mlsanityData to 7 Oct 2026

Variational image compression with a scale hyperprior

arXiv 1802.01436 ↗First posted 1 Feb 2018eess.IV cs.IT math.ITcited by 910

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Cited by 77 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

We describe an end-to-end trainable model for image compression based on variational autoencoders. The model incorporates a hyperprior to effectively capture spatial dependencies in the latent representation. This hyperprior relates to side information, a concept universal to virtually all modern image codecs, but largely unexplored in image compression using artificial neural networks (ANNs). Unlike existing autoencoder compression methods, our model trains a complex prior jointly with the underlying autoencoder. We demonstrate that this model leads to state-of-the-art image compression when measuring visual quality using the popular MS-SSIM index, and yields rate-distortion performance surpassing published ANN-based methods when evaluated using a more traditional metric based on squared error (PSNR). Furthermore, we provide a qualitative comparison of models trained for different distortion metrics.

Key facts. Cited by 910 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Feb 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 94; 2022: 125; 2023: 146; 2024: 207; 2025: 193; 2026: 145.

910 papers.

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  1. 2022ELIC: Efficient Learned Image Compression with Unevenly Grouped Space-Channel Contextual Adaptive Codingcited by 296
  2. 2023The Stable Signature: Rooting Watermarks in Latent Diffusion Modelscited by 289
  3. 2021COIN: COmpression with Implicit Neural representationscited by 232
  4. 2021Deep Contextual Video Compressioncited by 216
  5. 2023Learned Image Compression with Mixed Transformer-CNN Architecturescited by 205
  6. 2024HAC: Hash-grid Assisted Context for 3D Gaussian Splatting Compressioncited by 202
  7. 2021Checkerboard Context Model for Efficient Learned Image Compressioncited by 193
  8. 2023EAGLES: Efficient Accelerated 3D Gaussians with Lightweight EncodingScited by 191
  9. 2022Lossy Image Compression with Conditional Diffusion Modelscited by 165
  10. 2021Implicit Neural Representations for Image Compressioncited by 161
  11. 2023Neural Video Compression with Diverse Contextscited by 155
  12. 2021FVC: A New Framework towards Deep Video Compression in Feature Spacecited by 149
38 more
  1. 2022The Devil Is in the Details: Window-based Attention for Image Compressioncited by 141
  2. 2023Invisible Image Watermarks Are Provably Removable Using Generative AIcited by 124
  3. 2022Hybrid Spatial-Temporal Entropy Modelling for Neural Video Compressioncited by 123
  4. 2024Neural Video Compression with Feature Modulationcited by 115
  5. 2021Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challengescited by 114
  6. 2021Temporal Context Mining for Learned Video Compressioncited by 112
  7. 2022Entroformer: A Transformer-based Entropy Model for Learned Image Compressioncited by 102
  8. 2023Towards image compression with perfect realism at ultra-low bitratescited by 99
  9. 2024ContextGS: Compact 3D Gaussian Splatting with Anchor Level Context Modelcited by 98
  10. 2024GaussianImage: 1000 FPS Image Representation and Compression by 2D Gaussian Splattingcited by 97
  11. 2023Improving Statistical Fidelity for Neural Image Compression with Implicit Local Likelihood Modelscited by 90
  12. 2024WAVES: Benchmarking the Robustness of Image Watermarkscited by 89
  13. 2023Collaborative Perception in Autonomous Driving: Methods, Datasets and Challengescited by 87
  14. 2022COIN++: Neural Compression Across Modalitiescited by 81
  15. 2024CompGS: Efficient 3D Scene Representation via Compressed Gaussian Splattingcited by 80
  16. 2022Multi-Realism Image Compression with a Conditional Generatorcited by 79
  17. 2022An Introduction to Neural Data Compressioncited by 78
  18. 2022VCT: A Video Compression Transformercited by 74
  19. 2024An Undetectable Watermark for Generative Image Modelscited by 74
  20. 2025Improving the Diffusability of Autoencoderscited by 74
  21. 2021Nonlinear Transform Source-Channel Coding for Semantic Communicationscited by 73
  22. 2023HiNeRV: Video Compression with Hierarchical Encoding-based Neural Representationcited by 70
  23. 2021Sparse Tensor-based Multiscale Representation for Point Cloud Geometry Compressioncited by 69
  24. 2021ELF-VC: Efficient Learned Flexible-Rate Video Codingcited by 68
  25. 2021VoxelContext-Net: An Octree based Framework for Point Cloud Compressioncited by 60
  26. 2021Transformer-based Image Compressioncited by 60
  27. 2021Variable-Rate Deep Image Compression through Spatially-Adaptive Feature Transformcited by 56
  28. 2023MLIC++: Linear Complexity Multi-Reference Entropy Modeling for Learned Image Compressioncited by 56
  29. 2023Frequency-Aware Transformer for Learned Image Compressioncited by 56
  30. 2024Towards Extreme Image Compression with Latent Feature Guidance and Diffusion Priorcited by 56
  31. 2022Coarse-to-fine Deep Video Coding with Hyperprior-guided Mode Predictioncited by 55
  32. 2023C3: High-performance and low-complexity neural compression from a single image or videocited by 54
  33. 2021Joint Global and Local Hierarchical Priors for Learned Image Compressioncited by 52
  34. 2025HAC++: Towards 100X Compression of 3D Gaussian Splattingcited by 52
  35. 2021Lossy Compression for Lossless Predictioncited by 51
  36. 2021Optimal Representations for Covariate Shiftcited by 51
  37. 2023WOUAF: Weight Modulation for User Attribution and Fingerprinting in Text-to-Image Diffusion Modelscited by 51
  38. 2022NIRVANA: Neural Implicit Representations of Videos with Adaptive Networks and Autoregressive Patch-wise Modelingcited by 50

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