Self-Supervised Pre-Training Boosts Semantic Scene Segmentation on LiDAR data
Author:
Affiliation:
1. Universitat de Barcelona,Dept. de Matemàtiques i Informàtica,Barcelona
2. Cartographic and Geological Institute of Catalonia,Barcelona
Funder
Generalitat de Catalunya
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10215492/10215533/10216191.pdf?arnumber=10216191
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1. Linking Points With Labels in 3D: A Review of Point Cloud Semantic Segmentation
2. Pointnet++: Deep hierarchical feature learning on point sets in a metric space;qi;Advances in neural information processing systems,2017
3. Object Segmentation of Cluttered Airborne LiDAR Point Clouds
4. Point Transformer
5. Semdedup: Data-efficient learning at web-scale through semantic deduplication;abbas,2023
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. Effective Training and Inference Strategies for Point Classification in LiDAR Scenes;Remote Sensing;2024-06-13
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