EchoMatch: Partial-to-Partial Shape Matching via Correspondence Reflection
MCML Authors
Daniel Cremers
Prof. Dr.
Director
Abstract
Daniel Cremers
Prof. Dr.
Director
Abstract
Finding correspondences between 3D shapes is a crucial problem in computer vision and graphics. While most research has focused on finding correspondences in settings where at least one of the shapes is complete, the realm of partial-to-partial shape matching remains under-explored. Yet it is of importance since, in many applications, shapes are only observed partially due to occlusion or scanning.Finding correspondences between partial shapes comes with an additional challenge: We not only want to identify correspondences between points on either shape but also have to determine which points of each shape actually have a partner.To tackle this challenging problem, we present EchoMatch, a novel framework for partial-to-partial shape matching that incorporates the concept of correspondence reflection to enable an overlap prediction within a functional map framework.With this approach, we show that we can outperform current SOTA methods in challenging partial-to-partial shape matching problems.
inproceedings XER+25
CVPR 2025
IEEE/CVF Conference on Computer Vision and Pattern Recognition. Nashville, TN, USA, Jun 11-15, 2025.
Authors
Y. Xie • V. Ehm • P. Roetzer • N. Amrani • M. Gao • F. Bernard • D. CremersLinks
DOIResearch Area
BibTeXKey: XER+25