Towards Robust 3D Object Detection In Rainy Conditions
Author:
Affiliation:
1. Institute of Measurement, Control, and Microtechnology, Ulm University,Germany
2. BMW AG,Munich,Germany,80809
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10420842/10420843/10422250.pdf?arnumber=10422250
Reference29 articles.
1. Energy-Based Detection of Adverse Weather Effects in LiDAR Data
2. Robustness of Object Detectors in Degrading Weather Conditions
3. Detection of Condensed Vehicle Gas Exhaust in LiDAR Point Clouds
4. Benchmarking Robustness of 3D Object Detection to Common Corruptions in Autonomous Driving
5. Robust 3D Object Detection in Cold Weather Conditions
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1. DAN-YOLO: A Lightweight and Accurate Object Detector Using Dilated Aggregation Network for Autonomous Driving;Electronics;2024-08-27
2. Simulating Road Spray Effects in Automotive Lidar Sensor Models;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02
3. SemanticSpray++: A Multimodal Dataset for Autonomous Driving in Wet Surface Conditions;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02
4. Label-Efficient Semantic Segmentation of LiDAR Point Clouds in Adverse Weather Conditions;IEEE Robotics and Automation Letters;2024-06
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