arXiv Computer Vision By Khoa Pham-Dinh, Sanaz Nami, Hamed Rezazadegan Tavakoli, Moncef Gabbouj, Farhad Pakdaman

You've Seen Enough: Quality-Constrained Image Coding for Machines

Read the original on arXiv Computer Vision →

The paper introduces Quality-Constrained Image Coding for Machines (ICM), which compresses images by treating a computer vision application as the primary observer while limiting human-observed quality to a specified target. By formulating joint compression and segmentation as a constrained optimization problem, the authors design penalty functions that steer the codec toward the desired visual quality, allowing remaining coding capacity to enhance machine performance. Experiments demonstrate significant bitrate savings—up to 22.82% over unconstrained joint optimization and 29.81% over a simple rate–distortion baseline—while maintaining target visual quality without added complexity.

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arXiv Computer Vision
Sep 7

Multi-scale Image Representation Compression

The paper introduces MIRC, an overfitted image codec that quantizes and entropy‑codes all components—including latents, synthesis network, and entropy models—within a single end‑to‑end rate‑distortion framework inspired by NVRC. It adds a multi‑scale representation with cross‑stage parameter sharing to capture cross‑scale redundancy, yielding a 10.5 % BD‑rate saving over VVC on the CLIC2020 professional set. MIRC offers multiple configurations ranging from 1.2 to 2.9 kMAC per pixel, allowing decoding complexity to be tuned to deployment needs.

By Tianhao Peng, Ho Man Kwan, Fan Zhang, Shan Liu, David Bull
Hugging Face Trending Papers
Sep 2

Multi-scale Image Representation Compression

The paper introduces MIRC, an overfitted image codec that quantizes all components—including latents, synthesis network, and entropy models—within a single rate‑distortion objective, following the neural video representation codec NVRC. It adds a multi‑scale representation with cross‑stage parameter sharing to capture cross‑scale redundancy, achieving a 10.5% BD‑rate saving over VVC on the CLIC2020 professional validation set. MIRC also offers configurable decoding complexity ranging from 1.2 to 2.9 kMAC per pixel, allowing deployment to match specific resource budgets.