Radar-Camera Fusion for Object Detection and Semantic Segmentation in Autonomous Driving: A Comprehensive Review
University of Liverpool · Xi’an Jiaotong-Liverpool University
Abstract
Driven by deep learning techniques, perception technology in autonomous driving has developed rapidly in recent years, enabling vehicles to accurately detect and interpret surrounding environment for safe and efficient navigation. To achieve accurate and robust perception capabilities, autonomous vehicles are often equipped with multiple sensors, making sensor fusion a crucial part of the perception system. Among these fused sensors, radars and cameras enable a complementary and cost-effective perception of the surrounding environment regardless of lighting and weather conditions. This review aims to provide a comprehensive guideline for radar-camera fusion, particularly concentrating on perception tasks…
Citation impact
- FWCI
- 22.55
- Percentile
- 100%
- References
- 348
Authors
11Topics & keywords
- Computer vision
- Artificial intelligence
- Segmentation
- Computer science
- Fusion
- Object (grammar)
- Radar
- Object detection