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BridgeMatch: Conditional Transport Bridges in Matching Matrix Space for 3D Deformable Registration

arxiv.org/abs/2609.11472

Updated 51 min ago · first seen 11 Sept 2026

paper_01M294H23Y6WZP96D8ZJBB6SD4

Published
11 Sept 2026
T1 · 51 min ago
arXiv
2609.11472
T1 · 51 min ago
Category
cs.CV
T1 · 51 min ago

Abstract

Reliable non-rigid point cloud correspondences are important for deformable anatomical registration, embodied perception and manipulation, and dynamic 3D reconstruction. Coarse-to-fine methods reduce computational cost by selecting the top-\(K\) coarse regions. However, this pruning may remove weak but correct hypotheses and restrict fine matching to an incomplete search space. We present \paper, a two-stage generative solver that maintains the complete soft matching matrix at both coarse and high resolutions. Stage~I uses denoising diffusion to estimate a global matching matrix in the compact coarse-resolution space. We then lift this matrix to high resolution while preserving its hierarchy. The lifted matrix is rank-bounded and block-constant. Stage~II refines it through a conditional transport bridge. We implement the bridge with two types of dynamics: a deterministic endpoint-parameterized conditional Flow Matching (CFM) ODE and a stochastic Brownian-bridge SDE inspired by Schr\"odinger bridges. Both variants share the lifted source, a time-conditioned transformer, and a matching-matrix endpoint predictor. Experiments on 4DMatch and 4DLoMatch show that both variants produce more accurate correspondences than the compared methods and improve downstream registration, with larger gains in low-overlap cases. They also improve cross-dataset generalization on CAPE and DeepDeform without target-domain adaptation while using the same deformation solver.

Authors 7

Qianliang Wu, Haobo Jiang, Guangwei Gao, Shuo Chen, Jin Xie, Jian Yang, Yaqing Ding

Specification

Official page

Source:arXiv (Atom API + RSS)T1observed 51 min agohigh

Arxiv announce type
new

Source:arXiv (Atom API + RSS)T1observed 51 min agohigh

arXiv id
2609.11472

Source:arXiv (Atom API + RSS)T1observed 51 min agohigh

Categories
cs.CV

Source:arXiv (Atom API + RSS)T1observed 51 min agohigh

PDF

Source:arXiv (Atom API + RSS)T1observed 51 min agohigh

Primary category
cs.CV

Source:arXiv (Atom API + RSS)T1observed 51 min agohigh

Published
11 Sept 2026

Source:arXiv (Atom API + RSS)T1observed 51 min agohigh

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Provenance

Attributed facts

9

Source tiers

T19

Freshest observation

51 min ago

Conflicts

None