mlsanityData to 14 Oct 2026

Perceptual Learned Video Compression with Recurrent Conditional GAN

arXiv 2109.03082 ↗First posted 7 Sep 2021eess.IV cs.CVcited by 41

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Abstract (arXiv)

This paper proposes a Perceptual Learned Video Compression (PLVC) approach with recurrent conditional GAN. We employ the recurrent auto-encoder-based compression network as the generator, and most importantly, we propose a recurrent conditional discriminator, which judges on raw vs. compressed video conditioned on both spatial and temporal features, including the latent representation, temporal motion and hidden states in recurrent cells. This way, the adversarial training pushes the generated video to be not only spatially photo-realistic but also temporally consistent with the groundtruth and coherent among video frames. The experimental results show that the learned PLVC model compresses video with good perceptual quality at low bit-rate, and that it outperforms the official HEVC test model (HM 16.20) and the existing learned video compression approaches for several perceptual quality metrics and user studies. The codes will be released at the project page: https://github.com/RenYang-home/PLVC.

Key facts. Cited by 41 papers in the map (data through 14 Oct 2026). Builds on 32 of its 48 references that are in the map. First posted on arXiv 7 Sep 2021.

Builds on

32 of 48 references.

References · 32

  1. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
  2. 2014Conditional Generative Adversarial Netscited by 2,162
  3. 2018Spectral Normalization for Generative Adversarial Networkscited by 1,636
  4. 2018Demystifying MMD GANscited by 1,293
  5. 2018Variational image compression with a scale hyperpriorcited by 935
  6. 2016End-to-end Optimized Image Compressioncited by 696
  7. 2018Joint Autoregressive and Hierarchical Priors for Learned Image Compressioncited by 664
  8. 2017Video Enhancement with Task-Oriented Flowcited by 619
  9. 2016Optical Flow Estimation using a Spatial Pyramid Networkcited by 424
  10. 2020High-Fidelity Generative Image Compressioncited by 338
  11. 2018DVC: An End-to-end Deep Video Compression Frameworkcited by 332
  12. 2017Are GANs Created Equal? A Large-Scale Studycited by 267
20 more
  1. 2018Generative Adversarial Networks for Extreme Learned Image Compressioncited by 219
  2. 2021Checkerboard Context Model for Efficient Learned Image Compressioncited by 202
  3. 2016Full Resolution Image Compression with Recurrent Neural Networkscited by 175
  4. 2015Variable Rate Image Compression with Recurrent Neural Networkscited by 173
  5. 2021FVC: A New Framework towards Deep Video Compression in Feature Spacecited by 153
  6. 2018Video Compression through Image Interpolationcited by 143
  7. 2018Context-adaptive Entropy Model for End-to-end Optimized Image Compressioncited by 143
  8. 2018Conditional Probability Models for Deep Image Compressioncited by 133
  9. 2019Variable Rate Deep Image Compression With a Conditional Autoencodercited by 114
  10. 2020M-LVC: Multiple Frames Prediction for Learned Video Compressioncited by 107
  11. 2017Improved Lossy Image Compression with Priming and Spatially Adaptive Bit Rates for Recurrent Networkscited by 92
  12. 2020Learning for Video Compression with Hierarchical Quality and Recurrent Enhancementcited by 90
  13. 2020Content Adaptive and Error Propagation Aware Deep Video Compressioncited by 72
  14. 2020Learning for Video Compression with Recurrent Auto-Encoder and Recurrent Probability Modelcited by 67
  15. 2020Improving Deep Video Compression by Resolution-adaptive Flow Codingcited by 58
  16. 2020Feedback Recurrent Autoencoder for Video Compressioncited by 30
  17. 2019Learned Video Compression via Joint Spatial-Temporal Correlation Explorationcited by 28
  18. 2019Learning Image and Video Compression through Spatial-Temporal Energy Compactioncited by 27
  19. 2020Adversarial Distortion for Learned Video Compressioncited by 8
  20. 2020OpenDVC: An Open Source Implementation of the DVC Video Compression Methodcited by 7

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 1; 2022: 6; 2023: 6; 2024: 7; 2025: 6; 2026: 15.

41 papers.

