1 citations · 3 across the 16 of their papers we have counts for
7 papers · 1 filter
Teaching DINOv3 About Partial 3D Geometry: A Self-Supervised Geometry-Aware Approach
Viktoria Ehm, Dongliang Cao, Riccardo Marin +4
Partial shape matching is a crucial yet underexplored problem in 3D vision, with significant relevance to real-world scenarios where shapes are often only partially observed. Exist…
Towards Stellarator Geometry Optimisation for Nuclear Fusion
Tobias Weißberg, Moritz Heep, Zorah Lähner +1
We present a local geometry refinement method and a 2D latent representation that took us to the top of the ConStellaration leaderboard on the geometric task in May 2026.
Unsupervised Pixel-Level Semantic Left-Right Understanding of In-the-Wild Images
Weikang Wang, Tobias Weißberg, Florian Bernard
While various works address reflective symmetry understanding in 3D data and images, pixel-level semantic left-right prediction of in-the-wild images remains challenging, due to ce…
Hyper-Network Neural Functional Maps for Unsupervised Robust 3D Shape Matching
Dongliang Cao, Florian Bernard
Functional maps are the cornerstone of recent non-rigid 3D shape matching methods due to their efficiency and performance. However, existing methods struggle with challenging scena…
Non-Rigid 3D Shape Correspondences: From Foundations to Open Challenges and Opportunities
Aleksei Zhuravlev, Lennart Bastian, Dongliang Cao +12
Estimating correspondences between deformed shape instances is a long-standing problem in computer graphics; numerous applications, from texture transfer to statistical modelling,…
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…
Symmetry Informative and Agnostic Feature Disentanglement for 3D Shapes
Tobias Weißberg, Weikang Wang, Paul Roetzer +2
Shape descriptors, i.e., per-vertex features of 3D meshes or point clouds, are fundamental to shape analysis. Historically, various handcrafted geometry-aware descriptors and featu…