2.1k citations · 2.4k across the 8 of their papers we have counts for
3 papers · 1 filter
StructEdit: Learning Structural Shape Variations
Kaichun Mo, Paul Guerrero, Li Yi +4
Learning to encode differences in the geometry and (topological) structure of the shapes of ordinary objects is key to generating semantically plausible variations of a given shape…
StructureNet: Hierarchical Graph Networks for 3D Shape Generation
Kaichun Mo, Paul Guerrero, Li Yi +4
The ability to generate novel, diverse, and realistic 3D shapes along with associated part semantics and structure is central to many applications requiring high-quality 3D assets…
DeepSpline: Data-Driven Reconstruction of Parametric Curves and Surfaces
Jun Gao, Chengcheng Tang, Vignesh Ganapathi-Subramanian +3
Reconstruction of geometry based on different input modes, such as images or point clouds, has been instrumental in the development of computer aided design and computer graphics.…