Global Hierarchical Attention for 3D Point Cloud Analysis

7 August 2022

Papers citing "Global Hierarchical Attention for 3D Point Cloud Analysis"

7 / 7 papers shown

Title
Mix3D: Out-of-Context Data Augmentation for 3D Scenes Alexey Nekrasov Jonas Schult Or Litany Bastian Leibe Francis Engelmann 3DPC 142 154 0 05 Oct 2021
H-Transformer-1D: Fast One-Dimensional Hierarchical Attention for Sequences Zhenhai Zhu Radu Soricut 95 41 0 25 Jul 2021
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 283 5,723 0 29 Apr 2021
Self-Supervised Pretraining of 3D Features on any Point-Cloud Zaiwei Zhang Rohit Girdhar Armand Joulin Ishan Misra 3DPC 120 267 0 07 Jan 2021
Big Bird: Transformers for Longer Sequences Manzil Zaheer Guru Guruganesh Kumar Avinava Dubey Joshua Ainslie Chris Alberti ... Philip Pham Anirudh Ravula Qifan Wang Li Yang Amr Ahmed VLM 249 1,982 0 28 Jul 2020
SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters Yifan Xu Tianqi Fan Mingye Xu Long Zeng Yu Qiao 3DV 3DPC 150 760 0 30 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 219 13,886 0 02 Dec 2016