FA-ResNet: Feature affine residual network for large-scale point cloud segmentation-Reference-Cited by-同舟云学术

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FA-ResNet: Feature affine residual network for large-scale point cloud segmentation

Published:2023-04 Issue: Volume:118 Page:103259
ISSN:1569-8432
Container-title:International Journal of Applied Earth Observation and Geoinformation
language:en
Short-container-title:International Journal of Applied Earth Observation and Geoinformation

Author:

Zhan Lixin,Li Wei,Min Weidong^ORCID

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Computers in Earth Sciences,Earth-Surface Processes,Global and Planetary Change

Reference33 articles.

1. 3D semantic parsing of large-scale indoor spaces;Armeni,2016

2. Semantickitti: A dataset for semantic scene understanding of LiDAR sequences;Behley,2019

3. SCF-Net: Learning spatial contextual features for large-scale point cloud segmentation;Fan,2021

4. Omni-supervised point cloud segmentation via gradual receptive field component reasoning;Gong,2021

5. Pct: Point cloud transformer;Guo;Comput. Vis. Media,2021

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1. D2T-Net: A dual-domain transformer network exploiting spatial and channel dimensions for semantic segmentation of urban mobile laser scanning point clouds;International Journal of Applied Earth Observation and Geoinformation;2024-08

2. SGK-Net: A Novel Navigation Scene Graph Generation Network;Sensors;2024-07-03

3. Multi-scale learnable key-channel attention network for point cloud classification and segmentation;Applied Soft Computing;2024-07

4. DCSG: data complement pseudo-label refinement and self-guided pre-training for unsupervised person re-identification;The Visual Computer;2024-07-01

5. Large-scale point cloud semantic segmentation via local perception and global descriptor vector;Expert Systems with Applications;2024-07

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