Results 11 to 20 of about 61,541 (298)
Language-Level Semantics-Conditioned 3D Point Cloud Segmentation
Remote SensingIn this work, a language-level Semantics-Conditioned framework for 3D Point cloud segmentation, called SeCondPoint, is proposed, where language-level semantics are introduced to condition the modeling of the point feature distribution, as well as the ...
Bo Liu, Hui Zeng, Qiulei Dong, Zhanyi Hu
doaj +3 more sources
SSPC-Net: Semi-supervised Semantic 3D Point Cloud Segmentation Network [PDF]
AAAI Conference on Artificial Intelligence, 2021 Point cloud semantic segmentation is a crucial task in 3D scene understanding. Existing methods mainly focus on employing a large number of annotated labels for supervised semantic segmentation.
Mingmei Cheng +3 more
semanticscholar +1 more source
Boosting Few-shot 3D Point Cloud Segmentation via Query-Guided Enhancement [PDF]
ACM Multimedia, 2023 Although extensive research has been conducted on 3D point cloud segmentation, effectively adapting generic models to novel categories remains a formidable challenge.
Zhen-Hu Ning +3 more
semanticscholar +1 more source
Weakly Supervised 3D Point Cloud Segmentation via Multi-Prototype Learning [PDF]
IEEE transactions on circuits and systems for video technology (Print), 2022 Addressing the annotation challenge in 3D Point Cloud segmentation has inspired research into weakly supervised learning. Existing approaches mainly focus on exploiting manifold and pseudo-labeling to make use of large unlabeled data points.
Yongyi Su, Xun Xu, Kui Jia
semanticscholar +1 more source
SEMANTIC ENRICHMENT OF 3D POINT CLOUDS USING 2D IMAGE SEGMENTATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 3D point cloud segmentation is computationally intensive due to the lack of inherent structural information and the unstructured nature of the point cloud data, which hinders the identification and connection of neighboring points.
A. Rai +3 more
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PIG-Net: Inception based Deep Learning Architecture for 3D Point Cloud Segmentation [PDF]
Computers & graphics, 2021 Point clouds, being the simple and compact representation of surface geometry of 3D objects, have gained increasing popularity with the evolution of deep learning networks for classification and segmentation tasks.
Sindhu B. Hegde, Shankar Gangisetty
semanticscholar +1 more source
Point attention network for semantic segmentation of 3D point clouds [PDF]
Pattern Recognition, 2020 Submitted to a ...
Mingtao Feng +4 more
openaire +2 more sources
Point Cloud Semantic Segmentation Method Based on Block Feature Fusion [PDF]
Jisuanji gongcheng, 2022 A semantic segmentation method integrating block features is proposed to reduce the computational complexity of semantic segmentation of multi-class 3D objects in outdoor large-scale point cloud scenes.The square grid segmentation method is used to ...
GAO Qingji, LI Tianhao, XING Zhiwei, LIU Peipei
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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 +5 more
doaj +1 more source
Interactive Object Segmentation in 3D Point Clouds
2023 IEEE International Conference on Robotics and Automation (ICRA), 2023 We propose an interactive approach for 3D instance segmentation, where users can iteratively collaborate with a deep learning model to segment objects in a 3D point cloud directly. Current methods for 3D instance segmentation are generally trained in a fully-supervised fashion, which requires large amounts of costly training labels, and does not ...
Theodora Kontogianni +3 more
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