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English(EN) ResARC: Residual-Aware AutoRegressive Coding for Ultra-Low Bitrate Image Compression

新方法应对超低比特率生成式图像压缩

作者 PulseAugur 编辑部 · [2 个来源] ·

两篇新研究论文提出了在极低比特率下进行生成式图像压缩的新方法。第一篇论文介绍了RAE-CoD，一种面向压缩的扩散模型，它使压缩表示和源表示对齐，即使在非常低的比特率下也能保持可识别的内容，在特征MSE和Fréchet距离方面优于竞争对手。第二篇论文提出了ResARC，一种残差感知自回归编解码器，它在解码器中显式补偿量化和生成残差，实现了具有竞争力的感知相似性和改进的分布保真度。 AI

影响 这些进步可能导致更高效的图像存储和传输，尤其是在带宽受限的环境中。

排序理由 两篇在arXiv上发表的学术论文，提出了图像压缩的新方法。

在 arXiv cs.CV 阅读 →

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新方法应对超低比特率生成式图像压缩

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两篇在arXiv上发表的学术论文，提出了图像压缩的新方法。
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报道来源 [2]

  1. arXiv cs.CV TIER_1 English(EN) · Tianyu Zhang, Zhaoyang Jia, Houqiang Li, Dong Liu ·

    极低比特率下生成式图像压缩的再思考

    arXiv:2609.39315v1 Announce Type: new Abstract: Generative image compression produces visually plausible reconstructions at low bitrates, yet their behavior as the rate approaches zero remains largely unexplored. When pushed below normal operating rates, representative codecs und…

  2. arXiv cs.CV TIER_1 English(EN) · Qin Yan, Ruixiao Dong, Yutao Xie, Li Li, Ying Chen, Kai Li, Daowen Li, Houqiang Li ·

    ResARC：用于超低比特率图像压缩的残差感知自回归编码

    arXiv:2609.39451v1 Announce Type: new Abstract: Progressive autoregressive image codecs provide an appealing paradigm for generative compression by quantizing continuous latents into discrete tokens, transmitting coarse-to-fine prefix tokens and generating the remaining suffix to…

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