GeoMAE: Masked Geometric Target Prediction for Self-supervised Point Cloud Pre-Training-Reference-Cited by-同舟云学术

GeoMAE: Masked Geometric Target Prediction for Self-supervised Point Cloud Pre-Training

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Author:

Tian Xiaoyu¹,Ran Haoxi²,Wang Yue³,Zhao Hang¹

Affiliation:

1. IIIS, Tsinghua University

2. CMU

3. NVIDIA

Funder

National Key R&D Program of China

Publisher

IEEE

Link

Reference59 articles.

1. Peco: Perceptual codebook for bert pre-training of vision transformers;dong;ArXiv Preprint,2021

2. Class-balanced grouping and sampling for point cloud 3d object detection;zhu;ArXiv Preprint,2019

3. Bert: Pre-training of deep bidirectional transformers for language understanding;devlin;ArXiv Preprint,2018

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2. Self-Supervised Learning of 3D Point Clouds: A Survey;2024 36th Chinese Control and Decision Conference (CCDC);2024-05-25

4. MAELi: Masked Autoencoder for Large-Scale LiDAR Point Clouds;2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV);2024-01-03