mlsanityData to 7 Oct 2026

A Survey on Generative Adversarial Networks: Variants, Applications, and Training

arXiv 2006.05132 ↗First posted 9 Jun 2020cs.CV cs.LG eess.IVcited by 97

Not on the map. Why?

Abstract (arXiv)

The Generative Models have gained considerable attention in the field of unsupervised learning via a new and practical framework called Generative Adversarial Networks (GAN) due to its outstanding data generation capability. Many models of GAN have proposed, and several practical applications emerged in various domains of computer vision and machine learning. Despite GAN's excellent success, there are still obstacles to stable training. The problems are due to Nash-equilibrium, internal covariate shift, mode collapse, vanishing gradient, and lack of proper evaluation metrics. Therefore, stable training is a crucial issue in different applications for the success of GAN. Herein, we survey several training solutions proposed by different researchers to stabilize GAN training. We survey, (I) the original GAN model and its modified classical versions, (II) detail analysis of various GAN applications in different domains, (III) detail study about the various GAN training obstacles as well as training solutions. Finally, we discuss several new issues as well as research outlines to the topic.

Key facts. Cited by 97 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Jun 2020.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 12; 2022: 26; 2023: 23; 2024: 16; 2025: 16; 2026: 4.

97 papers.

Sort:

By area:

  1. 2023Text-to-image Diffusion Models in Generative AI: A Surveycited by 264
  2. 2022A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directionscited by 73
  3. 2021Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Generated Imagescited by 58
  4. 2025Text2Earth: Unlocking Text-driven Remote Sensing Image Generation with a Global-Scale Dataset and a Foundation Modelcited by 46
  5. 2022Recent Advances for Quantum Neural Networks in Generative Learningcited by 39
  6. 2024Alignment of Diffusion Models: Fundamentals, Challenges, and Futurecited by 34
  7. 2022A Review of Emerging Research Directions in Abstract Visual Reasoningcited by 33
  8. 20223D Human Motion Prediction: A Surveycited by 30
  9. 2022GAN-generated Faces Detection: A Survey and New Perspectivescited by 29
  10. 2023A Comprehensive Overview and Comparative Analysis on Deep Learning Models: CNN, RNN, LSTM, GRUcited by 25
  11. 2022A Survey on Training Challenges in Generative Adversarial Networks for Biomedical Image Analysiscited by 24
  12. 2024CharacterFactory: Sampling Consistent Characters with GANs for Diffusion Modelscited by 24
38 more
  1. 2023Precipitation nowcasting with generative diffusion modelscited by 22
  2. 2022A Comprehensive Survey on Data-Efficient GANs in Image Generationcited by 20
  3. 2023A Survey on Generative Modeling with Limited Data, Few Shots, and Zero Shotcited by 19
  4. 2022FreGAN: Exploiting Frequency Components for Training GANs under Limited Datacited by 16
  5. 2021Applications of Generative Adversarial Networks in Anomaly Detection: A Systematic Literature Reviewcited by 15
  6. 2022UDoc-GAN: Unpaired Document Illumination Correction with Background Light Priorcited by 15
  7. 2023Adversarial Score Distillation: When score distillation meets GANcited by 15
  8. 2021Hidden Convexity of Wasserstein GANs: Interpretable Generative Models with Closed-Form Solutionscited by 14
  9. 2023Ten Years of Generative Adversarial Nets (GANs): A survey of the state-of-the-artcited by 14
  10. 2024Generative AI for Unmanned Vehicle Swarms: Challenges, Applications and Opportunitiescited by 14
  11. 2025Simulating the Real World: A Unified Survey of Multimodal Generative Modelscited by 14
  12. 2025Flow Matching Meets Biology and Life Science: A Surveycited by 14
  13. 2023SequenceMatch: Imitation Learning for Autoregressive Sequence Modelling with Backtrackingcited by 13
  14. 2022HS-Diffusion: Semantic-Mixing Diffusion for Head Swappingcited by 12
  15. 2023MonoFlow: Rethinking Divergence GANs via the Perspective of Wasserstein Gradient Flowscited by 12
  16. 2023Transformer-based Generative Adversarial Networks in Computer Vision: A Comprehensive Surveycited by 10
  17. 2023An Overview on Generative AI at Scale with Edge-Cloud Computingcited by 9
  18. 2023Image Synthesis under Limited Data: A Survey and Taxonomycited by 9
  19. 2024A Comprehensive Survey on Underwater Image Enhancement Based on Deep Learningcited by 9
  20. 2024Applications of Generative AI (GAI) for Mobile and Wireless Networking: A Surveycited by 9
  21. 2024TextureCrop: Enhancing Synthetic Image Detection through Texture-based Croppingcited by 9
  22. 2022Creative Painting with Latent Diffusion Modelscited by 8
  23. 2025Zero-shot Meta-learning for Tabular Prediction Tasks with Adversarially Pre-trained Transformercited by 8
  24. 2021Game of GANs: Game-Theoretical Models for Generative Adversarial Networkscited by 6
  25. 2022Artificial intelligence approaches for materials-by-design of energetic materials: state-of-the-art, challenges, and future directionscited by 6
  26. 2023Digital Twin-based Anomaly Detection with Curriculum Learning in Cyber-physical Systemscited by 6
  27. 2024A Comprehensive Survey on Self-Supervised Learning for Recommendationcited by 6
  28. 2023Variational Mixture of HyperGenerators for Learning Distributions Over Functionscited by 5
  29. 2023Sublinear Convergence Rates of Extragradient-Type Methods: A Survey on Classical and Recent Developmentscited by 5
  30. 2025A Survey of Deep Learning Video Super-Resolutioncited by 5
  31. 2025Generative AI in Depth: A Survey of Recent Advances, Model Variants, and Real-World Applicationscited by 5
  32. 2021Learning Unsupervised Cross-domain Image-to-Image Translation Using a Shared Discriminatorcited by 4
  33. 2021Synthetic flow-based cryptomining attack generation through Generative Adversarial Networkscited by 4
  34. 2022Federated Split GANscited by 4
  35. 2022A Self-attention Guided Multi-scale Gradient GAN for Diversified X-ray Image Synthesiscited by 4
  36. 2021A Deterministic Sampling Method via Maximum Mean Discrepancy Flow with Adaptive Kernelcited by 3
  37. 2022Towards the Generation of Synthetic Images of Palm Vein Patterns: A Reviewcited by 3
  38. 2023Enhancing Deep Neural Network Training Efficiency and Performance through Linear Predictioncited by 3

50 most cited of 97 All 97 (JSON)