2 citations · 4 across the 7 of their papers we have counts for
8 papers
CoDimRecon: Agentic Reconstruction of Sim-Ready 3D Scenes with Deformable Curves, Surfaces, and Volumes
Shuzhao Xie, Lelin Wang, Guying Lin +2
Reconstructing simulation-ready 3D scenes from real-world observations enables robotics, gaming, and immersive applications, yet existing methods largely assume rigid objects. This…
PAT3D: Physics-Augmented Text-to-3D Scene Generation
Guying Lin, Kemeng Huang, Michael Liu +8
We introduce PAT3D, the first physics-augmented text-to-3D scene generation framework that integrates vision-language models with physics-based simulation to produce physically pla…
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…
On Optimal Sampling for Learning SDF Using MLPs Equipped with Positional Encoding
Guying Lin, Lei Yang, Yuan Liu +6
Neural implicit fields, such as the neural signed distance field (SDF) of a shape, have emerged as a powerful representation for many applications, e.g., encoding a 3D shape and pe…
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…
Patch-Grid: An Efficient and Feature-Preserving Neural Implicit Surface Representation
Guying Lin, Lei Yang, Congyi Zhang +6
Neural implicit representations are widely used for 3D shape modeling due to their smoothness and compactness, but traditional MLP-based methods struggle with sharp features, such…
Progressively-connected Light Field Network for Efficient View Synthesis
Peng Wang, Yuan Liu, Guying Lin +4
This paper presents a Progressively-connected Light Field network (ProLiF), for the novel view synthesis of complex forward-facing scenes. ProLiF encodes a 4D light field, which al…