mlsanityData to 7 Oct 2026

ELIC: Efficient Learned Image Compression with Unevenly Grouped Space-Channel Contextual Adaptive Coding

arXiv 2203.10886 ↗First posted 21 Mar 2022cs.CV eess.IVcited by 296

Not on the map. Why?

Cited by 30 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Recently, learned image compression techniques have achieved remarkable performance, even surpassing the best manually designed lossy image coders. They are promising to be large-scale adopted. For the sake of practicality, a thorough investigation of the architecture design of learned image compression, regarding both compression performance and running speed, is essential. In this paper, we first propose uneven channel-conditional adaptive coding, motivated by the observation of energy compaction in learned image compression. Combining the proposed uneven grouping model with existing context models, we obtain a spatial-channel contextual adaptive model to improve the coding performance without damage to running speed. Then we study the structure of the main transform and propose an efficient model, ELIC, to achieve state-of-the-art speed and compression ability. With superior performance, the proposed model also supports extremely fast preview decoding and progressive decoding, which makes the coming application of learning-based image compression more promising.

Key facts. Cited by 296 papers in the map (data through 7 Oct 2026). Builds on 31 of its 53 references that are in the map. First posted on arXiv 21 Mar 2022.

Builds on

31 of 53 references.

References · 31

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2018DARTS: Differentiable Architecture Searchcited by 1,782
  3. 2018Variational image compression with a scale hyperpriorcited by 910
  4. 2016Conditional Image Generation with PixelCNN Decoderscited by 859
  5. 2016End-to-end Optimized Image Compressioncited by 673
  6. 2018Joint Autoregressive and Hierarchical Priors for Learned Image Compressioncited by 642
  7. 2020Learned Image Compression with Discretized Gaussian Mixture Likelihoods and Attention Modulescited by 570
  8. 2020High-Fidelity Generative Image Compressioncited by 331
  9. 2020CompressAI: a PyTorch library and evaluation platform for end-to-end compression researchcited by 271
  10. 2020Channel-wise Autoregressive Entropy Models for Learned Image Compressioncited by 255
  11. 2019Rethinking Lossy Compression: The Rate-Distortion-Perception Tradeoffcited by 207
  12. 2021Checkerboard Context Model for Efficient Learned Image Compressioncited by 193
19 more
  1. 2020BigNAS: Scaling Up Neural Architecture Search with Big Single-Stage Modelscited by 187
  2. 2020Nonlinear Transform Codingcited by 132
  3. 2021Enhanced Invertible Encoding for Learned Image Compressioncited by 102
  4. 2019Non-local Attention Optimized Deep Image Compressioncited by 86
  5. 2020Improving Inference for Neural Image Compressioncited by 81
  6. 2020Causal Contextual Prediction for Learned Image Compressioncited by 70
  7. 2020A Unified End-to-End Framework for Efficient Deep Image Compressioncited by 56
  8. 2021Soft then Hard: Rethinking the Quantization in Neural Image Compressioncited by 50
  9. 2018Deep Convolutional AutoEncoder-based Lossy Image Compressioncited by 42
  10. 2021Slimmable Compressive Autoencoders for Practical Neural Image Compressioncited by 38
  11. 2019Efficient and Effective Context-Based Convolutional Entropy Modeling for Image Compressioncited by 33
  12. 2020Learned Block-based Hybrid Image Compressioncited by 30
  13. 2019AM-LFS: AutoML for Loss Function Searchcited by 29
  14. 2018Efficient Nonlinear Transforms for Lossy Image Compressioncited by 20
  15. 2019Deep Residual Learning for Image Compressioncited by 13
  16. 2019An End-to-End Joint Learning Scheme of Image Compression and Quality Enhancement with Improved Entropy Minimizationcited by 11
  17. 2021A Cross Channel Context Model for Latents in Deep Image Compressioncited by 10
  18. 2021Transform Network Architectures for Deep Learning based End-to-End Image/Video Coding in Subsampled Color Spacescited by 6
  19. 2021HLIC: Harmonizing Optimization Metrics in Learned Image Compression by Reinforcement Learningcited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 10; 2023: 44; 2024: 95; 2025: 82; 2026: 65.

296 papers.

