2 citations · 2 across the 7 of their papers we have counts for
6 papers · 1 filter
DJM: Compact Base Meshes for Displacement Mapping using Triangle Jacobians
Congyi Zhang, Nicholas Vining, Yanhong Lin +5
Representing complex geometry as a displacement function defined over a coarse base mesh enables compact storage and accelerated rendering. The core challenge in converting detaile…
NeuVAS: Neural Implicit Surfaces for Variational Shape Modeling
Pengfei Wang, Qiujie Dong, Fangtian Liang +11
Neural implicit shape representation has drawn significant attention in recent years due to its smoothness, differentiability, and topological flexibility. However, directly modeli…
NESI: Shape Representation via Neural Explicit Surface Intersection
Congyi Zhang, Jinfan Yang, Eric Hedlin +5
Compressed representations of 3D shapes that are compact, accurate, and can be processed efficiently directly in compressed form, are extremely useful for digital media application…
Region-Aware Color Smudging
Ying Jiang, Pengfei Xu, Congyi Zhang +3
Color smudge operations from digital painting software enable users to create natural shading effects in high-fidelity paintings by interactively mixing colors. To precisely contro…
Neural Parametric Surfaces for Shape Modeling
Lei Yang, Yongqing Liang, Xin Li +6
The recent surge of utilizing deep neural networks for geometric processing and shape modeling has opened up exciting avenues. However, there is a conspicuous lack of research effo…
Surface Extraction from Neural Unsigned Distance Fields
Congyi Zhang, Guying Lin, Lei Yang +5
We propose a method, named DualMesh-UDF, to extract a surface from unsigned distance functions (UDFs), encoded by neural networks, or neural UDFs. Neural UDFs are becoming increasi…