Efficient 3D Scene Semantic Segmentation via Active Learning on Rendered 2D Images
Author:
Affiliation:
1. Institute of Automation, Chinese Academy of Sciences, Beijing, China
Funder
National Natural Science Foundation of China
Beijing Natural Science Foundation
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Graphics and Computer-Aided Design,Software
Link
http://xplorestaging.ieee.org/ielx7/83/9991910/10158507.pdf?arnumber=10158507
Reference47 articles.
1. A new weakly supervised approach for ALS point cloud semantic segmentation
2. Towards weakly supervised semantic segmentation in 3D graph-structured point clouds of wild scenes;wang;Proc BMVC,2019
3. SQN: Weakly-supervised semantic segmentation of large-scale 3D point clouds;hu;arXiv 2104 04891,2021
4. xMUDA: Cross-Modal Unsupervised Domain Adaptation for 3D Semantic Segmentation
5. RGB-D Semantic Segmentation and Label-Oriented Voxelgrid Fusion for Accurate 3D Semantic Mapping
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2. OIPNet: Multimodal Network with Orthogonal Information Processing for Semantic Segmentation in Indoor Scenes;International Journal of Pattern Recognition and Artificial Intelligence;2024-01-20
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