most citedUnsupervised Deep Probabilistic Approach for Partial Point Cloud Registration

3 citations · 4 across the 5 of their papers we have counts for

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cs.CV2024

GSTran: Joint Geometric and Semantic Coherence for Point Cloud Segmentation

Abiao Li, Chenlei Lv, Guofeng Mei +3

Learning meaningful local and global information remains a challenge in point cloud segmentation tasks. When utilizing local information, prior studies indiscriminately aggregates…

cs.CV20241 cited

Bringing Masked Autoencoders Explicit Contrastive Properties for Point Cloud Self-Supervised Learning

Bin Ren, Guofeng Mei, Danda Pani Paudel +6

Contrastive learning (CL) for Vision Transformers (ViTs) in image domains has achieved performance comparable to CL for traditional convolutional backbones. However, in 3D point cl…

cs.CV2023

Attentive Multimodal Fusion for Optical and Scene Flow

Youjie Zhou, Guofeng Mei, Yiming Wang +2

This paper presents an investigation into the estimation of optical and scene flow using RGBD information in scenarios where the RGB modality is affected by noise or captured in da…

cs.CV2023

Cross-source Point Cloud Registration: Challenges, Progress and Prospects

Xiaoshui Huang, Guofeng Mei, Jian Zhang

The emerging topic of cross-source point cloud (CSPC) registration has attracted increasing attention with the fast development background of 3D sensor technologies. Different from…

cs.CV20233 cited

Unsupervised Deep Probabilistic Approach for Partial Point Cloud Registration

Guofeng Mei, Hao Tang, Xiaoshui Huang +5

Deep point cloud registration methods face challenges to partial overlaps and rely on labeled data. To address these issues, we propose UDPReg, an unsupervised deep probabilistic r…