5 papers
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…
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…
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…
Symmetry Understanding of 3D Shapes via Chirality Disentanglement
Weikang Wang, Tobias Weißberg, Nafie El Amrani +1
Chirality information (i.e. information that allows distinguishing left from right) is ubiquitous for various data modes in computer vision, including images, videos, point clouds,…
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…