6 citations · 8 across the 5 of their papers we have counts for
5 papers
Text-guided Controllable Mesh Refinement for Interactive 3D Modeling
Yun-Chun Chen, Selena Ling, Zhiqin Chen +3
We propose a novel technique for adding geometric details to an input coarse 3D mesh guided by a text prompt. Our method is composed of three stages. First, we generate a single-vi…
Compact Neural Graphics Primitives with Learned Hash Probing
Towaki Takikawa, Thomas Müller, Merlin Nimier-David +4
Neural graphics primitives are faster and achieve higher quality when their neural networks are augmented by spatial data structures that hold trainable features arranged in a grid…
Neural Stochastic Screened Poisson Reconstruction
Silvia Sellán, Alec Jacobson
Reconstructing a surface from a point cloud is an underdetermined problem. We use a neural network to study and quantify this reconstruction uncertainty under a Poisson smoothness…
Bayes' Rays: Uncertainty Quantification for Neural Radiance Fields
Lily Goli, Cody Reading, Silvia Sellán +2
Neural Radiance Fields (NeRFs) have shown promise in applications like view synthesis and depth estimation, but learning from multiview images faces inherent uncertainties. Current…
Breaking Good: Fracture Modes for Realtime Destruction
Silvia Sellán, Jack Luong, Leticia Mattos Da Silva +3
Drawing a direct analogy with the well-studied vibration or elastic modes, we introduce an object's fracture modes, which constitute its preferred or most natural ways of breaking.…