5 citations · 6 across the 3 of their papers we have counts for
3 papers
CageNet: A Meta-Framework for Learning on Wild Meshes
Michal Edelstein, Hsueh-Ti Derek Liu, Mirela Ben-Chen
Learning on triangle meshes has recently proven to be instrumental to a myriad of tasks, from shape classification, to segmentation, to deformation and animation, to mention just a…
Designing 3D Anisotropic Frame Fields with Odeco Tensors
Haikuan Zhu, Hongbo Li, Hsueh-Ti Derek Liu +3
This paper introduces a method to synthesize a 3D tensor field within a constrained geometric domain represented as a tetrahedral mesh. Whereas previous techniques optimize for iso…
Kubric: A scalable dataset generator
Klaus Greff, Francois Belletti, Lucas Beyer +32
Data is the driving force of machine learning, with the amount and quality of training data often being more important for the performance of a system than architecture and trainin…