Hsueh-Ti Derek Liu | DeepAI

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∙ 05/10/2023

Surface Simplification using Intrinsic Error Metrics

This paper describes a method for fast simplification of surface meshes....

0 Hsueh-Ti Derek Liu, et al. ∙

∙ 02/16/2022

Learning Smooth Neural Functions via Lipschitz Regularization

Neural implicit fields have recently emerged as a useful representation ...

3 Hsueh-Ti Derek Liu, et al. ∙

∙ 04/28/2021

Surface Multigrid via Intrinsic Prolongation

This paper introduces a novel geometric multigrid solver for unstructure...

0 Hsueh-Ti Derek Liu, et al. ∙

∙ 04/24/2021

Normal-Driven Spherical Shape Analogies

This paper introduces a new method to stylize 3D geometry. The key obser...

0 Hsueh-Ti Derek Liu, et al. ∙

∙ 09/04/2020

Chordal Decomposition for Spectral Coarsening

We introduce a novel solver to significantly reduce the size of a geomet...

0 Honglin Chen, et al. ∙

∙ 05/04/2020

Neural Subdivision

This paper introduces Neural Subdivision, a novel framework for data-dri...

0 Hsueh-Ti Derek Liu, et al. ∙

∙ 10/07/2019

Cubic Stylization

We present a 3D stylization algorithm that can turn an input shape into ...

0 Hsueh-Ti Derek Liu, et al. ∙

∙ 05/08/2019

Spectral Coarsening of Geometric Operators

We introduce a novel approach to measure the behavior of a geometric ope...

0 Hsueh-Ti Derek Liu, et al. ∙

∙ 08/08/2018

Adversarial Geometry and Lighting using a Differentiable Renderer

Many machine learning classifiers are vulnerable to adversarial attacks,...

2 Hsueh-Ti Derek Liu, et al. ∙

∙ 08/08/2018

Beyond Pixel Norm-Balls: Parametric Adversaries using an Analytically Differentiable Renderer

Many machine learning image classifiers are vulnerable to adversarial at...

0 Hsueh-Ti Derek Liu, et al. ∙

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