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cs.CV2026

RegFormer++: An Efficient Large-Scale 3D LiDAR Point Registration Network with Projection-Aware 2D Transformer

Jiuming Liu, Guangming Wang, Zhe Liu +7

Although point cloud registration has achieved remarkable advances in object-level and indoor scenes, large-scale LiDAR registration methods has been rarely explored before. Challe…

cs.CV2025

Reloc-VGGT: Visual Re-localization with Geometry Grounded Transformer

Tianchen Deng, Wenhua Wu, Kunzhen Wu +7

Visual localization has traditionally been formulated as a pair-wise pose regression problem. Existing approaches mainly estimate relative poses between two images and employ a lat…

cs.CV2024

Spherical Frustum Sparse Convolution Network for LiDAR Point Cloud Semantic Segmentation

Yu Zheng, Guangming Wang, Jiuming Liu +2

LiDAR point cloud semantic segmentation enables the robots to obtain fine-grained semantic information of the surrounding environment. Recently, many works project the point cloud…

cs.CV2024

DSLO: Deep Sequence LiDAR Odometry Based on Inconsistent Spatio-temporal Propagation

Huixin Zhang, Guangming Wang, Xinrui Wu +5

This paper introduces a 3D point cloud sequence learning model based on inconsistent spatio-temporal propagation for LiDAR odometry, termed DSLO. It consists of a pyramid structure…

cs.CV2024

DifFlow3D: Toward Robust Uncertainty-Aware Scene Flow Estimation with Diffusion Model

Jiuming Liu, Guangming Wang, Weicai Ye +6

Scene flow estimation, which aims to predict per-point 3D displacements of dynamic scenes, is a fundamental task in the computer vision field. However, previous works commonly suff…