Uncertainty-Guided Contrastive Learning for Weakly Supervised Point Cloud Segmentation-Reference-Cited by-同舟云学术

Uncertainty-Guided Contrastive Learning for Weakly Supervised Point Cloud Segmentation

Published:2024 Issue: Volume:62 Page:1-13
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Yao Baochen¹^ORCID,Dong Li¹^ORCID,Qiu Xiaojie²,Song Kangkang³^ORCID,Yan Diqun¹^ORCID,Peng Chengbin¹^ORCID

Affiliation:

1. College of Information Science and Engineering and the Key Laboratory of Mobile Network Application Technology of Zhejiang Province, Ningbo University, Ningbo, China

2. Zhejiang Cowain Automation Technology Company Ltd., Ningbo, China

3. Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China

Funder

Ningbo Science and Technology Innovation Project

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/36/10354519/10560026.pdf?arnumber=10560026

Reference59 articles.

1. Indoor Point Cloud Segmentation Using Iterative Gaussian Mapping and Improved Model Fitting

2. Semantic Segmentation of Terrestrial Laser Scanning Point Clouds Using Locally Enhanced Image-Based Geometric Representations

3. A Dual Attention Neural Network for Airborne LiDAR Point Cloud Semantic Segmentation

4. Semantic Segmentation of Spectral LiDAR Point Clouds Based on Neural Architecture Search

5. Meta Architecture for Point Cloud Analysis

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