3 papers
cs.CV2026
UGD: An Unsupervised Geometric Distance for Evaluating Real-world Noisy Point Cloud Denoising
Zhiyong Su, Jincan Wu, Yonghui Liu +2
Point cloud denoising is a fundamental and crucial challenge in real-world point cloud applications. Existing quantitative evaluation metrics for point cloud denoising methods are…
cs.RO2026
CLAIM: Camera-LiDAR Alignment with Intensity and Monodepth
Zhuo Zhang, Yonghui Liu, Meijie Zhang +2
In this paper, we unleash the potential of the powerful monodepth model in camera-LiDAR calibration and propose CLAIM, a novel method of aligning data from the camera and LiDAR. Gi…
eess.IV2026
UPDA: Unsupervised Progressive Domain Adaptation for No-Reference Point Cloud Quality Assessment
Bingxu Xie, Fang Zhou, Jincan Wu +3
While no-reference point cloud quality assessment (NR-PCQA) approaches have achieved significant progress over the past decade, their performance often degrades substantially when…