mlsanityData to 7 Oct 2026

High-Fidelity Generative Image Compression

arXiv 2006.09965 ↗First posted 17 Jun 2020eess.IV cs.CV cs.LGcited by 331

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Cited by 61 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

We extensively study how to combine Generative Adversarial Networks and learned compression to obtain a state-of-the-art generative lossy compression system. In particular, we investigate normalization layers, generator and discriminator architectures, training strategies, as well as perceptual losses. In contrast to previous work, i) we obtain visually pleasing reconstructions that are perceptually similar to the input, ii) we operate in a broad range of bitrates, and iii) our approach can be applied to high-resolution images. We bridge the gap between rate-distortion-perception theory and practice by evaluating our approach both quantitatively with various perceptual metrics, and with a user study. The study shows that our method is preferred to previous approaches even if they use more than 2x the bitrate.

Key facts. Cited by 331 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Jun 2020.

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Citing papers per year: 2021: 33; 2022: 45; 2023: 56; 2024: 74; 2025: 64; 2026: 59.

331 papers.

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  1. 2023A Comprehensive Survey of Continual Learning: Theory, Method and Applicationcited by 860
  2. 2021SoundStream: An End-to-End Neural Audio Codeccited by 756
  3. 2023Finite Scalar Quantization: VQ-VAE Made Simplecited by 425
  4. 2022ELIC: Efficient Learned Image Compression with Unevenly Grouped Space-Channel Contextual Adaptive Codingcited by 296
  5. 2021Deblurring via Stochastic Refinementcited by 248
  6. 2022Lossy Image Compression with Conditional Diffusion Modelscited by 165
  7. 2021Implicit Neural Representations for Image Compressioncited by 161
  8. 2022The Devil Is in the Details: Window-based Attention for Image Compressioncited by 141
  9. 2021ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesiscited by 122
  10. 2023Towards image compression with perfect realism at ultra-low bitratescited by 99
  11. 2024GaussianImage: 1000 FPS Image Representation and Compression by 2D Gaussian Splattingcited by 97
  12. 2023Improving Statistical Fidelity for Neural Image Compression with Implicit Local Likelihood Modelscited by 90
38 more
  1. 2022Lossy Compression with Gaussian Diffusioncited by 87
  2. 2022COIN++: Neural Compression Across Modalitiescited by 81
  3. 2022Memory Replay with Data Compression for Continual Learningcited by 80
  4. 2022Multi-Realism Image Compression with a Conditional Generatorcited by 79
  5. 2022An Introduction to Neural Data Compressioncited by 78
  6. 2021Nonlinear Transform Source-Channel Coding for Semantic Communicationscited by 73
  7. 2023Text + Sketch: Image Compression at Ultra Low Ratescited by 63
  8. 2021Variable-Rate Deep Image Compression through Spatially-Adaptive Feature Transformcited by 56
  9. 2024Towards Extreme Image Compression with Latent Feature Guidance and Diffusion Priorcited by 56
  10. 2023High-Fidelity Image Compression with Score-based Generative Modelscited by 53
  11. 2021Lossy Compression for Lossless Predictioncited by 51
  12. 2022Wireless Deep Video Semantic Transmissioncited by 49
  13. 2021Universal Rate-Distortion-Perception Representations for Lossy Compressioncited by 46
  14. 2021Perceptual Learned Video Compression with Recurrent Conditional GANcited by 38
  15. 2021Neural Video Compression using GANs for Detail Synthesis and Propagationcited by 35
  16. 2022Towards Semantic Communications: Deep Learning-Based Image Semantic Codingcited by 35
  17. 2021Image2Reverb: Cross-Modal Reverb Impulse Response Synthesiscited by 34
  18. 2024Lossy Image Compression with Foundation Diffusion Modelscited by 34
  19. 2023A Residual Diffusion Model for High Perceptual Quality Codec Augmentationcited by 33
  20. 2022Image Compression with Product Quantized Masked Image Modelingcited by 32
  21. 2022Image Coding for Machines with Omnipotent Feature Learningcited by 31
  22. 2022Extreme Generative Image Compression by Learning Text Embedding from Diffusion Modelscited by 30
  23. 2024MISC: Ultra-low Bitrate Image Semantic Compression Driven by Large Multimodal Modelcited by 29
  24. 2025StableCodec: Taming One-Step Diffusion for Extreme Image Compressioncited by 29
  25. 2021On Perceptual Lossy Compression: The Cost of Perceptual Reconstruction and An Optimal Training Frameworkcited by 27
  26. 2023Extreme Image Compression using Fine-tuned VQGANscited by 27
  27. 2024Idempotence and Perceptual Image Compressioncited by 27
  28. 2023Compression with Bayesian Implicit Neural Representationscited by 25
  29. 2021Towards Robust Neural Image Compression: Adversarial Attack and Model Finetuningcited by 24
  30. 2025Compressed Image Generation with Denoising Diffusion Codebook Modelscited by 24
  31. 2023Random-Access Neural Compression of Material Texturescited by 23
  32. 2025Lossy Compression with Pretrained Diffusion Modelscited by 23
  33. 2025One-Step Diffusion-Based Image Compression with Semantic Distillationcited by 23
  34. 2023A Unified Conditional Framework for Diffusion-based Image Restorationcited by 22
  35. 2024OFTSR: One-Step Flow for Image Super-Resolution with Tunable Fidelity-Realism Trade-offscited by 22
  36. 2025Generative Latent Coding for Ultra-Low Bitrate Image and Video Compressioncited by 22
  37. 2024RDEIC: Accelerating Diffusion-Based Extreme Image Compression with Relay Residual Diffusioncited by 21
  38. 2025Generative Latent Coding for Ultra-Low Bitrate Image Compressioncited by 21

50 most cited of 331 All 331 (JSON)