51 citations · 128 across the 10 of their papers we have counts for
12 papers
A Geodesic Cut-Cell Prior for Neural Skinning
Wenchao Ma, Surya Dwarakanath, Yizhak Ben-Shabat +4
We introduce cut-cell skinning, a geometric prior designed to augment data-driven skinning weight generation. While data-driven methods show promise in producing high-quality skinn…
Trust-Region Eigenvalue Filtering for Projected Newton
Honglin Chen, Hsueh-Ti Derek Liu, Alec Jacobson +2
We introduce a novel adaptive eigenvalue filtering strategy to stabilize and accelerate the optimization of Neo-Hookean energy and its variants under the Projected Newton framework…
Stabler Neo-Hookean Simulation: Absolute Eigenvalue Filtering for Projected Newton
Honglin Chen, Hsueh-Ti Derek Liu, David I. W. Levin +2
Volume-preserving hyperelastic materials are widely used to model near-incompressible materials such as rubber and soft tissues. However, the numerical simulation of volume-preserv…
Surface Simplification using Intrinsic Error Metrics
Hsueh-Ti Derek Liu, Mark Gillespie, Benjamin Chislett +3
This paper describes a method for fast simplification of surface meshes. Whereas past methods focus on visual appearance, our goal is to solve equations on the surface. Hence, rath…
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…
Surface Multigrid via Intrinsic Prolongation
Hsueh-Ti Derek Liu, Jiayi Eris Zhang, Mirela Ben-Chen +1
This paper introduces a novel geometric multigrid solver for unstructured curved surfaces. Multigrid methods are highly efficient iterative methods for solving systems of linear eq…
Normal-Driven Spherical Shape Analogies
Hsueh-Ti Derek Liu, Alec Jacobson
This paper introduces a new method to stylize 3D geometry. The key observation is that the surface normal is an effective instrument to capture different geometric styles. Centered…
Chordal Decomposition for Spectral Coarsening
Honglin Chen, Hsueh-Ti Derek Liu, Alec Jacobson +1
We introduce a novel solver to significantly reduce the size of a geometric operator while preserving its spectral properties at the lowest frequencies. We use chordal decompositio…
Neural Subdivision
Hsueh-Ti Derek Liu, Vladimir G. Kim, Siddhartha Chaudhuri +2
This paper introduces Neural Subdivision, a novel framework for data-driven coarse-to-fine geometry modeling. During inference, our method takes a coarse triangle mesh as input and…
Cubic Stylization
Hsueh-Ti Derek Liu, Alec Jacobson
We present a 3D stylization algorithm that can turn an input shape into the style of a cube while maintaining the content of the original shape. The key insight is that cubic style…
Spectral Coarsening of Geometric Operators
Hsueh-Ti Derek Liu, Alec Jacobson, Maks Ovsjanikov
We introduce a novel approach to measure the behavior of a geometric operator before and after coarsening. By comparing eigenvectors of the input operator and its coarsened counter…
Beyond Pixel Norm-Balls: Parametric Adversaries using an Analytically Differentiable Renderer
Hsueh-Ti Derek Liu, Michael Tao, Chun-Liang Li +2
Many machine learning image classifiers are vulnerable to adversarial attacks, inputs with perturbations designed to intentionally trigger misclassification. Current adversarial me…