Search Results for author: Shiqing Xin

Found 3 papers, 2 papers with code

Laplacian2Mesh: Laplacian-Based Mesh Understanding

1 code implementation1 Feb 2022 Qiujie Dong, Zixiong Wang, Junjie Gao, Shuangmin Chen, Zhenyu Shu, Shiqing Xin

Geometric deep learning has sparked a rising interest in computer graphics to perform shape understanding tasks, such as shape classification and semantic segmentation on three-dimensional (3D) geometric surfaces.

Semantic Segmentation Surface Reconstruction

Neural-IMLS: Learning Implicit Moving Least-Squares for Surface Reconstruction from Unoriented Point Clouds

no code implementations9 Sep 2021 Zixiong Wang, Pengfei Wang, Qiujie Dong, Junjie Gao, Shuangmin Chen, Shiqing Xin, Changhe Tu, Wenping Wang

Instead of explicitly learning priors with the ground-truth signed distance values, our method learns the underlying SDF from raw point clouds in a self-supervised fashion by minimizing the loss between a couple of SDFs, one obtained by the implicit moving least-square function (IMLS) and the other by our neural network, where the gradients of our predictor define the tangent bundle that facilitates the computation of IMLS.

Surface Reconstruction

SEG-MAT: 3D Shape Segmentation Using Medial Axis Transform

1 code implementation22 Oct 2020 Cheng Lin, Lingjie Liu, Changjian Li, Leif Kobbelt, Bin Wang, Shiqing Xin, Wenping Wang

Segmenting arbitrary 3D objects into constituent parts that are structurally meaningful is a fundamental problem encountered in a wide range of computer graphics applications.

Cannot find the paper you are looking for? You can Submit a new open access paper.