171 citations · 235 across the 10 of their papers we have counts for
16 papers · 1 filter
Universe Points Representation Learning for Partial Multi-Graph Matching
Zhakshylyk Nurlanov, Frank R. Schmidt, Florian Bernard
Many challenges from natural world can be formulated as a graph matching problem. Previous deep learning-based methods mainly consider a full two-graph matching setting. In this wo…
HandFlow: Quantifying View-Dependent 3D Ambiguity in Two-Hand Reconstruction with Normalizing Flow
Jiayi Wang, Diogo Luvizon, Franziska Mueller +4
Reconstructing two-hand interactions from a single image is a challenging problem due to ambiguities that stem from projective geometry and heavy occlusions. Existing methods are d…
A Unified Framework for Implicit Sinkhorn Differentiation
Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé +2
The Sinkhorn operator has recently experienced a surge of popularity in computer vision and related fields. One major reason is its ease of integration into deep learning framework…
A Scalable Combinatorial Solver for Elastic Geometrically Consistent 3D Shape Matching
Paul Roetzer, Paul Swoboda, Daniel Cremers +1
We present a scalable combinatorial algorithm for globally optimizing over the space of geometrically consistent mappings between 3D shapes. We use the mathematically elegant forma…
The Probabilistic Normal Epipolar Constraint for Frame-To-Frame Rotation Optimization under Uncertain Feature Positions
Dominik Muhle, Lukas Koestler, Nikolaus Demmel +2
The estimation of the relative pose of two camera views is a fundamental problem in computer vision. Kneip et al. proposed to solve this problem by introducing the normal epipolar…
Convex Joint Graph Matching and Clustering via Semidefinite Relaxations
Maximilian Krahn, Florian Bernard, Vladislav Golyanik
This paper proposes a new algorithm for simultaneous graph matching and clustering. For the first time in the literature, these two problems are solved jointly and synergetically w…