Robustness-Aware 3D Object Detection in Autonomous Driving: A Review and Outlook
Beijing Jiaotong University · The University of Queensland · +3 more institutions
Abstract
In the realm of modern autonomous driving, the perception system is indispensable for accurately assessing the state of the surrounding environment, thereby enabling informed prediction and planning. The key step to this system is related to 3D object detection that utilizes vehicle-mounted sensors such as LiDAR and cameras to identify the size, the category, and the location of nearby objects. Despite the surge in 3D object detection methods aimed at enhancing detection precision and efficiency, there is a gap in the literature that systematically examines their resilience against environmental variations, noise, and weather changes. This study emphasizes the importance of robustness, alongside accuracy and…
Citation impact
- FWCI
- 28.95
- Percentile
- 100%
- References
- 481
Authors
8Topics & keywords
- Robustness (evolution)
- Computer science
- Artificial intelligence