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New PICA framework enhances image compression with adaptive multi-agent system

研究人员开发了一种新颖的多智能体框架 PICA,旨在通过将现有编解码器适应不同场景和降级输入来增强图像压缩。该系统利用四个协作智能体——感知(Perception)、改进(Improvement)、编码(Coding)和后编码(After-coding)——来解读用户意图,优化预编码恢复,精炼质量设置,并处理残余伪影。PICA 的智能体 ROI 编码 (AROIC) 允许编解码器无关的区域适应,从而无需重新训练即可自动调度和评估编码计划。实验表明,PICA 在各种数据集和图像条件下,显著提高了传统和神经网络编解码器的压缩性能。 AI

影响 该框架可能带来更高效、更具适应性的图像压缩解决方案,影响依赖于高效图像数据处理的领域。

排序理由 这是一篇详细介绍图像压缩新技术框架的研究论文。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.CV 阅读 →

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New PICA framework enhances image compression with adaptive multi-agent system

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这是一篇详细介绍图像压缩新技术框架的研究论文。[lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Zhenghao Chen, Lebin Zhou, Zicong Chen, Naifu Xue, Jiahao Li, Bin Li, Dong Xu, Yan Lu ·

    面向质量感知和场景自适应的图像压缩的智能体框架

    arXiv:2611.04960v2 Announce Type: replace Abstract: Despite decades of progress, image codecs remain difficult to adapt to diverse real-world compression scenarios for two main reasons. First, most image codecs are optimized for a specific objective and require substantial redeve…