mlsanityData to 14 Oct 2026

Content-oriented learned image compression

arXiv 2207.14168 ↗First posted 28 Jul 2022cs.CV cs.MM eess.IVcited by 12

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Abstract (arXiv)

In recent years, with the development of deep neural networks, end-to-end optimized image compression has made significant progress and exceeded the classic methods in terms of rate-distortion performance. However, most learning-based image compression methods are unlabeled and do not consider image semantics or content when optimizing the model. In fact, human eyes have different sensitivities to different content, so the image content also needs to be considered. In this paper, we propose a content-oriented image compression method, which handles different kinds of image contents with different strategies. Extensive experiments show that the proposed method achieves competitive subjective results compared with state-of-the-art end-to-end learned image compression methods or classic methods.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 22 of its 30 references that are in the map. First posted on arXiv 28 Jul 2022.

Builds on

22 of 30 references.

References · 22

  1. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  2. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
  3. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
  4. 2015Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classificationcited by 3,611
  5. 2018ESRGAN: Enhanced Super-Resolution Generative Adversarial Networkscited by 1,254
  6. 2018Variational image compression with a scale hyperpriorcited by 935
  7. 2016End-to-end Optimized Image Compressioncited by 696
  8. 2018Joint Autoregressive and Hierarchical Priors for Learned Image Compressioncited by 664
  9. 2020High-Fidelity Generative Image Compressioncited by 338
  10. 2018The relativistic discriminator: a key element missing from standard GANcited by 238
  11. 2019Residual Non-local Attention Networks for Image Restorationcited by 236
  12. 2018Generative Adversarial Networks for Extreme Learned Image Compressioncited by 219
10 more
  1. 2019Rethinking Lossy Compression: The Rate-Distortion-Perception Tradeoffcited by 211
  2. 2016Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networkscited by 192
  3. 2018Context-adaptive Entropy Model for End-to-end Optimized Image Compressioncited by 143
  4. 2017Real-Time Adaptive Image Compressioncited by 130
  5. 2020Structure-Preserving Super Resolution with Gradient Guidancecited by 116
  6. 2020Asymmetric Gained Deep Image Compression With Continuous Rate Adaptationcited by 85
  7. 2017Learning Convolutional Networks for Content-weighted Image Compressioncited by 76
  8. 2021Attention-guided Image Compression by Deep Reconstruction of Compressive Sensed Saliency Skeletoncited by 16
  9. 2020CompressNet: Generative Compression at Extremely Low Bitratescited by 10
  10. 2017Pixel Deconvolutional Networkscited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 1; 2023: 5; 2024: 3; 2025: 1; 2026: 2.

12 papers.

  1. 2022Multi-Realism Image Compression with a Conditional Generatorcited by 80
  2. 2023LVQAC: Lattice Vector Quantization Coupled with Spatially Adaptive Companding for Efficient Learned Image Compressioncited by 19
  3. 2023EGIC: Enhanced Low-Bit-Rate Generative Image Compression Guided by Semantic Segmentationcited by 14
  4. 2023High Visual-Fidelity Learned Video Compressioncited by 8
  5. 2024Learning Optimal Lattice Vector Quantizers for End-to-end Neural Image Compressioncited by 8
  6. 2024COSMIC: Compress Satellite Images Efficiently via Diffusion Compensationcited by 3
  7. 2026CADC: Content Adaptive Diffusion-Based Generative Image Compressioncited by 2
  8. 2023MM-NeRF: Multimodal-Guided 3D Multi-Style Transfer of Neural Radiance Fieldcited by 1
  9. 2023HFLIC: Human Friendly Perceptual Learned Image Compression with Reinforced Transformcited by 0
  10. 2024FLLIC: Functionally Lossless Image Compressioncited by 0
  11. 2025HyperVQ: Enabling Hyperprior Entropy Modeling for VQ-Based Generative Image Compressioncited by 0
  12. 2026Clear-Weighted Bit Allocation for Satellite Downlinkscited by 0