Privacy-Preserving Semantic Segmentation from High-Resolution Depth and Ultra-Low-Resolution RGB
Paper recorded by Signals 4 on 2026-09-23 in cs.CV. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-23 on arXiv · recorded by Signals 4 on 2026-09-24
Category: cs.CV · 计算机视觉 · first seen 2026-09-24
Abstract
As mobile robots become increasingly integrated into everyday environments, privacy risks arising from onboard cameras have become a growing concern. Ultra-low-resolution (ULR) RGB can mitigate visual privacy exposure at the source, but ULR appearance alone substantially limits semantic and spatial understanding. We therefore introduce a privacy-preserving asymmetric sensing setting that combines
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Cite this page: Privacy-Preserving Semantic Segmentation from High-Resolution Depth and Ultra-Low-Resolution RGB: the #6 most recent of 301 cs.CV papers we have recorded (as of 2026-09-23). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/privacy-preserving-semantic-segmentation-from-high-resolution-depth-and-ultra-lo.html
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