Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression 文章

ArXiv CS.CV2026-06-02NEWSen作者: Hao Wei, Yanhui Zhou, Chenyang Ge, Saeed Anwar, Ajmal Mian

摘要

arXiv:2606.01608v1 Announce Type: new Abstract: Most existing extreme compression methods fail to achieve an optimal rate-distortion-perception trade-off, as they typically prioritize perceptual fidelity and visual realism over pixel-level accuracy. Consequently, the resulting reconstructions often deviate noticeably from the originals. Ultra-low bitrate image compression is therefore crucial-not only for producing extremely compact representations but also for ensuring that reconstructed images remain semantically coherent and faithful to the source at the pixel level. To this end, we propose SPRDiff, a diffusion-based compression method that fully leverages both semantic and pixel representations, thereby enhancing reconstruction fidelity under ultra-low bitrate constraints.

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