← Search

Jinlai Zhang

2 accepted papers

2024

Improving Robustness of 3D Point Cloud Recognition from a Fourier Perspective

NeurIPS 2024poster

Although 3D point cloud recognition has achieved substantial progress on standard benchmarks, the typical models are vulnerable to point cloud corruptions, leading to security threats in real-world applications. To improve the corruption robustness, various data augmentation methods have been studie…

Cited by 0SourcePDFScholar
2023

Benchmarking Robustness of 3D Object Detection to Common Corruptions

CVPR 2023poster

3D object detection is an important task in autonomous driving to perceive the surroundings. Despite the excellent performance, the existing 3D detectors lack the robustness to real-world corruptions caused by adverse weathers, sensor noises, etc., provoking concerns about the safety and reliability…