March 27, 2024, 4:47 a.m. | Jiarui Zhang, Ruixu Geng, Xiaolong Du, Yan Chen, Houqiang Li, Yang Hu

cs.CV updates on arXiv.org arxiv.org

arXiv:2312.16014v2 Announce Type: replace
Abstract: Passive non-line-of-sight (NLOS) imaging has witnessed rapid development in recent years, due to its ability to image objects that are out of sight. The light transport condition plays an important role in this task since changing the conditions will lead to different imaging models. Existing learning-based NLOS methods usually train independent models for different light transport conditions, which is computationally inefficient and impairs the practicality of the models. In this work, we propose NLOS-LTM, a …

arxiv cs.cv eess.iv imaging light line transport type

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