no code implementations • 8 Apr 2024 • Haimei Zhao, Jing Zhang, Zhuo Chen, Shanshan Zhao, DaCheng Tao
We devote UniMix to two main setups: 1) unsupervised domain adaption, adapting the model from the clear weather source domain to the adverse weather target domain; 2) domain generalization, learning a model that generalizes well to unseen scenes in adverse weather.
2 code implementations • 29 Mar 2023 • Haimei Zhao, Qiming Zhang, Shanshan Zhao, Zhe Chen, Jing Zhang, DaCheng Tao
Multi-view camera-based 3D object detection has become popular due to its low cost, but accurately inferring 3D geometry solely from camera data remains challenging and may lead to inferior performance.
1 code implementation • 19 Sep 2022 • Haimei Zhao, Jing Zhang, Zhuo Chen, Bo Yuan, DaCheng Tao
Compared with the photometric consistency loss as well as the rigid point cloud alignment loss, the proposed DFA and VDA losses are more robust owing to the strong representation power of deep features as well as the high tolerance of voxel density to the aforementioned challenges.
1 code implementation • 16 Jul 2022 • Haimei Zhao, Jing Zhang, Sen Zhang, DaCheng Tao
A naive way is to accomplish them independently in a sequential or parallel manner, but there are many drawbacks, i. e., 1) the depth and VO results suffer from the inherent scale ambiguity issue; 2) the BEV layout is directly predicted from the front-view image without using any depth-related information, although the depth map contains useful geometry clues for inferring scene layouts.