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GS-Pool: Object-Level Change Detection in 3D Gaussian Splatting

Paper recorded by Signals 4 on 2026-10-05 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-05 on arXiv · recorded by Signals 4 on 2026-10-06

Category: cs.CV · 计算机视觉 · first seen 2026-10-06

Abstract

Factories, museums and surveyors photograph the same space months apart and need to know which objects changed. When each visit is reconstructed with 3D Gaussian Splatting (3DGS), a direct comparison of the two reconstructions does not answer this. Training is stochastic, so two reconstructions of an unchanged space never coincide, and the second visit is often a quick re-scan with far fewer photo

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#356 most recent of 756 cs.CV papers we have recorded · ↑ newer: Extending Dynamic World Surface Water Mapping to Sentinel-1 with Alpha · ↓ older: ChronoWorld: Camera-Controlled Consistent 4D World Generation via Spat
Cite this page: GS-Pool: Object-Level Change Detection in 3D Gaussian Splatting: the #356 most recent of 756 cs.CV papers we have recorded (as of 2026-10-05). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/gs-pool-object-level-change-detection-in-3d-gaussian-splatting.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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