337 citations · 608 across the 32 of their papers we have counts for
8 papers · 1 filter
The Shape Part Slot Machine: Contact-based Reasoning for Generating 3D Shapes from Parts
Kai Wang, Paul Guerrero, Vladimir Kim +3
We present the Shape Part Slot Machine, a new method for assembling novel 3D shapes from existing parts by performing contact-based reasoning. Our method represents each shape as a…
ReGroup: Recursive Neural Networks for Hierarchical Grouping of Vector Graphic Primitives
Sumit Chaturvedi, Michal Lukáč, Siddhartha Chaudhuri
Selection functionality is as fundamental to vector graphics as it is for raster data. But vector selection is quite different: instead of pixel-level labeling, we make a binary de…
Temporally-Consistent Surface Reconstruction using Metrically-Consistent Atlases
Jan Bednarik, Noam Aigerman, Vladimir G. Kim +4
We propose a method for unsupervised reconstruction of a temporally-consistent sequence of surfaces from a sequence of time-evolving point clouds. It yields dense and semantically…
BuildingNet: Learning to Label 3D Buildings
Pratheba Selvaraju, Mohamed Nabail, Marios Loizou +5
We introduce BuildingNet: (a) a large-scale dataset of 3D building models whose exteriors are consistently labeled, (b) a graph neural network that labels building meshes by analyz…
GLASS: Geometric Latent Augmentation for Shape Spaces
Sanjeev Muralikrishnan, Siddhartha Chaudhuri, Noam Aigerman +3
We investigate the problem of training generative models on a very sparse collection of 3D models. We use geometrically motivated energies to augment and thus boost a sparse collec…
Temporally-Coherent Surface Reconstruction via Metric-Consistent Atlases
Jan Bednarik, Vladimir G. Kim, Siddhartha Chaudhuri +4
We propose a method for the unsupervised reconstruction of a temporally-coherent sequence of surfaces from a sequence of time-evolving point clouds, yielding dense, semantically me…