March 28, 2024, 4:46 a.m. | Liyuan Zhu, Shengyu Huang, Konrad Schindler, Iro Armeni

cs.CV updates on arXiv.org arxiv.org

arXiv:2312.09138v2 Announce Type: replace
Abstract: Research into dynamic 3D scene understanding has primarily focused on short-term change tracking from dense observations, while little attention has been paid to long-term changes with sparse observations. We address this gap with MoRE, a novel approach for multi-object relocalization and reconstruction in evolving environments. We view these environments as "living scenes" and consider the problem of transforming scans taken at different points in time into a 3D reconstruction of the object instances, whose accuracy …

abstract arxiv attention change cs.cv dynamic environments gap long-term novel object research tracking type understanding

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