no code implementations • CVPR 2023 • Wending Zhou, Xu Yan, Yinghong Liao, Yuankai Lin, Jin Huang, Gangming Zhao, Shuguang Cui, Zhen Li
In practice, the proposed BEV@DC model comprehensively takes advantage of LiDARs with rich geometric details in training, employing an enhanced depth completion manner in inference, which takes only images (RGB and depth) as input.
no code implementations • 2 Dec 2022 • Yinghong Liao, Wending Zhou, Xu Yan, Shuguang Cui, Yizhou Yu, Zhen Li
Moreover, to improve the 2D classifier in the target domain, we perform domain-invariant geometric adaptation from source to target and unify the 2D semantic and 3D geometric segmentation results in two domains.
1 code implementation • 20 Feb 2022 • Yuankai Lin, Tao Cheng, Qi Zhong, Wending Zhou, Hua Yang
Our solution is to estimate independent affinity matrices in each SPN iteration, but it is over-parameterized and heavy calculation.