mlsanityData to 7 Oct 2026

End-to-end Optimized Image Compression

arXiv 1611.01704 ↗First posted 5 Nov 2016cs.CV cs.IT math.ITcited by 673

Not on the map. Why?

Cited by 43 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

We describe an image compression method, consisting of a nonlinear analysis transformation, a uniform quantizer, and a nonlinear synthesis transformation. The transforms are constructed in three successive stages of convolutional linear filters and nonlinear activation functions. Unlike most convolutional neural networks, the joint nonlinearity is chosen to implement a form of local gain control, inspired by those used to model biological neurons. Using a variant of stochastic gradient descent, we jointly optimize the entire model for rate-distortion performance over a database of training images, introducing a continuous proxy for the discontinuous loss function arising from the quantizer. Under certain conditions, the relaxed loss function may be interpreted as the log likelihood of a generative model, as implemented by a variational autoencoder. Unlike these models, however, the compression model must operate at any given point along the rate-distortion curve, as specified by a trade-off parameter. Across an independent set of test images, we find that the optimized method generally exhibits better rate-distortion performance than the standard JPEG and JPEG 2000 compression methods. More importantly, we observe a dramatic improvement in visual quality for all images at all bit rates, which is supported by objective quality estimates using MS-SSIM.

Key facts. Cited by 673 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Nov 2016.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2020: 1; 2021: 86; 2022: 116; 2023: 114; 2024: 149; 2025: 119; 2026: 88.

673 papers.

Sort:

By area:

  1. 2021Barlow Twins: Self-Supervised Learning via Redundancy Reductioncited by 1,818
  2. 2022High Fidelity Neural Audio Compressioncited by 673
  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. 2021Deep Contextual Video Compressioncited by 216
  6. 2023Learned Image Compression with Mixed Transformer-CNN Architecturescited by 205
  7. 2021Checkerboard Context Model for Efficient Learned Image Compressioncited by 193
  8. 2022From data to functa: Your data point is a function and you can treat it like onecited by 183
  9. 2022Beyond Transmitting Bits: Context, Semantics, and Task-Oriented Communicationscited by 166
  10. 2021Implicit Neural Representations for Image Compressioncited by 161
  11. 2021FVC: A New Framework towards Deep Video Compression in Feature Spacecited by 149
  12. 2022The Devil Is in the Details: Window-based Attention for Image Compressioncited by 141
38 more
  1. 2022Hybrid Spatial-Temporal Entropy Modelling for Neural Video Compressioncited by 123
  2. 2021Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challengescited by 114
  3. 2021Enhanced Invertible Encoding for Learned Image Compressioncited by 102
  4. 2022Entroformer: A Transformer-based Entropy Model for Learned Image Compressioncited by 102
  5. 2023Towards image compression with perfect realism at ultra-low bitratescited by 99
  6. 2024GaussianImage: 1000 FPS Image Representation and Compression by 2D Gaussian Splattingcited by 97
  7. 2021Semantic Communications: Principles and Challengescited by 90
  8. 2023Improving Statistical Fidelity for Neural Image Compression with Implicit Local Likelihood Modelscited by 90
  9. 2022Lossy Compression with Gaussian Diffusioncited by 87
  10. 2021Graph Barlow Twins: A self-supervised representation learning framework for graphscited by 85
  11. 2022COIN++: Neural Compression Across Modalitiescited by 81
  12. 2022MLIC: Multi-Reference Entropy Model for Learned Image Compressioncited by 80
  13. 2024CompGS: Efficient 3D Scene Representation via Compressed Gaussian Splattingcited by 80
  14. 2022An Introduction to Neural Data Compressioncited by 78
  15. 2025Improving the Diffusability of Autoencoderscited by 74
  16. 2021Nonlinear Transform Source-Channel Coding for Semantic Communicationscited by 73
  17. 2024End-to-End Rate-Distortion Optimized 3D Gaussian Representationcited by 71
  18. 2023Text + Sketch: Image Compression at Ultra Low Ratescited by 63
  19. 2021VoxelContext-Net: An Octree based Framework for Point Cloud Compressioncited by 60
  20. 2021Transformer-based Image Compressioncited by 60
  21. 2022Rethinking Reconstruction Autoencoder-Based Out-of-Distribution Detectioncited by 59
  22. 2021Variable-Rate Deep Image Compression through Spatially-Adaptive Feature Transformcited by 56
  23. 2023MLIC++: Linear Complexity Multi-Reference Entropy Modeling for Learned Image Compressioncited by 56
  24. 2024Towards Extreme Image Compression with Latent Feature Guidance and Diffusion Priorcited by 56
  25. 2022Coarse-to-fine Deep Video Coding with Hyperprior-guided Mode Predictioncited by 55
  26. 2023C3: High-performance and low-complexity neural compression from a single image or videocited by 54
  27. 2024LidarDM: Generative LiDAR Simulation in a Generated Worldcited by 53
  28. 2021Joint Global and Local Hierarchical Priors for Learned Image Compressioncited by 52
  29. 2021Lossy Compression for Lossless Predictioncited by 51
  30. 2021Optimal Representations for Covariate Shiftcited by 51
  31. 2022NIRVANA: Neural Implicit Representations of Videos with Adaptive Networks and Autoregressive Patch-wise Modelingcited by 50
  32. 2022Wireless Deep Video Semantic Transmissioncited by 49
  33. 2023EVC: Towards Real-Time Neural Image Compression with Mask Decaycited by 46
  34. 2021Differentiable Model Compression via Pseudo Quantization Noisecited by 44
  35. 2022CANF-VC: Conditional Augmented Normalizing Flows for Video Compressioncited by 44
  36. 2022Unified Multivariate Gaussian Mixture for Efficient Neural Image Compressioncited by 43
  37. 2022Contextformer: A Transformer with Spatio-Channel Attention for Context Modeling in Learned Image Compressioncited by 42
  38. 2023Disentanglement via Latent Quantizationcited by 40

50 most cited of 673 All 673 (JSON)