5 citations · 7 across the 8 of their papers we have counts for
9 papers
Levy-Driven Correspondence Estimation for Registration
Qianliang Wu, Jiaqi Yang, Wankou Yang +4
Finding reliable point correspondences is difficult when point clouds have low overlap or undergo non-rigid deformation. Iterative refinement can correct uncertain matches, but cos…
BridgeMatch: Conditional Transport Bridges in Matching Matrix Space for 3D Deformable Registration
Qianliang Wu, Haobo Jiang, Guangwei Gao +5
Reliable matching between partially observed, deforming point clouds requires global context and fine geometric detail. Coarse candidate selection can exclude correct fine-level co…
Diff-Reg v2: Diffusion-Based Matching Matrix Estimation for Image Matching and 3D Registration
Qianliang Wu, Haobo Jiang, Yaqing Ding +5
Establishing reliable correspondences is crucial for all registration tasks, including 2D image registration, 3D point cloud registration, and 2D-3D image-to-point cloud registrati…
Three-view Focal Length Recovery From Homographies
Yaqing Ding, Viktor Kocur, Zuzana Berger Haladová +4
In this paper, we propose a novel approach for recovering focal lengths from three-view homographies. By examining the consistency of normal vectors between two homographies, we de…
Diff-Reg v1: Diffusion Matching Model for Registration Problem
Qianliang Wu, Haobo Jiang, Lei Luo +4
Establishing reliable correspondences is essential for registration tasks such as 3D and 2D3D registration. Existing methods commonly leverage geometric or semantic point features…
Diff-PCR: Diffusion-Based Correspondence Searching in Doubly Stochastic Matrix Space for Point Cloud Registration
Haihua Shi, Qianliang Wu
Efficiently identifying accurate correspondences between point clouds is crucial for both rigid and non-rigid point cloud registration. Existing methods usually rely on geometric o…
SGNet: Salient Geometric Network for Point Cloud Registration
Qianliang Wu, Yaqing Ding, Lei Luo +5
Point Cloud Registration (PCR) is a critical and challenging task in computer vision. One of the primary difficulties in PCR is identifying salient and meaningful points that exhib…
Graph Matching Optimization Network for Point Cloud Registration
Qianliang Wu, Yaqi Shen, Haobo Jiang +5
Point Cloud Registration is a fundamental and challenging problem in 3D computer vision. Recent works often utilize the geometric structure information in point feature embedding o…
Interest-Behaviour Multiplicative Network for Resource-limited Recommendation
Qianliang Wu, Tong Zhang, Zhen Cui +1
Resource constraints, e.g. limited product inventory or financial strength, may affect consumers' choices or preferences in some recommendation tasks but are usually ignored in pre…