR |
2017 |
📄 💻 |
| CAN: Creative Adversarial Networks Generating "Art" |
— |
2017 |
📄 |
| Face Aging with Conditional Generative Adversarial Networks |
— |
2017 |
📄 |
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🕺 Human Pose Estimation
| Title |
Venue |
Year |
Links |
| Joint Discriminative and Generative Learning for Person Re-identification (DG-Net) |
CVPR |
2019 |
📄 💻 🎬 |
| Pose Guided Person Image Generation |
NeurIPS |
2017 |
📄 |
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🗣 Talking Head and Face Reenactment
| Title |
Venue |
Year |
Links |
| First Order Motion Model for Image Animation |
NeurIPS |
2019 |
📄 💻 |
| A Lip Sync Expert Is All You Need for Speech to Lip Generation In the Wild (Wav2Lip) |
ACM MM |
2020 |
📄 💻 |
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👗 Virtual Try-On
| Title |
Venue |
Year |
Links |
| VITON-HD: High-Resolution Virtual Try-On via Misalignment-Aware Normalization |
CVPR |
2021 |
📄 💻 |
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🔄 Domain-transfer (e.g. style-transfer, pix2pix, sketch2image)
| Title |
Venue |
Year |
Links |
| Image-to-Image Translation with Conditional Adversarial Networks (pix2pix) |
CVPR |
2017 |
📄 💻 🎬 |
| Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks (CycleGAN) |
ICCV |
2017 |
📄 💻 🎬 |
| Learning to Discover Cross-Domain Relations with GANs (DiscoGAN) |
ICML |
2017 |
📄 💻 |
| StarGAN: Unified Multi-Domain Image-to-Image Translation |
CVPR |
2018 |
📄 💻 |
| StarGAN v2: Diverse Image Synthesis for Multiple Domains |
CVPR |
2020 |
📄 💻 |
| Multimodal Unsupervised Image-to-Image Translation (MUNIT) |
ECCV |
2018 |
📄 💻 |
| Unsupervised Creation of Parameterized Avatars |
— |
2017 |
📄 |
| Unsupervised Cross-Domain Image Generation (DTN) |
ICLR |
2017 |
📄 |
| Precomputed Real-Time Texture Synthesis with Markovian GANs (MGANs) |
ECCV |
2016 |
📄 💻 |
| Pixel-Level Domain Transfer (PixelDTGAN) |
ECCV |
2016 |
📄 💻 |
| TextureGAN: Controlling Deep Image Synthesis with Texture Patches |
CVPR |
2018 |
📄 🌐 |
| Vincent AI Sketch Demo (NVIDIA, GTC Europe) |
— |
2017 |
📝 🎬 |
| Deep Photo Style Transfer |
CVPR |
2017 |
📄 💻 |
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🩹 Image Inpainting (hole filling)
| Title |
Venue |
Year |
Links |
| Context Encoders: Feature Learning by Inpainting |
CVPR |
2016 |
📄 💻 |
| Semantic Image Inpainting with Perceptual and Contextual Losses |
CVPR |
2017 |
📄 💻 |
| Semi-Supervised Learning with Context-Conditional GANs |
— |
2016 |
📄 |
| Free-Form Image Inpainting with Gated Convolution (DeepFill v2) |
ICCV |
2019 |
📄 💻 |
| Resolution-robust Large Mask Inpainting with Fourier Convolutions (LaMa) |
WACV |
2022 |
📄 💻 |
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🪄 Image Blending
| Title |
Venue |
Year |
Links |
| GP-GAN: Towards Realistic High-Resolution Image Blending |
ACM MM |
2019 |
📄 💻 |
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🔍 Super-resolution
| Title |
Venue |
Year |
Links |
| Image Super-Resolution Through Deep Learning (srez) |
— |
2016 |
💻 |
| Photo-Realistic Single Image Super-Resolution Using a GAN (SRGAN) |
CVPR |
2017 |
📄 💻 |
| High-Quality Face Image Super-Resolution Using Conditional GANs |
— |
2017 |
📄 |
| Analyzing Perception-Distortion Tradeoff (EPSR) |
ECCVW |
2018 |
📄 💻 |
| ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks |
ECCVW |
2018 |
📄 💻 |
| Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data |
ICCVW |
2021 |
📄 💻 |
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🖼 High-resolution image generation (large-scale image)
| Title |
Venue |
Year |
Links |
| Generating Large Images from Latent Vectors |
— |
2016 |
💻 📝 |
| Progressive Growing of GANs for Improved Quality, Stability, and Variation (PGGAN) |
ICLR |
2018 |
📄 💻 |
| Large Scale GAN Training for High Fidelity Natural Image Synthesis (BigGAN) |
ICLR |
2019 |
📄 |
| SinGAN: Learning a Generative Model from a Single Natural Image |
ICCV |
2019 |
📄 💻 |
| Analyzing and Improving the Image Quality of StyleGAN (StyleGAN2) |
CVPR |
2020 |
📄 💻 |
| Alias-Free Generative Adversarial Networks (StyleGAN3) |
NeurIPS |
2021 |
📄 💻 |
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🛡 Adversarial Examples (Defense vs Attack)
| Title |
Venue |
Year |
Links |
| SafetyNet: Detecting and Rejecting Adversarial Examples Robustly |
ICCV |
2017 |
📄 |
| Adversarial Examples for Generative Models |
