Results 11 to 20 of about 309,652 (283)
3D Point Cloud Semantic Segmentation System Based on Lightweight FPConv
IEEE Access, 2023 In this paper, we proposed a 3D point cloud semantic segmentation system based on lightweight FPConv. In 3D point cloud mapping, data is depicted in a 3D space to represent 3D imagery data. These maps are collected through direct measurements; all points
Yu-Cheng Fan +4 more
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Panicle-3D: Efficient Phenotyping Tool for Precise Semantic Segmentation of Rice Panicle Point Cloud
Plant Phenomics, 2021 The automated measurement of crop phenotypic parameters is of great significance to the quantitative study of crop growth. The segmentation and classification of crop point cloud help to realize the automation of crop phenotypic parameter measurement. At
Liang Gong +7 more
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Equivariant Point Network for 3D Point Cloud Analysis [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 Features that are equivariant to a larger group of symmetries have been shown to be more discriminative and powerful in recent studies [4], [40], [5]. However, higher-order equivariant features often come with an exponentially-growing computational cost. Furthermore, it remains relatively less explored how rotation-equivariant features can be leveraged
Haiwei Chen +4 more
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Research on Deformation Monitoring of Invert Uplifts in Soft Rock Tunnels Based on 3D Laser Scanning
Applied Sciences, 2023 The soft surrounding rock in tunnels has the characteristics of low strength, easy softening after soaking, and poor self-stability, which makes the inverted arch structure in soft rock tunnels prone to uplift deformations.
Enchao Zhang, Pengtao Niu, Jianfei Liu
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3D Point Cloud Simplification Based on k-Nearest Neighbor and Clustering
Advances in Multimedia, 2020 While the reconstruction of 3D objects is increasingly used today, the simplification of 3D point cloud, however, becomes a substantial phase in this process of reconstruction.
Abdelaaziz Mahdaoui, El Hassan Sbai
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Quality Judgment of 3D Face Point Cloud Based on Feature Fusion
IEEE Access, 2022 With the rapid development of face recognition, the 3D face has gradually become the mainstream, 3D face point cloud quality judgment was an important process.
Gong Gao, Hong Liu, Hongyu Yang
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Generating 3D Adversarial Point Clouds [PDF]
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 Deep neural networks are known to be vulnerable to adversarial examples which are carefully crafted instances to cause the models to make wrong predictions. While adversarial examples for 2D images and CNNs have been extensively studied, less attention has been paid to 3D data such as point clouds.
Xiang, Chong, Qi, Charles R., Li, Bo
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Deep Magnification-Flexible Upsampling Over 3D Point Clouds [PDF]
IEEE Transactions on Image Processing, 2021 15 pages, 16 figures, 6 ...
Yue Qian, Junhui Hou, Sam Kwong, Ying He
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3D‐FEGNet: A feature enhanced point cloud generation network from a single image
IET Computer Vision, 2023 Deep learning‐based single view 3D reconstruction is a hot topic in computer vision. However, predicting a more realistic 3D point cloud from a single image is an ill‐posed problem.
Ende Wang +4 more
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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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