BEVStereo: Enhancing Depth Estimation in Multi-View 3D Object Detection with Temporal Stereo
Institute of Computing Technology · University of Chinese Academy of Sciences · +3 more institutions
Abstract
Restricted by the ability of depth perception, all Multi-view 3D object detection methods fall into the bottleneck of depth accuracy. By constructing temporal stereo, depth estimation is quite reliable in indoor scenarios. However, there are two difficulties in directly integrating temporal stereo into outdoor multi-view 3D object detectors: 1) The construction of temporal stereos for all views results in high computing costs. 2) Unable to adapt to challenging outdoor scenarios. In this study, we propose an effective method for creating temporal stereo by dynamically determining the center and range of the temporal stereo. The most confident center is found using the EM algorithm. Numerous experiments on…
Citation impact
- FWCI
- 10.79
- Percentile
- 100%
- References
- 50
Authors
6- YLYinhao LiCorresponding
Institute of Computing Technology, University of Chinese Academy of Sciences
- HBHan Bao
Institute of Computing Technology, University of Chinese Academy of Sciences
- ZGZheng Ge
Vi Technology (United States), Megvii (China)
- JYJinrong Yang
Huazhong University of Science and Technology
- JSJianjian Sun
Vi Technology (United States), Megvii (China)
Topics & keywords
- Computer science
- Artificial intelligence
- Computer vision
- Bottleneck
- Stereopsis
- Stereo camera
- Object (grammar)
- Depth perception
- Sustainable cities and communities