Self-supervised Point Cloud Representation Learning via Separating Mixed Shapes

1 September 2021

Papers citing "Self-supervised Point Cloud Representation Learning via Separating Mixed Shapes"

9 / 9 papers shown

Title
SegDA: Maximum Separable Segment Mask with Pseudo Labels for Domain Adaptive Semantic Segmentation Anant Khandelwal 21 1 0 10 Aug 2023
PiPa: Pixel- and Patch-wise Self-supervised Learning for Domain Adaptative Semantic Segmentation Mu Chen Zhedong Zheng Yi Yang Tat-Seng Chua 45 53 0 14 Nov 2022
Walk in the Cloud: Learning Curves for Point Clouds Shape Analysis Tiange Xiang Chaoyi Zhang Yang Song Jianhui Yu Weidong (Tom) Cai 3DPC 138 283 0 04 May 2021
Regularization Strategy for Point Cloud via Rigidly Mixed Sample Dogyoon Lee Jaeha Lee Junhyeop Lee Hyeongmin Lee Minhyeok Lee Sungmin Woo Sangyoun Lee 3DPC 148 74 0 03 Feb 2021
Self-Supervised Pretraining of 3D Features on any Point-Cloud Zaiwei Zhang Rohit Girdhar Armand Joulin Ishan Misra 3DPC 124 268 0 07 Jan 2021
Self-supervised Co-training for Video Representation Learning Tengda Han Weidi Xie Andrew Zisserman SSL 209 308 0 19 Oct 2020
PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding Saining Xie Jiatao Gu Demi Guo C. Qi Leonidas J. Guibas Or Litany 3DPC 141 622 0 21 Jul 2020
Joint 2D-3D-Semantic Data for Indoor Scene Understanding Iro Armeni S. Sax Amir Zamir Silvio Savarese 3DV 3DPC 113 875 0 03 Feb 2017
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation C. Qi Hao Su Kaichun Mo Leonidas J. Guibas 3DH 3DPC 3DV PINN 222 14,099 0 02 Dec 2016