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

ArXiv CS.CV2026-06-02NEWSen作者: Yui Tatsumi, Hiroshi Watanabe

摘要

arXiv:2606.00158v1 Announce Type: cross Abstract: 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 adjusting quantization steps based on predicted scale values, the proposed method achieves continuous bitrate control while preserving high-scale information in the machine and enhancement layers. Experimental results demonstrate the effectiveness of the proposed method and highlight the importance of bitrate allocation between the two layers.

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