Sort:

By area:

  1. 2023Learned Image Compression with Mixed Transformer-CNN Architecturescited by 205
  2. 2024HAC: Hash-grid Assisted Context for 3D Gaussian Splatting Compressioncited by 202
  3. 2022Lossy Image Compression with Conditional Diffusion Modelscited by 165
  4. 2024Image and Video Tokenization with Binary Spherical Quantizationcited by 110
  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. 2023Improving Statistical Fidelity for Neural Image Compression with Implicit Local Likelihood Modelscited by 90
  8. 2022MLIC: Multi-Reference Entropy Model for Learned Image Compressioncited by 80
  9. 2022Multi-Realism Image Compression with a Conditional Generatorcited by 79
  10. 2022VCT: A Video Compression Transformercited by 74
  11. 2023MLIC++: Linear Complexity Multi-Reference Entropy Modeling for Learned Image Compressioncited by 56
  12. 2023Frequency-Aware Transformer for Learned Image Compressioncited by 56
38 more
  1. 2024Towards Extreme Image Compression with Latent Feature Guidance and Diffusion Priorcited by 56
  2. 2023C3: High-performance and low-complexity neural compression from a single image or videocited by 54
  3. 2023High-Fidelity Image Compression with Score-based Generative Modelscited by 53
  4. 2023EVC: Towards Real-Time Neural Image Compression with Mask Decaycited by 46
  5. 2024USTC-TD: A Test Dataset and Benchmark for Image and Video Coding in 2020scited by 37
  6. 2024Lossy Image Compression with Foundation Diffusion Modelscited by 34
  7. 2024How Far Can We Compress Instant-NGP-Based NeRF?cited by 30
  8. 2024NVRC: Neural Video Representation Compressioncited by 29
  9. 2025Learned Image Compression with Dictionary-based Entropy Modelcited by 29
  10. 2025StableCodec: Taming One-Step Diffusion for Extreme Image Compressioncited by 29
  11. 2024MambaVC: Learned Visual Compression with Selective State Spacescited by 28
  12. 2024Idempotence and Perceptual Image Compressioncited by 27
  13. 2023Compression with Bayesian Implicit Neural Representationscited by 25
  14. 2023Computationally-Efficient Neural Image Compression with Shallow Decoderscited by 22
  15. 2024CRA5: Extreme Compression of ERA5 for Portable Global Climate and Weather Research via an Efficient Variational Transformercited by 22
  16. 2025Linear Attention Modeling for Learned Image Compressioncited by 22
  17. 2024Spatial Decomposition and Temporal Fusion based Inter Prediction for Learned Video Compressioncited by 21
  18. 2024RDEIC: Accelerating Diffusion-Based Extreme Image Compression with Relay Residual Diffusioncited by 21
  19. 2024Neural Image Compression with Text-guided Encoding for both Pixel-level and Perceptual Fidelitycited by 20
  20. 2024Lossless data compression by large modelscited by 20
  21. 2025Learned Image Compression with Hierarchical Progressive Context Modelingcited by 20
  22. 2022Flexible Neural Image Compression via Code Editingcited by 19
  23. 2023LVQAC: Lattice Vector Quantization Coupled with Spatially Adaptive Companding for Efficient Learned Image Compressioncited by 19
  24. 2024PNVC: Towards Practical INR-based Video Compressioncited by 19
  25. 2024Causal Context Adjustment Loss for Learned Image Compressioncited by 19
  26. 2025MambaIC: State Space Models for High-Performance Learned Image Compressioncited by 18
  27. 2025Task-Oriented Feature Compression for Multimodal Understanding via Device-Edge Co-Inferencecited by 18
  28. 2025Ultra Lowrate Image Compression with Semantic Residual Coding and Compression-aware Diffusioncited by 17
  29. 2022High-Efficiency Lossy Image Coding Through Adaptive Neighborhood Information Aggregationcited by 16
  30. 2024NeRFCodec: Neural Feature Compression Meets Neural Radiance Fields for Memory-Efficient Scene Representationcited by 16
  31. 2024Controlling Rate, Distortion, and Realism: Towards a Single Comprehensive Neural Image Compression Modelcited by 16
  32. 2024Video Quality Assessment: A Comprehensive Surveycited by 15
  33. 2025Large Language Model for Lossless Image Compression with Visual Promptscited by 15
  34. 2025Neural Video Compression with Context Modulationcited by 15
  35. 2023M2T: Masking Transformers Twice for Faster Decodingcited by 14
  36. 2023Frequency Disentangled Features in Neural Image Compressioncited by 14
  37. 2023LDMIC: Learning-based Distributed Multi-view Image Codingcited by 13
  38. 2023Efficient Contextformer: Spatio-Channel Window Attention for Fast Context Modeling in Learned Image Compressioncited by 13

50 most cited of 296 All 296 (JSON)