Joint‐Learning: A Robust Segmentation Method for 3D Point Clouds Under Label Noise

• Published in: Computer animation and virtual worlds Vol. 36; no. 3
• Main Authors: Zhang, Mengyao, Zhou, Jie, Miao, Tingyun, Zhao, Yong, Si, Xin, Zhang, Jingliang
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 01.05.2025; Wiley Subscription Services, Inc
• Subjects: adaptive sample selection; Adaptive sampling; Datasets; dual‐network framework; Image segmentation; joint label correction; label noise; Labels; Learning; Networks; Noise; point cloud segmentation; Three dimensional models

ABSTRACT Most of point cloud segmentation methods are based on clean datasets and are easily affected by label noise. We present a novel method called Joint‐learning, which is the first attempt to apply a dual‐network framework to point cloud segmentation with noisy labels. Two networks are trained...