Cloud Transformers: A Universal Approach To Point Cloud Processing Tasks

22 July 2020

Papers citing "Cloud Transformers: A Universal Approach To Point Cloud Processing Tasks"

11 / 11 papers shown

Title
PointWavelet: Learning in Spectral Domain for 3D Point Cloud Analysis Cheng Wen Jia-Li Long B. Yu Dacheng Tao 3DPC 37 7 0 10 Feb 2023
Learning from Mistakes: Self-Regularizing Hierarchical Representations in Point Cloud Semantic Segmentation Elena Camuffo Umberto Michieli Simone Milani 3DPC 24 4 0 26 Jan 2023
3DGTN: 3D Dual-Attention GLocal Transformer Network for Point Cloud Classification and Segmentation Dening Lu K. Gao Qian Xie Linlin Xu Jonathan Li 3DPC ViT 29 4 0 21 Sep 2022
Points to Patches: Enabling the Use of Self-Attention for 3D Shape Recognition Axel Berg Magnus Oskarsson Mark O'Connor 3DPC ViT 27 26 0 08 Apr 2022
3DCTN: 3D Convolution-Transformer Network for Point Cloud Classification Dening Lu Qian Xie Linlin Xu Jonathan Li 3DV 19 68 0 02 Mar 2022
Benchmarking and Analyzing Point Cloud Classification under Corruptions Jiawei Ren Liang Pan Ziwei Liu 3DPC 16 80 0 07 Feb 2022
PartGlot: Learning Shape Part Segmentation from Language Reference Games Juil Koo Ian Huang Panos Achlioptas Leonidas J. Guibas Minhyuk Sung 3DPC 28 28 0 13 Dec 2021
PU-Transformer: Point Cloud Upsampling Transformer Shi Qiu Saeed Anwar Nick Barnes 3DPC ViT 29 51 0 24 Nov 2021
PointMixer: MLP-Mixer for Point Cloud Understanding Jaesung Choe Chunghyun Park François Rameau Jaesik Park In So Kweon 3DPC 39 98 0 22 Nov 2021
SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters Yifan Xu Tianqi Fan Mingye Xu Long Zeng Yu Qiao 3DV 3DPC 152 768 0 30 Mar 2018
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Z. Tu Kaiming He 297 10,216 0 16 Nov 2016