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[ARTICLE · art-13493] src=apple.github.io pub= topic=machine-learning verified=true sentiment=↑ positive

Perceptual Image Codec: What Matters in Practical Learned Image Compression

Researchers at Apple have developed PICO (Perceptual Image Codec), the first learned image compression model optimized for human visual perception and practical on-device deployment. The codec achieves 2.3-3× bitrate savings over traditional standards like AV1 and VVC, while encoding 12MP images in 230ms and decoding in 150ms on an iPhone 17 Pro Max. PICO also delivers 20-40% bitrate savings over competing learned codecs and includes cross-platform robustness guarantees.

read1 min publishedMay 24, 2026

About We introduce PICO (Perceptual Image Codec) — the first learned codec that is both practical, and optimized directly for the human visual system. To derive it, we perform a comprehensive study of modeling choices for practical learned codecs, and search over millions of model configurations to jointly optimize over perceptual quality and on-device runtime.

Based on large-scale subjective user studies, PICO provides 2.3-3× bitrate savings against AV1, AV2, VVC, ECM and JPEG-AI, and 20-40% bitrate savings against the best learned codec alternatives. At the same time, on an iPhone 17 Pro Max, it encodes 12MP images as fast as 230ms, and decodes them in 150ms — faster than most top ML-based codecs run on a V100 GPU. Different from most learned codecs, PICO furthermore comes with cross-platform robustness guarantees.

Comparisons of state-of-the-art traditional and learned codecs across different considerations of practicality.

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