110 citations · 170 across the 10 of their papers we have counts for
5 papers · 1 filter
fVDB: A Deep-Learning Framework for Sparse, Large-Scale, and High-Performance Spatial Intelligence
Francis Williams, Jiahui Huang, Jonathan Swartz +9
We present fVDB, a novel GPU-optimized framework for deep learning on large-scale 3D data. fVDB provides a complete set of differentiable primitives to build deep learning architec…
Learning a Generalized Physical Face Model From Data
Lingchen Yang, Gaspard Zoss, Prashanth Chandran +4
Physically-based simulation is a powerful approach for 3D facial animation as the resulting deformations are governed by physical constraints, allowing to easily resolve self-colli…
An Implicit Physical Face Model Driven by Expression and Style
Lingchen Yang, Gaspard Zoss, Prashanth Chandran +5
3D facial animation is often produced by manipulating facial deformation models (or rigs), that are traditionally parameterized by expression controls. A key component that is usua…
Fast Sparse 3D Convolution Network with VDB
Fangjun Zhou, Anyong Mao, Eftychios Sifakis
We proposed a new Convolution Neural Network implementation optimized for sparse 3D data inference. This implementation uses NanoVDB as the data structure to store the sparse tenso…
Real-time Non-line-of-Sight imaging of dynamic scenes
Ji Hyun Nam, Eric Brandt, Sebastian Bauer +3
Non-Line-of-Sight (NLOS) imaging aims at recovering the 3D geometry of objects that are hidden from the direct line of sight. In the past, this method has suffered from the weak av…