PointClustering: Unsupervised Point Cloud Pre-training using Transformation Invariance in Clustering-Reference-Cited by-同舟云学术

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PointClustering: Unsupervised Point Cloud Pre-training using Transformation Invariance in Clustering

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:

Long Fuchen¹,Yao Ting¹,Qiu Zhaofan¹,Li Lusong¹,Mei Tao¹

Affiliation:

1. HiDream.ai Inc.,JD Explore Academy,Beijing,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10203037/10203050/10205041.pdf?arnumber=10205041

Reference75 articles.

1. A Large-Scale Study on Unsuper-vised Spatiotemporal Representation Learning;feichtenhofer;CVPR,2021

2. Repre-sentation Learning with Contrastive Predictive Coding;van den oord;NeurIPS,2018

3. A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise;ester;SIGKDD,1996

4. Revisiting Point Cloud Classification: A New Benchmark Dataset and Classification Model on Real-World Data

5. Unsu-pervised Representation Learning by Predicting Image Rotations;gidaris;ICLRE,2018

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A point cloud self-learning network based on contrastive learning for classification and segmentation;The Visual Computer;2024-01-23

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