261 citations · 852 across the 31 of their papers we have counts for
6 papers · 1 filter
Breaking Bad: A Dataset for Geometric Fracture and Reassembly
Silvia Sellán, Yun-Chun Chen, Ziyi Wu +2
We introduce Breaking Bad, a large-scale dataset of fractured objects. Our dataset consists of over one million fractured objects simulated from ten thousand base models. The fract…
Variable Bitrate Neural Fields
Towaki Takikawa, Alex Evans, Jonathan Tremblay +4
Neural approximations of scalar and vector fields, such as signed distance functions and radiance fields, have emerged as accurate, high-quality representations. State-of-the-art r…
Stochastic Poisson Surface Reconstruction
Silvia Sellán, Alec Jacobson
We introduce a statistical extension of the classic Poisson Surface Reconstruction algorithm for recovering shapes from 3D point clouds. Instead of outputting an implicit function,…
VectorAdam for Rotation Equivariant Geometry Optimization
Selena Ling, Nicholas Sharp, Alec Jacobson
The Adam optimization algorithm has proven remarkably effective for optimization problems across machine learning and even traditional tasks in geometry processing. At the same tim…
Learning Smooth Neural Functions via Lipschitz Regularization
Hsueh-Ti Derek Liu, Francis Williams, Alec Jacobson +2
Neural implicit fields have recently emerged as a useful representation for 3D shapes. These fields are commonly represented as neural networks which map latent descriptors and 3D…
Spelunking the Deep: Guaranteed Queries on General Neural Implicit Surfaces via Range Analysis
Nicholas Sharp, Alec Jacobson
Neural implicit representations, which encode a surface as the level set of a neural network applied to spatial coordinates, have proven to be remarkably effective for optimizing,…