mlsanityData to 7 Oct 2026

Learned Image Compression with Discretized Gaussian Mixture Likelihoods and Attention Modules

arXiv 2001.01568 ↗First posted 6 Jan 2020eess.IVcited by 570

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Cited by 52 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Image compression is a fundamental research field and many well-known compression standards have been developed for many decades. Recently, learned compression methods exhibit a fast development trend with promising results. However, there is still a performance gap between learned compression algorithms and reigning compression standards, especially in terms of widely used PSNR metric. In this paper, we explore the remaining redundancy of recent learned compression algorithms. We have found accurate entropy models for rate estimation largely affect the optimization of network parameters and thus affect the rate-distortion performance. Therefore, in this paper, we propose to use discretized Gaussian Mixture Likelihoods to parameterize the distributions of latent codes, which can achieve a more accurate and flexible entropy model. Besides, we take advantage of recent attention modules and incorporate them into network architecture to enhance the performance. Experimental results demonstrate our proposed method achieves a state-of-the-art performance compared to existing learned compression methods on both Kodak and high-resolution datasets. To our knowledge our approach is the first work to achieve comparable performance with latest compression standard Versatile Video Coding (VVC) regarding PSNR. More importantly, our approach generates more visually pleasant results when optimized by MS-SSIM. This project page is at this https URL https://github.com/ZhengxueCheng/Learned-Image-Compression-with-GMM-and-Attention

Key facts. Cited by 570 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Jan 2020.

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Citing papers per year: 2021: 43; 2022: 79; 2023: 98; 2024: 144; 2025: 122; 2026: 84.

570 papers.

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  1. 2023Finite Scalar Quantization: VQ-VAE Made Simplecited by 425
  2. 2022ELIC: Efficient Learned Image Compression with Unevenly Grouped Space-Channel Contextual Adaptive Codingcited by 296
  3. 2023The Stable Signature: Rooting Watermarks in Latent Diffusion Modelscited by 289
  4. 2021COIN: COmpression with Implicit Neural representationscited by 232
  5. 2021Deep Contextual Video Compressioncited by 216
  6. 2023Learned Image Compression with Mixed Transformer-CNN Architecturescited by 205
  7. 2024HAC: Hash-grid Assisted Context for 3D Gaussian Splatting Compressioncited by 202
  8. 2021Checkerboard Context Model for Efficient Learned Image Compressioncited by 193
  9. 2022Lossy Image Compression with Conditional Diffusion Modelscited by 165
  10. 2021Implicit Neural Representations for Image Compressioncited by 161
  11. 2022The Devil Is in the Details: Window-based Attention for Image Compressioncited by 141
  12. 2023Invisible Image Watermarks Are Provably Removable Using Generative AIcited by 124
38 more
  1. 2022Hybrid Spatial-Temporal Entropy Modelling for Neural Video Compressioncited by 123
  2. 2021Temporal Context Mining for Learned Video Compressioncited by 112
  3. 2022Entroformer: A Transformer-based Entropy Model for Learned Image Compressioncited by 102
  4. 2023Towards image compression with perfect realism at ultra-low bitratescited by 99
  5. 2024GaussianImage: 1000 FPS Image Representation and Compression by 2D Gaussian Splattingcited by 97
  6. 2023Improving Statistical Fidelity for Neural Image Compression with Implicit Local Likelihood Modelscited by 90
  7. 2022COIN++: Neural Compression Across Modalitiescited by 81
  8. 2022MLIC: Multi-Reference Entropy Model for Learned Image Compressioncited by 80
  9. 2023GIVT: Generative Infinite-Vocabulary Transformerscited by 80
  10. 2022Multi-Realism Image Compression with a Conditional Generatorcited by 79
  11. 2022An Introduction to Neural Data Compressioncited by 78
  12. 2024An Undetectable Watermark for Generative Image Modelscited by 74
  13. 2025Improving the Diffusability of Autoencoderscited by 74
  14. 2023Text + Sketch: Image Compression at Ultra Low Ratescited by 63
  15. 2021Transformer-based Image Compressioncited by 60
  16. 2023MLIC++: Linear Complexity Multi-Reference Entropy Modeling for Learned Image Compressioncited by 56
  17. 2023Frequency-Aware Transformer for Learned Image Compressioncited by 56
  18. 2022Coarse-to-fine Deep Video Coding with Hyperprior-guided Mode Predictioncited by 55
  19. 2023C3: High-performance and low-complexity neural compression from a single image or videocited by 54
  20. 2021Joint Global and Local Hierarchical Priors for Learned Image Compressioncited by 52
  21. 2025HAC++: Towards 100X Compression of 3D Gaussian Splattingcited by 52
  22. 2023WOUAF: Weight Modulation for User Attribution and Fingerprinting in Text-to-Image Diffusion Modelscited by 51
  23. 2023EVC: Towards Real-Time Neural Image Compression with Mask Decaycited by 46
  24. 2021DeepWiVe: Deep-Learning-Aided Wireless Video Transmissioncited by 45
  25. 2022CANF-VC: Conditional Augmented Normalizing Flows for Video Compressioncited by 44
  26. 2022Contextformer: A Transformer with Spatio-Channel Attention for Context Modeling in Learned Image Compressioncited by 42
  27. 2023Backdoor Attacks Against Deep Image Compression via Adaptive Frequency Triggercited by 40
  28. 2023Towards Scalable Neural Representation for Diverse Videoscited by 37
  29. 2024USTC-TD: A Test Dataset and Benchmark for Image and Video Coding in 2020scited by 37
  30. 2022DeepJSCC-Q: Constellation Constrained Deep Joint Source-Channel Codingcited by 36
  31. 2022Towards Semantic Communications: Deep Learning-Based Image Semantic Codingcited by 35
  32. 2024OmniGuard: Hybrid Manipulation Localization via Augmented Versatile Deep Image Watermarkingcited by 35
  33. 2024Image-GS: Content-Adaptive Image Representation via 2D Gaussianscited by 34
  34. 2021Learned Image Compression with Gaussian-Laplacian-Logistic Mixture Model and Concatenated Residual Modulescited by 33
  35. 2024Attack-Resilient Image Watermarking Using Stable Diffusioncited by 33
  36. 2022Lossy Image Compression with Quantized Hierarchical VAEscited by 32
  37. 2022Image Compression with Product Quantized Masked Image Modelingcited by 32
  38. 2025Token Communications: A Large Model-Driven Framework for Cross-modal Context-aware Semantic Communicationscited by 32

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