3 DAILY CVPR Thursday CVPR Daily Publisher: RSIP Vision Copyright: RSIP Vision Editor: Ralph Anzarouth All rights reserved Unauthorized reproduction is strictly forbidden. Our editorial choices are fully independent from IEEE, CVPR and the conference organizers. Paul Roetzer (left) is a PhD student under the supervision of Florian Bernard (right), an Associate Professor at the University of Bonn and the Head of the Learning and Optimisation for Visual Computing Group. Before their oral presentation this afternoon, they speak to us about their highlight paper on 3D shape matching, which has also been chosen as a Best Paper Award candidate. SpiderMatch: 3D Shape Matching with Global Optimality and Geometric Consistency Award Candidate The problem of 3D shape matching involves identifying correspondences between surfaces of 3D objects, a task with applications in medical imaging, graphics, and computer vision. This work’s main novelty is that it accounts for geometric consistency, a property often neglected in previous 3D shape matching methods due to its complexity. Geometric consistency ensures that when matching the surface of one shape to another, the neighboring elements are matched consistently,
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