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arXiv · 2610.39778

SCOPE: Semantic COdec Pre-Editing for Object-Preserving Compression

Silvia Dani·Leonardo Galteri·Marco Bertini
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Abstract

Image compression is increasingly used before machine vision systems, yet standard codecs are mainly optimized for human perception rather than downstream task accuracy. We propose SCOPE (Semantic COdec Pre-Editing), a conditional image pre-editor that modifies images before compression to improve the bitrate and detection accuracy trade-off. The model is conditioned on the codec family and compression severity, allowing a single trained network to adapt to multiple compression settings without retraining or loading codec-specific weights. Instead of uniformly preserving the whole image, the pre-editor learns to protect task-relevant regions while simplifying less important background content to improve compressibility. The resulting rate-accuracy curves show consistent gains across different codec families and detector architectures, together with strong transferability to unseen learned and wavelet-based compression families.

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Silvia Dani, Leonardo Galteri, Marco Bertini. 2026-10-29. SCOPE: Semantic COdec Pre-Editing for Object-Preserving Compression. https://arxiv.org/abs/2610.39778

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