Generative Adversarial Networks

Also known as GAN

Ask about this topic

Overview

Generative Adversarial Networks learn to produce data by training a generator against a discriminator that distinguishes generated samples from real ones. Common approaches include conditional GANs for controlled generation, Wasserstein GANs for more stable training, cycle-consistent models for unpaired translation, and StyleGAN-family models for high-quality images. GANs are used for image and audio synthesis, data augmentation, time-series modeling, and scientific applications, often with added constraints from labels, physics, or domain knowledge. A central tension is balancing realism, diversity, and training stability; strong visual or distributional metrics do not always predict whether synthetic data helps downstream tasks, and diffusion models are an important alternative.

Latest papers

CardsList

178 papers20 papers in the last four weeks, up 18% on the four weeks before. 0.1% of all new papers.

  1. IncepDeHazeGAN: Novel Satellite Image Dehazing

    Apr 17, 2026Tejeswar Pokuri, Shivarth RaiImage RestorationImage Dehazing

    No Institute Given

  2. Enhancing Hazy Wildlife Imagery: AnimalHaze3k and IncepDehazeGan

    Apr 17, 2026Shivarth Rai, Tejeswar PokuriSynthetic Data GenerationImage Restoration

    Department of Computer Science Manipal Institute of Technology, Manipal, India

  3. Synthetic data in cryptocurrencies using generative models

    Apr 17, 2026André Saimon S. Sousa, Otto Pires, Frank Acasiete +3Synthetic Data GenerationTime Series Generation

    Universidade SENAI CIMATEC Salvador, Brazil · CoFi, Universidad Jorge Tadeo Lozano Bogotá, Colombia · Universidade do Estado da Bahia - UNEB Salvador, Brazil

  4. Beyond Sequential Prediction: Learning Financial Market Dynamics in Volatile and Non-Stationary Environments through Sentiment-Conditioned Generative Modelling

    Apr 13, 2026Alexis Lazanas, Spyridon KarpouzisTime Series ForecastingNon-Stationary Time Series Forecasting

    Department of Mechanical Engineering and Aeronautics, University of Patras, Rion-Patras, Greece · FICC Market Risk, BNP Paribas CIB, London, United Kingdom

  5. Sign-to-Speech Prosody Transfer via Sign Reconstruction-based GAN

    Apr 12, 2026Toranosuke Manabe, Yuto Shibata, Shinnosuke Takamichi +1Generative Adversarial NetworksText-to-Speech

    Keio University, Yagami Campus, Yokohama Kanagawa 223-8522, Japan

  6. Domain-generalizable Face Anti-Spoofing with Patch-based Multi-tasking and Artifact Pattern Conversion

    Apr 10, 2026Seungjin Jung, Yonghyun Jeong, Minha Kim +3Face Anti-SpoofingDomain Generalization

    Department of Artificial Intelligence, Chung-Ang University, Seoul, 06974, Korea · Team of Image Vision, Naver Cloud, Seongnam, 13561, Korea · Department of Human-centric AI, Nota AI, Seoul, 06164, Korea +2

  7. GAN-based Domain Adaptation for Image-aware Layout Generation in Advertising Poster Design

    Apr 8, 2026Chenchen Xu, Min Zhou, Tiezheng Ge +1Generative Adversarial Networks

    Anhui Normal University, Wuhu, China · Zhejiang University, Hangzhou, China · Shenzhen Bay Laboratory, Shenzhen, China +1

  8. DAGAF: A directed acyclic generative adversarial framework for joint structure learning and tabular data synthesis

    Apr 5, 2026Hristo Petkov, Calum MacLellan, Feng DongCausal Structure LearningTabular Data Synthesis

    Department of Computer and Information Sciences, University of Strathclyde, 16 Richmond Street, Glasgow, G1 1XQ, Lanarkshire, United Kingdom.

