2.9k citations · 10.7k across the 136 of their papers we have counts for
3 papers · 2 filters
ComplementMe: Weakly-Supervised Component Suggestions for 3D Modeling
Minhyuk Sung, Hao Su, Vladimir G. Kim +2
Assembly-based tools provide a powerful modeling paradigm for non-expert shape designers. However, choosing a component from a large shape repository and aligning it to a partial a…
GRASS: Generative Recursive Autoencoders for Shape Structures
Jun Li, Kai Xu, Siddhartha Chaudhuri +3
We introduce a novel neural network architecture for encoding and synthesis of 3D shapes, particularly their structures. Our key insight is that 3D shapes are effectively character…
Learning Hierarchical Shape Segmentation and Labeling from Online Repositories
Li Yi, Leonidas Guibas, Aaron Hertzmann +3
We propose a method for converting geometric shapes into hierarchically segmented parts with part labels. Our key idea is to train category-specific models from the scene graphs an…