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CompMVR: Compression-Aware Multi-View Restoration Using Diffusion Models for Geometrically Consistent 3D Reconstruction

Paper recorded by Signals 4 on 2026-10-23 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-23 on arXiv · recorded by Signals 4 on 2026-10-26

Category: cs.CV · 计算机视觉 · first seen 2026-10-26

Abstract

Real-world 3D reconstruction pipelines often rely on multi-view images degraded by lossy compression. While compression artifacts have been extensively studied in single-image or video restoration, their impact on multi-view geometry remains largely overlooked. In this work, we identify compression-induced cross-view geometric inconsistency as a critical failure mode, where view-dependent artifact

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#167 most recent of 756 cs.CV papers we have recorded · ↑ newer: Sounding Surgical Instrument Localisation through Audio-Visual Corresp · ↓ older: Consommé: Conditioned Token Merging for Split Inference
Cite this page: CompMVR: Compression-Aware Multi-View Restoration Using Diffusion Models for Geometrically Consistent 3D Reconstruction: the #167 most recent of 756 cs.CV papers we have recorded (as of 2026-10-23). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/compmvr-compression-aware-multi-view-restoration-using-diffusion-models-for-geom.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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