32 citations · 58 across the 15 of their papers we have counts for
14 papers · 1 filter
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…
Spectral Meets Spatial: Harmonising 3D Shape Matching and Interpolation
Dongliang Cao, Marvin Eisenberger, Nafie El Amrani +2
Although 3D shape matching and interpolation are highly interrelated, they are often studied separately and applied sequentially to relate different 3D shapes, thus resulting in su…
SatSynth: Augmenting Image-Mask Pairs through Diffusion Models for Aerial Semantic Segmentation
Aysim Toker, Marvin Eisenberger, Daniel Cremers +1
In recent years, semantic segmentation has become a pivotal tool in processing and interpreting satellite imagery. Yet, a prevalent limitation of supervised learning techniques rem…
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…
SIGMA: Scale-Invariant Global Sparse Shape Matching
Maolin Gao, Paul Roetzer, Marvin Eisenberger +4
We propose a novel mixed-integer programming (MIP) formulation for generating precise sparse correspondences for highly non-rigid shapes. To this end, we introduce a projected Lapl…
G-MSM: Unsupervised Multi-Shape Matching with Graph-based Affinity Priors
Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé +1
We present G-MSM (Graph-based Multi-Shape Matching), a novel unsupervised learning approach for non-rigid shape correspondence. Rather than treating a collection of input poses as…