no code implementations • CVPR 2023 • Yue Li, Jiayong Peng, Juntian Ye, Yueyi Zhang, Feihu Xu, Zhiwei Xiong
Specifically, after extracting the shallow features with the assistance of physics-based priors, we design two spatial-temporal self attention encoders to explore both local and global correlations within 3D NLOS data by splitting or downsampling the features into different scales, respectively.
1 code implementation • 1 Jan 2023 • Rui Ding, Juntian Ye, Qifeng Gao, Feihu Xu, Yuping Duan
Non-line-of-sight (NLOS) imaging aims to reconstruct the three-dimensional hidden scenes from the data measured in the line-of-sight, which uses photon time-of-flight information encoded in light after multiple diffuse reflections.
