mlsanityData to 7 Oct 2026

Generative Adversarial Networks: An Overview

arXiv 1710.07035 ↗First posted 19 Oct 2017cs.CVcited by 588

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Cited by 99 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Generative adversarial networks (GANs) provide a way to learn deep representations without extensively annotated training data. They achieve this through deriving backpropagation signals through a competitive process involving a pair of networks. The representations that can be learned by GANs may be used in a variety of applications, including image synthesis, semantic image editing, style transfer, image super-resolution and classification. The aim of this review paper is to provide an overview of GANs for the signal processing community, drawing on familiar analogies and concepts where possible. In addition to identifying different methods for training and constructing GANs, we also point to remaining challenges in their theory and application.

Key facts. Cited by 588 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Oct 2017.

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Citing papers per year: 2021: 66; 2022: 98; 2023: 149; 2024: 161; 2025: 87; 2026: 27.

588 papers.

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  1. 2022Generative Adversarial Networkscited by 5,603
  2. 2023T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Modelscited by 1,339
  3. 2022Diffusion Models: A Comprehensive Survey of Methods and Applicationscited by 1,107
  4. 2024VideoCrafter2: Overcoming Data Limitations for High-Quality Video Diffusion Modelscited by 568
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  6. 2022Brain Imaging Generation with Latent Diffusion Modelscited by 267
  7. 2022A Survey on Generative Diffusion Modelcited by 238
  8. 2024Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMscited by 224
  9. 2023Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifoldcited by 218
  10. 2022ProDiff: Progressive Fast Diffusion Model For High-Quality Text-to-Speechcited by 147
  11. 2023RAPHAEL: Text-to-Image Generation via Large Mixture of Diffusion Pathscited by 141
  12. 2022FastDiff: A Fast Conditional Diffusion Model for High-Quality Speech Synthesiscited by 136
38 more
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  2. 2023VidToMe: Video Token Merging for Zero-Shot Video Editingcited by 111
  3. 2024DiTFastAttn: Attention Compression for Diffusion Transformer Modelscited by 109
  4. 2023Diffusion Models for Image Restoration and Enhancement: A Comprehensive Surveycited by 108
  5. 2023Advancing Pose-Guided Image Synthesis with Progressive Conditional Diffusion Modelscited by 104
  6. 2021Deep Generative Models in Engineering Design: A Reviewcited by 103
  7. 2024IMAGDressing-v1: Customizable Virtual Dressingcited by 100
  8. 2024Flow map matching with stochastic interpolants: A mathematical framework for consistency modelscited by 99
  9. 2023Vision-Language Models in Remote Sensing: Current Progress and Future Trendscited by 93
  10. 2024MAISI: Medical AI for Synthetic Imagingcited by 86
  11. 2023ChatGPT is not all you need. A State of the Art Review of large Generative AI modelscited by 85
  12. 2024Self-Play Fine-Tuning of Diffusion Models for Text-to-Image Generationcited by 85
  13. 2023DiffFit: Unlocking Transferability of Large Diffusion Models via Simple Parameter-Efficient Fine-Tuningcited by 82
  14. 2022NOMAD: Nonlinear Manifold Decoders for Operator Learningcited by 81
  15. 2024Seamless Human Motion Composition with Blended Positional Encodingscited by 77
  16. 2024An Overview of Diffusion Models: Applications, Guided Generation, Statistical Rates and Optimizationcited by 72
  17. 2024Fusion-Mamba for Cross-modality Object Detectioncited by 67
  18. 2024Towards Generalizable Tumor Synthesiscited by 65
  19. 2024FasterDiT: Towards Faster Diffusion Transformers Training without Architecture Modificationcited by 64
  20. 2022CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIPcited by 60
  21. 2024360DVD: Controllable Panorama Video Generation with 360-Degree Video Diffusion Modelcited by 56
  22. 2024Boosting Consistency in Story Visualization with Rich-Contextual Conditional Diffusion Modelscited by 54
  23. 2021Adversarial Text-to-Image Synthesis: A Reviewcited by 52
  24. 2021Machine Learning in the Search for New Fundamental Physicscited by 50
  25. 2023Efficient Neural Music Generationcited by 50
  26. 2023Customizing 360-Degree Panoramas through Text-to-Image Diffusion Modelscited by 47
  27. 2021Protecting Intellectual Property of Generative Adversarial Networks from Ambiguity Attackcited by 45
  28. 2022UCC: Uncertainty guided Cross-head Co-training for Semi-Supervised Semantic Segmentationcited by 45
  29. 2022DiffStyler: Controllable Dual Diffusion for Text-Driven Image Stylizationcited by 45
  30. 2024Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modellingcited by 43
  31. 2023White-box Membership Inference Attacks against Diffusion Modelscited by 42
  32. 2024PoCo: Policy Composition from and for Heterogeneous Robot Learningcited by 42
  33. 2024SemantiCodec: An Ultra Low Bitrate Semantic Audio Codec for General Soundcited by 42
  34. 2023JEN-1: Text-Guided Universal Music Generation with Omnidirectional Diffusion Modelscited by 41
  35. 2024A Survey on Long Video Generation: Challenges, Methods, and Prospectscited by 40
  36. 2024HiCo: Hierarchical Controllable Diffusion Model for Layout-to-image Generationcited by 39
  37. 2024CleanDiffuser: An Easy-to-use Modularized Library for Diffusion Models in Decision Makingcited by 38
  38. 2022Deep Learning Methods for Abstract Visual Reasoning: A Survey on Raven's Progressive Matricescited by 37

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