DAIR-V2X: A Large-Scale Dataset for Vehicle-Infrastructure Cooperative 3D Object Detection
Aviation Industry Corporation of China (China) · Tsinghua University · +2 more institutions
Abstract
Autonomous driving faces great safety challenges for a lack of global perspective and the limitation of long-range perception capabilities. It has been widely agreed that vehicle-infrastructure cooperation is required to achieve Level 5 autonomy. However, there is still NO dataset from real scenarios available for computer vision researchers to work on vehicle-infrastructure cooperation-related problems. To accelerate computer vision research and innovation for Vehicle-Infrastructure Cooperative Autonomous Driving (VICAD), we release DAIR-V2X Dataset, which is the first large-scale, multi-modality, multi-view dataset from real scenarios for VICAD. DAIR-V2X comprises 71254 LiDAR frames and 71254 Camera frames,…
Citation impact
- FWCI
- 26.79
- Percentile
- 100%
- References
- 34
Authors
11- HYHaibao YuCorresponding
Aviation Industry Corporation of China (China), Tsinghua University
- YLYizhen Luo
Tsinghua University, Aviation Industry Corporation of China (China)
- MSMao Shu
Baidu (China)
- YHYiyi Huo
University of Chinese Academy of Sciences, Aviation Industry Corporation of China (China), Tsinghua University
- ZYZebang Yang
Tsinghua University, Aviation Industry Corporation of China (China)
Topics & keywords
- Computer science
- Benchmark (surveying)
- Task (project management)
- Object (grammar)
- Sensor fusion
- Object detection
- Scale (ratio)
- Real-time computing
- Industry, innovation and infrastructure