34 citations · 139 across the 20 of their papers we have counts for
26 papers
HSurf-Net: Normal Estimation for 3D Point Clouds by Learning Hyper Surfaces
Qing Li, Yu-Shen Liu, Jin-San Cheng +3
We propose a novel normal estimation method called HSurf-Net, which can accurately predict normals from point clouds with noise and density variations. Previous methods focus on le…
ContinuityLearner: Geometric Continuity Feature Learning for Lane Segmentation
Haoyu Fang, Jing Zhu, Yi Fang
Lane segmentation is a challenging issue in autonomous driving system designing because lane marks show weak textural consistency due to occlusion or extreme illumination but stron…
Learn to Learn Metric Space for Few-Shot Segmentation of 3D Shapes
Xiang Li, Lingjing Wang, Yi Fang
Recent research has seen numerous supervised learning-based methods for 3D shape segmentation and remarkable performance has been achieved on various benchmark datasets. These supe…
G-VAE, a Geometric Convolutional VAE for ProteinStructure Generation
Hao Huang, Boulbaba Ben Amor, Xichan Lin +2
Analyzing the structure of proteins is a key part of understanding their functions and thus their role in biology at the molecular level. In addition, design new proteins in a meth…
Residual Networks as Flows of Velocity Fields for Diffeomorphic Time Series Alignment
Hao Huang, Boulbaba Ben Amor, Xichan Lin +2
Non-linear (large) time warping is a challenging source of nuisance in time-series analysis. In this paper, we propose a novel diffeomorphic temporal transformer network for both p…
3D Meta-Registration: Learning to Learn Registration of 3D Point Clouds
Lingjing Wang, Yu Hao, Xiang Li +1
Deep learning-based point cloud registration models are often generalized from extensive training over a large volume of data to learn the ability to predict the desired geometric…