mlsanityData to 14 Oct 2026

Training-Free Continuous Bitrate Control for Scalable Image Coding for Humans and Machines

arXiv 2606.00158 ↗First posted 29 May 2026eess.IV cs.CVcited by 0

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Abstract (arXiv)

Continuous variable-rate compression is highly demanded in real-world applications, but remains underexplored in scalable image coding for humans and machines. In this paper, we propose a training-free variable-rate scalable image coding framework. By adaptively adjusting quantization step sizes based on predicted scale values, the proposed method enables independent and continuous bitrate control for the machine and enhancement layers while preserving important latent information in each layer. Experimental results demonstrate the effectiveness of the proposed method and highlight the importance of bitrate allocation between the two layers.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 6 of its 6 references that are in the map. First posted on arXiv 29 May 2026.

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References · 6

  1. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  2. 2020Channel-wise Autoregressive Entropy Models for Learned Image Compressioncited by 264
  3. 2023Learned Image Compression with Mixed Transformer-CNN Architecturescited by 211
  4. 2024Image Coding for Machines with Edge Information Learning Using Segment Anythingcited by 17
  5. 2025Explicit Residual-Based Scalable Image Coding for Humans and Machinescited by 3
  6. 2025Training-Free Adaptive Quantization for Variable Rate Image Coding for Machinescited by 1

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  1. 2021Learned Image Coding for Machines: A Content-Adaptive Approach
  2. 2022Flexible Neural Image Compression via Code Editing
  3. 2023QVRF: A Quantization-error-aware Variable Rate Framework for Learned Image Compression
  4. 2026Entropy-Coded MS-VQ-VAE with Learned Priors for Ultra-Low Bitrate Video Compression
  5. 2025Single-step Diffusion for Image Compression at Ultra-Low Bitrates
  6. 2024Rate-Distortion-Cognition Controllable Versatile Neural Image Compression
  7. 2021Progressive Neural Image Compression with Nested Quantization and Latent Ordering
  8. 2024Variable-Rate Learned Image Compression with Multi-Objective Optimization and Quantization-Reconstruction Offsets