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20232026
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cs.CV2026

An Integer Linear Programming Approach to Geometrically Consistent Partial-Partial Shape Matching

Viktoria Ehm, Paul Roetzer, Florian Bernard +1

The task of establishing correspondences between two 3D shapes is a long-standing challenge in computer vision. While numerous studies address full-full and partial-full 3D shape m…

cs.CV2024

Beyond Complete Shapes: A Benchmark for Quantitative Evaluation of 3D Shape Surface Matching Algorithms

Viktoria Ehm, Nafie El Amrani, Yizheng Xie +9

Finding correspondences between 3D deformable shapes is an important and long-standing problem in geometry processing, computer vision, graphics, and beyond. While various shape ma…

cs.CV2024

Partial-to-Partial Shape Matching with Geometric Consistency

Viktoria Ehm, Maolin Gao, Paul Roetzer +3

Finding correspondences between 3D shapes is an important and long-standing problem in computer vision, graphics and beyond. A prominent challenge are partial-to-partial shape matc…

cs.CV2023

Geometrically Consistent Partial Shape Matching

Viktoria Ehm, Paul Roetzer, Marvin Eisenberger +3

Finding correspondences between 3D shapes is a crucial problem in computer vision and graphics, which is for example relevant for tasks like shape interpolation, pose transfer, or…

cs.CV2023

Non-Separable Multi-Dimensional Network Flows for Visual Computing

Viktoria Ehm, Daniel Cremers, Florian Bernard

Flows in networks (or graphs) play a significant role in numerous computer vision tasks. The scalar-valued edges in these graphs often lead to a loss of information and thereby to…