— |
2017 |
📄 |
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👁 Visual Saliency Prediction (attention prediction)
| Title |
Venue |
Year |
Links |
| SalGAN: Visual Saliency Prediction with Generative Adversarial Networks |
— |
2017 |
📄 💻 |
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🎯 Object Detection/Recognition
| Title |
Venue |
Year |
Links |
| Perceptual Generative Adversarial Networks for Small Object Detection |
CVPR |
2017 |
📄 |
| Adversarial Generation of Training Examples for Vehicle License Plate Recognition |
— |
2017 |
📄 |
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🎬 Video (generation/prediction)
| Title |
Venue |
Year |
Links |
| Deep Multi-Scale Video Prediction Beyond Mean Square Error |
ICLR |
2016 |
📄 💻 |
| Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation (TecoGAN) |
SIGGRAPH |
2020 |
📄 💻 |
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🔊 Audio and Speech Synthesis
| Title |
Venue |
Year |
Links |
| Adversarial Audio Synthesis (WaveGAN) |
ICLR |
2019 |
📄 💻 |
| HiFi-GAN: GANs for Efficient and High Fidelity Speech Synthesis |
NeurIPS |
2020 |
📄 💻 |
| BigVGAN: A Universal Neural Vocoder with Large-Scale Training (v2 2024) |
ICLR |
2023 |
📄 💻 |
| Vocos: Closing the Gap between Time-domain and Fourier-based Neural Vocoders |
ICLR |
2024 |
📄 💻 |
| BemaGANv2: Discriminator Combination Strategies for GAN-based Vocoders in Long-Term Audio |
arXiv |
2025 |
📄 💻 |
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🔡 Text and Sequence Generation
| Title |
Venue |
Year |
Links |
| SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient |
AAAI |
2017 |
📄 💻 |
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🚨 Anomaly Detection
| Title |
Venue |
Year |
Links |
| Unsupervised Anomaly Detection with GANs to Guide Marker Discovery (AnoGAN) |
IPMI |
2017 |
📄 |
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🧪 Synthetic Data Generation
| Title |
Venue |
Year |
Links |
| Learning from Simulated and Unsupervised Images through Adversarial Training (SimGAN) |
CVPR |
2017 |
📄 💻 |
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🧩 Others
| Title |
Venue |
Year |
Links |
| (Physics) Location-Aware Generative Adversarial Networks for Physics Synthesis |
— |
2017 |
📄 💻 |
| (General) Spectral Normalization for Generative Adversarial Networks |
ICLR |
2018 |
📄 💻 |
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Did not use GAN, but still interesting applications.
🧑 Real-time face reconstruction
| Title |
Venue |
Year |
Links |
| Model-based Deep Convolutional Face Autoencoder for Unsupervised Monocular Reconstruction (MoFA) |
ICCV |
2017 |
📄 💻 🎬 |
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🔍 Super-resolution
| Title |
Venue |
Year |
Links |
| Learning to Simplify: Fully Convolutional Networks for Rough Sketch Cleanup |
SIGGRAPH |
2016 |
🌐 🎬 |
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🖼 Photorealistic Image generation (e.g. pix2pix, sketch2image)
| Title |
Venue |
Year |
Links |
| The Sketchy Database: Learning to Retrieve Badly Drawn Bunnies |
SIGGRAPH |
2016 |
🎬 |
| PatchMatch: A Randomized Correspondence Algorithm for Structural Image Editing |
SIGGRAPH |
2009 |
📄 💻 🎬 |
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🕺 Human Pose Estimation
| Title |
Venue |
Year |
Links |
| Knowledge-Guided Deep Fractal Neural Networks for Human Pose Estimation |
— |
2017 |
📄 💻 |
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🧊 3D Object generation
| Title |
Venue |
Year |
Links |
| 3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction |
ECCV |
2016 |
📄 💻 |
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📚 GAN tutorials with easy and simple example code for starters
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Genuinely awesome, widely-used GitHub repos built on GANs — usable code and tools, not just papers. Star counts update automatically.
Foundational model code (official / canonical)
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🧰 Implementations of various types of GANs collection
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📰 Trendy AI-application Articles
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Author
Minchul Shin, @nashory
Any recommendations to add to the list are welcome — see CONTRIBUTING.md and feel free to make pull requests! :)