Lune

CVPR2025Top-tier venue

ColabSfM: Collaborative Structure-from-Motion by Point Cloud Registration

Johan Edstedt, André Mateus, Alberto Jaenal

2025Year
2Top-tier citations

Abstract

Figure 1 . Our proposed registration paradigm for collaborative SfM reconstructions (ColabSfM). Given two input SfM reconstructions P, Q of the same scene, the task is to estimate the relative similarity transform (s, R, t) between them. Our first contribution is to address this as a point cloud registration problem, using only 3D SfM tracks. For this, we do not rely on the visual descriptors, but on the 3D coordinates of the points P, Q, their normals N, M and, optionally, but not necessarily, features X, Y. To make point cloud registration methods perform well on this task, we propose as our second contribution a scalable pipeline to construct synthetic training datasets for SfM registration. Finally, we propose an improved version of RoITr [64] as registration method f θ .

Ask about this paper

Your agent reads all of it.

Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.

Questions to start from

Your agent calls

Luneget_paper_fulltext

Ask in Lune

Free to start. No credit card required.

lune papers fulltext 1c836881-86ef-4957-bc60-a16a7f6f2dcc

Cited by top-tier papers2

Ask how each one uses it

Builds on18

Related papers

Dusk over the sea between two cliffs drawn in fine vertical lines