mlsanityData to 7 Oct 2026

A survey on GANs for computer vision: Recent research, analysis and taxonomy

arXiv 2203.11242 ↗First posted 21 Mar 2022cs.LG cs.AI cs.CVcited by 15

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Abstract (arXiv)

In the last few years, there have been several revolutions in the field of deep learning, mainly headlined by the large impact of Generative Adversarial Networks (GANs). GANs not only provide an unique architecture when defining their models, but also generate incredible results which have had a direct impact on society. Due to the significant improvements and new areas of research that GANs have brought, the community is constantly coming up with new researches that make it almost impossible to keep up with the times. Our survey aims to provide a general overview of GANs, showing the latest architectures, optimizations of the loss functions, validation metrics and application areas of the most widely recognized variants. The efficiency of the different variants of the model architecture will be evaluated, as well as showing the best application area; as a vital part of the process, the different metrics for evaluating the performance of GANs and the frequently used loss functions will be analyzed. The final objective of this survey is to provide a summary of the evolution and performance of the GANs which are having better results to guide future researchers in the field.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Builds on 105 of its 214 references that are in the map. First posted on arXiv 21 Mar 2022.

Builds on

105 of 214 references.

References · 105

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38 more
  1. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  2. 2017Progressive Growing of GANs for Improved Quality, Stability, and Variationcited by 2,967
  3. 2016Perceptual Losses for Real-Time Style Transfer and Super-Resolutioncited by 2,678
  4. 2018Large Scale GAN Training for High Fidelity Natural Image Synthesiscited by 2,609
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  6. 2020Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domainscited by 2,170
  7. 2014Conditional Generative Adversarial Netscited by 2,152
  8. 2015Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networkscited by 2,048
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  13. 2016Progressive Neural Networkscited by 1,332
  14. 2021Palette: Image-to-Image Diffusion Modelscited by 1,296
  15. 2021Alias-Free Generative Adversarial Networkscited by 1,181
  16. 2017High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANscited by 1,176
  17. 2016Least Squares Generative Adversarial Networkscited by 1,000
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  20. 2018Self-Attention Generative Adversarial Networkscited by 809
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Citing papers per year: 2022: 1; 2023: 3; 2024: 7; 2025: 4.

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  1. 2024Leveraging Representations from Intermediate Encoder-blocks for Synthetic Image Detectioncited by 88
  2. 2022Data Augmentation techniques in time series domain: A survey and taxonomycited by 41
  3. 2023ArtiFact: A Large-Scale Dataset with Artificial and Factual Images for Generalizable and Robust Synthetic Image Detectioncited by 35
  4. 2023Ten Years of Generative Adversarial Nets (GANs): A survey of the state-of-the-artcited by 14
  5. 2023Diffusion Models for Generative Artificial Intelligence: An Introduction for Applied Mathematicianscited by 5
  6. 2024Generative AI in Vision: A Survey on Models, Metrics and Applicationscited by 4
  7. 2024DiffFinger: Advancing Synthetic Fingerprint Generation through Denoising Diffusion Probabilistic Modelscited by 2
  8. 2025Generative Adversarial Network based Voice Conversion: Techniques, Challenges, and Recent Advancementscited by 2
  9. 2024MaSkel: A Model for Human Whole-body X-rays Generation from Human Masking Imagescited by 1
  10. 2024Multi-view X-ray Image Synthesis with Multiple Domain Disentanglement from CT Scanscited by 1
  11. 2025Underwater Diffusion Attention Network with Contrastive Language-Image Joint Learning for Underwater Image Enhancementcited by 1
  12. 2024Towards Realistic Landmark-Guided Facial Video Inpainting Based on GANscited by 0
3 more
  1. 2024Fusion Embedding for Pose-Guided Person Image Synthesis with Diffusion Modelcited by 0
  2. 2025Real-Time Person Image Synthesis Using a Flow Matching Modelcited by 0
  3. 2025SDAKD: Student Discriminator Assisted Knowledge Distillation for Super-Resolution Generative Adversarial Networkscited by 0