3 papers
cs.GR2025
Attention-Guided Multi-Scale Local Reconstruction for Point Clouds via Masked Autoencoder Self-Supervised Learning
Xin Cao, Haoyu Wang, Yuzhu Mao +3
Self-supervised learning has emerged as a prominent research direction in point cloud processing. While existing models predominantly concentrate on reconstruction tasks at higher…
cs.CV2023
PointMoment:Mixed-Moment-based Self-Supervised Representation Learning for 3D Point Clouds
Xin Cao, Xinxin Han, Yifan Wang +2
Large and rich data is a prerequisite for effective training of deep neural networks. However, the irregularity of point cloud data makes manual annotation time-consuming and labor…
cs.CV2023
PointJEM: Self-supervised Point Cloud Understanding for Reducing Feature Redundancy via Joint Entropy Maximization
Xin Cao, Huan Xia, Xinxin Han +3
Most deep learning-based point cloud processing methods are supervised and require large scale of labeled data. However, manual labeling of point cloud data is laborious and time-c…