DAIR-V2X: A Large-Scale Dataset for Vehicle-Infrastructure Cooperative 3D Object Detection

Aviation Industry Corporation of China (China) · Tsinghua University · +2 more institutions

Indexed incrossref

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

485
total citations
FWCI
26.79
Percentile
100%
References
34
Citations per year

Authors

11

Topics & keywords

Keywords
  • Computer science
  • Benchmark (surveying)
  • Task (project management)
  • Object (grammar)
  • Sensor fusion
  • Object detection
  • Scale (ratio)
  • Real-time computing
UN Sustainable Development Goals
  • Industry, innovation and infrastructure
No related works found for this paper.