LIDSOR: A FILTER FOR REMOVING RAIN AND SNOW NOISE POINTS FROM LIDAR POINT CLOUDS IN RAINY AND SNOWY WEATHER

7 citations as recorded by crossref.

1. AdverseNet: A LiDAR Point Cloud Denoising Network for Autonomous Driving in Rainy, Snowy, and Foggy Weather X. Yan et al. 10.1109/JSEN.2024.3505234
2. LAWA: LiDAR Adverse Weather Augmentation for Robust Point Cloud Semantic Segmentation H. Kang et al. 10.1109/JSEN.2025.3580941
3. High-Speed Outlier Removal Filter for LiDAR Sensor Point Cloud Data Y. Byun & R. Jeong 10.1109/ACCESS.2024.3517750
4. LiDAR Denoising Methods in Adverse Environments: A Review J. Park et al. 10.1109/JSEN.2025.3526175
5. Denoising Framework Based on Multiframe Continuous Point Clouds for Autonomous Driving LiDAR in Snowy Weather X. Yan et al. 10.1109/JSEN.2024.3358341
6. Point cloud processing under adverse weather: a survey of datasets, enhancement, and denoising methods Z. Gu et al. 10.1007/s11760-025-04352-9
7. LiDAR De-Snow Score (DSS): Combining Quality and Perception Metrics for Optimized De-Noising V. Donzella et al. 10.1109/JSEN.2025.3570478