activity
20202026
most citedA comprehensive survey on point cloud registration

187 citations · 222 across the 22 of their papers we have counts for

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Showing 2025Show all

5 papers · 1 filter

cs.CV2025

A Self-Conditioned Representation Guided Diffusion Model for Realistic Text-to-LiDAR Scene Generation

Wentao Qu, Guofeng Mei, Yang Wu +3

Text-to-LiDAR generation can customize 3D data with rich structures and diverse scenes for downstream tasks. However, the scarcity of Text-LiDAR pairs often causes insufficient tra…

cs.CV2025

Robust Single-Stage Fully Sparse 3D Object Detection via Detachable Latent Diffusion

Wentao Qu, Guofeng Mei, Jing Wang +3

Denoising Diffusion Probabilistic Models (DDPMs) have shown success in robust 3D object detection tasks. Existing methods often rely on the score matching from 3D boxes or pre-trai…

cs.CV2025

Masked Clustering Prediction for Unsupervised Point Cloud Pre-training

Bin Ren, Xiaoshui Huang, Mengyuan Liu +4

Vision transformers (ViTs) have recently been widely applied to 3D point cloud understanding, with masked autoencoding as the predominant pre-training paradigm. However, the challe…

cs.CV2025

PointGAC: Geometric-Aware Codebook for Masked Point Cloud Modeling

Abiao Li, Chenlei Lv, Yuming Fang +3

Most masked point cloud modeling (MPM) methods follow a regression paradigm to reconstruct the coordinate or feature of masked regions. However, they tend to over-constrain the mod…

cs.CV2025

Fully-Geometric Cross-Attention for Point Cloud Registration

Weijie Wang, Guofeng Mei, Jian Zhang +3

Point cloud registration approaches often fail when the overlap between point clouds is low due to noisy point correspondences. This work introduces a novel cross-attention mechani…