No Pain, Big Gain: Classify Dynamic Point Cloud Sequences with Static Models by Fitting Feature-level Space-time Surfaces

21 March 2022

Papers citing "No Pain, Big Gain: Classify Dynamic Point Cloud Sequences with Static Models by Fitting Feature-level Space-time Surfaces"

8 / 8 papers shown

Title
PvNeXt: Rethinking Network Design and Temporal Motion for Point Cloud Video Recognition Jie Wang Tingfa Xu Lihe Ding Xinjie Zhang Long Bai Jianan Li 3DPC 50 0 0 07 Apr 2025
PRENet: A Plane-Fit Redundancy Encoding Point Cloud Sequence Network for Real-Time 3D Action Recognition Shenglin He Xiaoyang Qu Jiguang Wan Guokuan Li Changsheng Xie Jianzong Wang 3DPC 3DH 33 1 0 11 May 2024
PSTNet: Point Spatio-Temporal Convolution on Point Cloud Sequences Hehe Fan Xin Yu Yuhang Ding Yi Yang Mohan S. Kankanhalli 3DPC 112 108 0 27 May 2022
Weakly Supervised Learning of Rigid 3D Scene Flow Zan Gojcic Or Litany A. Wieser Leonidas J. Guibas Tolga Birdal 3DPC 96 91 0 17 Feb 2021
FLOT: Scene Flow on Point Clouds Guided by Optimal Transport Gilles Puy Alexandre Boulch Renaud Marlet 3DPC OT 107 161 0 22 Jul 2020
SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters Yifan Xu Tianqi Fan Mingye Xu Long Zeng Yu Qiao 3DV 3DPC 142 760 0 30 Mar 2018
Depth Pooling Based Large-scale 3D Action Recognition with Convolutional Neural Networks Pichao Wang W. Li Zhimin Gao Chang-Fu Tang P. Ogunbona 3DV 101 137 0 17 Mar 2018
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation C. Qi Hao Su Kaichun Mo Leonidas J. Guibas 3DH 3DPC 3DV PINN 210 13,886 0 02 Dec 2016