  9. Cognitive Energy Modeling for Neuroadaptive Human-Machine Systems using EEG and WGAN-GP

    Apr 2, 2026Sriram Sattiraju, Vaibhav Gollapalli, Aryan Shah +1EEG Signal GenerationCognitive Modeling

    Department of Computer Science, University of Texas at Austin, Austin, TX 78712, USA · Department of Learning Technologies, University of North Texas, Denton, TX 76203, USA

  10. Looking into a Pixel by Nonlinear Unmixing -- A Generative Approach

    Apr 1, 2026Maofeng Tang, Hairong QiSpectral UnmixingHyperspectral Unmixing

    Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville

  11. Brain MR Image Synthesis with 3D Multi-Contrast Self-Attention GAN

    Mar 31, 2026Zaid A. Abod, Furqan AzizMedical Image Synthesis3D Medical Imaging

    School of Computing and Mathematical Sciences, University of Leicester, Leicester, United Kingdom.

  12. GMA-SAWGAN-GP: A Novel Data Generative Framework to Enhance IDS Detection Performance

    Mar 30, 2026Ziyu Mu, Xiyu Shi, Safak DoganSynthetic Data AugmentationNetwork Intrusion Detection

    Institute for Digital Technologies, Loughborough University London, London E20 3BS, UK.

  13. GAN-Enhanced Deep Reinforcement Learning for Semantic-Aware Resource Allocation in 6G Network Slicing

    Mar 27, 2026Daniel Benniah JohnNetwork SlicingWireless Resource Allocation

    University of California, Berkeley, CA, USA

  14. PoiCGAN: A Targeted Poisoning Based on Feature-Label Joint Perturbation in Federated Learning

    Mar 24, 2026Tao Liu, Jiguang Lv, Dapeng Man +7Data Poisoning AttacksAdversarial Attacks

    College of Computer Science and Technology, Harbin Engineering University, Harbin, 150001, China

  15. Graph-Informed Adversarial Modeling: Infimal Subadditivity of Interpolative Divergences

    Mar 20, 2026Panagiota Birmpa, Eric Joseph HallGenerative Adversarial Networks

    Heriot--Watt University · Maxwell Institute for Mathematical Sciences · School of Mathematical and Computer Sciences Heriot–Watt University Edinburgh EH14 4AS, UK +1

  16. A Novel Solution for Zero-Day Attack Detection in IDS using Self-Attention and Jensen-Shannon Divergence in WGAN-GP

    Mar 19, 2026Ziyu Mu, Xiyu Shi, Safak DoganNetwork Intrusion DetectionGenerative Adversarial Networks

    Institute for Digital Technologies, Loughborough University, London, UK

  17. Epistemic Generative Adversarial Networks

    Mar 18, 2026Muhammad Mubashar, Fabio CuzzolinGenerative ModelingGenerative Adversarial Networks

    School of Engineering, Computing and Mathematics, Oxford Brookes University, UK.

  18. DSS-GAN: Directional State Space GAN with Mamba backbone for Class-Conditional Image Synthesis

    Mar 18, 2026Aleksander Ogonowski, Konrad Klimaszewski, Przemysław RokitaGenerative Adversarial NetworksConditional Image Generation

    Warsaw University of Technology · National Centre for Nuclear Research

  19. When Generative Augmentation Hurts: A Benchmark Study of GAN and Diffusion Models for Bias Correction in AI Classification Systems

    Mar 17, 2026Shesh Narayan Gupta, Nik Bear BrownSynthetic Data AugmentationClass-Imbalanced Learning

    College of Engineering, Northeastern University, Boston, MA 02115, USA

  20. Seismic full-waveform inversion based on a physics-driven generative adversarial network

    Mar 16, 2026Xinyi Zhang, Caiyun Liu, Jie Xiong +1Seismic ImagingInverse Problems

    School of Electronic Information and Electrical Engineering, Yangtze University Jingzhou, Hubei 434023, P.R.China