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  1. 2021Temporal Context Mining for Learned Video Compressioncited by 117
  2. 2023LDMVFI: Video Frame Interpolation with Latent Diffusion Modelscited by 89
  3. 2022Multi-Realism Image Compression with a Conditional Generatorcited by 80
  4. 2022VCT: A Video Compression Transformercited by 74
  5. 2023A Residual Diffusion Model for High Perceptual Quality Codec Augmentationcited by 35
  6. 2025Generative Latent Coding for Ultra-Low Bitrate Image and Video Compressioncited by 25
  7. 2022MobileCodec: Neural Inter-frame Video Compression on Mobile Devicescited by 19
  8. 2022A Coding Framework and Benchmark towards Low-Bitrate Video Understandingcited by 17
  9. 2022Advancing Learned Video Compression with In-loop Frame Predictioncited by 14
  10. 2024Motion-aware Latent Diffusion Models for Video Frame Interpolationcited by 14
  11. 2025Single-step Diffusion-based Video Coding with Semantic-Temporal Guidancecited by 13
  12. 2024SMC++: Masked Learning of Unsupervised Video Semantic Compressioncited by 12
29 more
  1. 2025DiffVC-OSD: One-Step Diffusion-based Perceptual Neural Video Compression Frameworkcited by 11
  2. 2023On the Choice of Perception Loss Function for Learned Video Compressioncited by 10
  3. 2025T-GVC: Trajectory-Guided Generative Video Coding at Ultra-Low Bitratescited by 10
  4. 2023High Visual-Fidelity Learned Video Compressioncited by 8
  5. 2024Task-Aware Encoder Control for Deep Video Compressioncited by 6
  6. 2022Boosting neural video codecs by exploiting hierarchical redundancycited by 5
  7. 2025Low-Bitrate Video Compression through Semantic-Conditioned Diffusioncited by 4
  8. 2024Laplacian-guided Entropy Model in Neural Codec with Blur-dissipated Synthesiscited by 3
  9. 2026DiffVC-RT: Towards Practical Real-Time Diffusion-based Perceptual Neural Video Compressioncited by 3
  10. 2026ProGVC: Progressive-based Generative Video Compression via Auto-Regressive Context Modelingcited by 3
  11. 2026ZeroGVC: Zero-Shot Generative Video Compression with Autoregressive Diffusion Priorscited by 3
  12. 2023Learning Kernel-Modulated Neural Representation for Efficient Light Field Compressioncited by 2
  13. 2024Low-Latency Neural Stereo Streamingcited by 2
  14. 2024Survey on Visual Signal Coding and Processing with Generative Models: Technologies, Standards and Optimizationcited by 2
  15. 2024Enhancing Quality of Compressed Images by Mitigating Enhancement Bias Towards Compression Domaincited by 1
  16. 2025Higher fidelity perceptual image and video compression with a latent conditioned residual denoising diffusion modelcited by 1
  17. 2026Efficient Video Diffusion with Sparse Information Transmission for Video Compressioncited by 1
  18. 2026Dense-Prior-Guided Generative Video Compressioncited by 1
  19. 2026Generative Video Compression with Adaptive Score Distillationcited by 1
  20. 2023Blurry Video Compression: A Trade-off between Visual Enhancement and Data Compressioncited by 0
  21. 2026A Causal Diffusion Model for Video Reconstruction from Ultra-Low-Bitrate Representationscited by 0
  22. 2026Geometric Transformation-Embedded Mamba for Learned Video Compressioncited by 0
  23. 2026A Synonymous Variational Perspective on the Rate-Distortion-Perception Tradeoffcited by 0
  24. 2026Active Sampling for Ultra-Low-Bit-Rate Video Compression via Conditional Controlled Diffusioncited by 0
  25. 2026KD-NVC: A Search-and-Distill Framework to Accelerate Neural Video Codingcited by 0
  26. 2026Generative Video Compression Based on Hierarchical Referencingcited by 0
  27. 2026DiffVC-ONE: Diffusion-based Generative Video Compression with One-Step Video Diffusion Transformercited by 0
  28. 2026A Spatiotemporal Semantic Importance-Guided Unified Compression and Editing Framework for AI-Generated Videoscited by 0
  29. 2026Unified Generative Video Compression with Autoregressive and Bidirectional Video Diffusioncited by 0

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  1. 2022Video Coding Using Learned Latent GAN Compression
  2. 2025Conditional Video Generation for High-Efficiency Video Compression
  3. 2022Microdosing: Knowledge Distillation for GAN based Compression
  4. 2026Compression as Adaptation: Implicit Visual Representation with Diffusion Foundation Models
  5. 2024Neural Video Compression with Feature Modulation
  6. 2025Generative Neural Video Compression via Video Diffusion Prior
  7. 2022PeQuENet: Perceptual Quality Enhancement of Compressed Video with Adaptation- and Attention-based Network
  8. 2024Controlling Rate, Distortion, and Realism: Towards a Single Comprehensive Neural Image Compression Model