Deep Positional and Relational Feature Learning for Rotation-Invariant Point Cloud Analysis

18 November 2020

Papers citing "Deep Positional and Relational Feature Learning for Rotation-Invariant Point Cloud Analysis"

8 / 8 papers shown

Title
Cloud-RAIN: Point Cloud Analysis with Reflectional Invariance Yiming Cui Lecheng Ruan Hang Dong Qiang Li Zhongming Wu T. Zeng Fengyu Fan 3DPC 35 0 0 13 May 2023
CRIN: Rotation-Invariant Point Cloud Analysis and Rotation Estimation via Centrifugal Reference Frame Yujing Lou Zelin Ye Yang You Nianjuan Jiang Jiangbo Lu Weiming Wang Lizhuang Ma Cewu Lu 3DPC 44 7 0 06 Mar 2023
General Rotation Invariance Learning for Point Clouds via Weight-Feature Alignment Liang Xie Yibo Yang Wenxiao Wang Binbin Lin Deng Cai Xiaofei He Ronghua Liang 3DPC 24 2 0 20 Feb 2023
A Simple Strategy to Provable Invariance via Orbit Mapping Kanchana Vaishnavi Gandikota Jonas Geiping Zorah Lähner Adam Czapliñski Michael Moeller AAML 3DPC 18 3 0 24 Sep 2022
Frame Averaging for Equivariant Shape Space Learning Matan Atzmon Koki Nagano Sanja Fidler S. Khamis Y. Lipman FedML 33 13 0 03 Dec 2021
You Only Hypothesize Once: Point Cloud Registration with Rotation-equivariant Descriptors Haiping Wang Yuan Liu Zhen Dong Wenping Wang 3DPC 27 124 0 01 Sep 2021
SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration Sheng Ao Qingyong Hu Bo Yang Andrew Markham Yulan Guo 3DPC OOD 42 272 0 24 Nov 2020
SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters Yifan Xu Tianqi Fan Mingye Xu Long Zeng Yu Qiao 3DV 3DPC 152 769 0 30 Mar 2018