  21. PGcGAN: Pathological Gait-Conditioned GAN for Human Gait Synthesis

    Mar 15, 2026Mritula Chandrasekaran, Sanket Kachole, Jarek Francik +1Human Motion GenerationGait Analysis

    Kingston University, Kingston Upon Thames, London, UK · Indiana University Health, Indianapolis, Indiana

  22. A Systematic Benchmark of GAN Architectures for MRI-to-CT Synthesis

    Mar 13, 2026Alessandro Pesci, Valerio Guarrasi, Marco Alì +2Medical Image SynthesisGenerative Adversarial Networks

    Unit of Artificial Intelligence and Computer Systems, Department of Engineering, Università Campus Bio-Medico di Roma, Italy · CDI Centro Diagnostico Italiano S.p.A., Milan, Italy · University of Milan-Bicocca, Milan, Italy +1

  23. Synthetic Melanoma Image Generation and Evaluation Using Generative Adversarial Networks

    Mar 13, 2026Pei-Yu Lin, Yidan Shen, Neville Mathew +6Medical Image SynthesisSynthetic Data Evaluation

    Department of Engineering Technology, University of Houston, Sugar Land, TX 77479, USA · Department of Electrical and Computer Engineering, University of Houston, Houston, TX 77204, USA · Department of Information Science Technology, University of Houston, Sugar Land, TX 77479, USA +5

  24. A Decade of Generative Adversarial Networks for Porous Material Reconstruction

    Mar 12, 2026Ali Sadeghkhani, Brandon Bennett, Masoud Babaei +1Generative Adversarial Networks3D Reconstruction

    School of Computer Science, University of Leeds, Leeds, UK. · School of Chemical Engineering, The University of Manchester, Manchester, UK.

  25. RAF: Relativistic Adversarial Feedback For Universal Speech Synthesis

    Mar 12, 2026Yongjoon Lee, Jung-Woo ChoiNeural VocodersSpeech Processing

    Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea

  26. Toward Complex-Valued Neural Networks for Waveform Generation

    Mar 12, 2026Hyung-Seok Oh, Deok-Hyeon Cho, Seung-Bin Kim +1Neural VocodersComplex-Valued Neural Networks

    Department of Artificial Intelligence Korea University Seoul, Republic of Korea

  27. Gen-Fab: A Variation-Aware Generative Model for Predicting Fabrication Variations in Nanophotonic Devices

    Mar 12, 2026Rambod Azimi, Yuri Grinberg, Dan-Xia Xu +1ManufacturingDigital Twins

    Department of Electrical and Computer Engineering, McGill University, Montreal, QC, Canada. · Digital Technologies Research Center, National Research Council of Canada, Ottawa, ON, Canada. · Quantum and Nanotechnologies Research Center, National Research Council of Canada, Ottawa, ON, Canada.

  28. HyPER-GAN: Hybrid Patch-Based Image-to-Image Translation for Real-Time Photorealism Enhancement in Game Engines

    Mar 11, 2026Stefanos Pasios, Nikos NikolaidisImage-to-Image TranslationGenerative Adversarial Networks

    School of Informatics, Aristotle University of Thessaloniki (AUTH), Thessaloniki, 54124, Greece

  29. Well Log-Guided Synthesis of Subsurface Images from Sparse Petrography Data Using cGANs

    Mar 10, 2026Ali Sadeghkhani, A. Assadi, B. Bennett +1Image GenerationComputational Imaging

    School of Computer Science, University of Leeds, Leeds, UK · TEC

  30. Component-Aware Sketch-to-Image Generation Using Self-Attention Encoding and Coordinate-Preserving Fusion

    Mar 10, 2026Ali Zia, Muhammad Umer Ramzan, Usman Ali +3Image GenerationConditional Image Generation

    School of Computing, Engineering and Mathematical Sciences La Trobe University. · Gujranwala Institute of Future Technologies(GIFT) University. · Data61, CSIRO. +1