Results 21 to 30 of about 7,018 (281)

Semantic Segmentation of Heavy Construction Equipment Based on Point Cloud Data [PDF]

Buildings
Most of the currently developed 3D point cloud data-based object recognition algorithms have been designed for small indoor objects, posing challenges when applied to large-scale 3D point cloud data in outdoor construction sites.
Suyeul Park, Seok Kim
doaj   +2 more sources

Few-shot 3D Point Cloud Semantic Segmentation [PDF]

2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021
Many existing approaches for 3D point cloud semantic segmentation are fully supervised. These fully supervised approaches heavily rely on large amounts of labeled training data that are difficult to obtain and cannot segment new classes after training.
Na Zhao 0004, Tat-Seng Chua, Gim Hee Lee
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Compositional Semantic Mix for Domain Adaptation in Point Cloud Segmentation [PDF]

, 2023
Deep-learning models for 3D point cloud semantic segmentation exhibit limited generalization capabilities when trained and tested on data captured with different sensors or in varying environments due to domain shift.
Fabio Poiesi, Giuseppe Fiameni, Fiameni, Giuseppe, Sebe, Nicu, Ricci, Elisa, Cristiano Saltori, Elisa Ricci, Poiesi, Fabio, Nicu Sebe, Saltori, Cristiano, Fabio Galasso, Galasso, Fabio   +11 more
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Point attention network for semantic segmentation of 3D point clouds [PDF]

Pattern Recognition, 2020
Submitted to a ...
Mingtao Feng, Liang Zhang 0010, Xuefei Lin, Syed Zulqarnain Gilani, Ajmal Mian   +4 more
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SS-IPLE: Semantic Segmentation of Electric Power Corridor Scene and Individual Power Line Extraction From UAV-Based Lidar Point Cloud

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
Key objects’ semantic segmentation and power line extraction from the electric power corridor point cloud are critical steps in power line inspection.
Xiuning Liu, Feng Shuang, Yong Li, Liqiang Zhang, Xingwen Huang, Jianchuang Qin   +5 more
doaj   +1 more source

Semantic segmentation of surface from lidar point cloud [PDF]

Multimedia Tools and Applications, 2020
In the field of SLAM (Simultaneous Localization And Mapping) for robot navigation, mapping the environment is an important task. In this regard the Lidar sensor can produce near accurate 3D map of the environment in the format of point cloud, in real time.
Aritra Mukherjee, Sourya Dipta Das, Jasorsi Ghosh, Ananda S. Chowdhury, Sanjoy Kumar Saha 0001   +4 more
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3D point cloud semantic segmentation: state of the art and challenges

工程科学学报, 2023
Decrease in the cost of acquiring 3D point cloud data coupled with the rapid advancements in GPU computing power have resulted in an increased demand for 3D point cloud semantic segmentation in numerous 3D visual applications, including but not limited ...
Yixian WANG, Yufan HU, Qingqun KONG, Hui ZENG, Lixin ZHANG, Bin FAN   +5 more
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Deep-Learning-Based Semantic Segmentation Approach for Point Clouds of Extra-High-Voltage Transmission Lines

Remote Sensing, 2023
The accurate semantic segmentation of point cloud data is the basis for their application in the inspection of extra high-voltage transmission lines (EHVTL).
Hao Yu, Zhengyang Wang, Qingjie Zhou, Yuxuan Ma, Zhuo Wang, Huan Liu, Chunqing Ran, Shengli Wang, Xinghua Zhou, Xiaobo Zhang   +9 more
doaj   +1 more source

Indoor Scene Segmentation Model Using Three-Dimensional Point Cloud Based on Super Point Graph Network [PDF]

Jisuanji gongcheng, 2021
The samples of the existing current point cloud datasets are unbalanced, and PointNet can not effectively utilize the neighborhood information of the point cloud.To address the problem, a three-dimensional scene segmentation method using point cloud is ...
HUO Zhanqiang, WANG Yongjie, LUO Fen, QIAO Yingxu
doaj   +1 more source

On Adversarial Robustness of Point Cloud Semantic Segmentation

2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2023
Recent research efforts on 3D point cloud semantic segmentation (PCSS) have achieved outstanding performance by adopting neural networks. However, the robustness of these complex models have not been systematically analyzed. Given that PCSS has been applied in many safety-critical applications like autonomous driving, it is important to fill this ...
Jiacen Xu, Zhe Zhou 0001, Boyuan Feng, Yufei Ding 0001, Zhou Li 0001   +4 more
openaire   +2 more sources