Results 21 to 30 of about 5,548,528 (274)
Graph-Guided Deformation for Point Cloud Completion [PDF]
IEEE Robotics and Automation Letters, 2021 RAL with IROS ...
Jieqi Shi +3 more
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Attention-Enhanced Feature-Based Point Cloud Completion Network for Precision Parts [PDF]
SensorsWhen acquiring point cloud data of precision parts using 3D scanning devices, occlusion or equipment limitations often lead to sparse and incomplete data, resulting in the distortion or loss of key geometric features.
Hongfei Zu +5 more
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Learning Geometric Transformation for Point Cloud Completion
International Journal of Computer Vision, 2023 Point cloud completion aims to estimate the missing shape from a partial point cloud. Existing encoder-decoder based generative models usually reconstruct the complete point cloud from the learned distribution of the shape prior, which may lead to ...
Shengping Zhang +6 more
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Generative adversarial networks for high-fidelity 3D point cloud completion [PDF]
Scientific Reports3D point clouds are essential for representing geometric structures in various fields such as autonomous driving and virtual reality. However, real-world data often suffers from incompleteness due to occlusions and noise, and existing completion methods ...
Di Zhao +3 more
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Enhancing the performance of point cloud completion assisted with tactile information
EURASIP Journal on Image and Video ProcessingPoint cloud completion is a crucial task in the field of 3D imaging and is becoming a current research hotspot. However, traditional point cloud completion methods often fail to accurately restore the local details of objects due to the lack of detailed ...
Ming Lu +7 more
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View-Guided Point Cloud Completion [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 This paper presents a view-guided solution for the task of point cloud completion. Unlike most existing methods directly inferring the missing points using shape priors, we address this task by introducing ViPC (view-guided point cloud completion) that takes the missing crucial global structure information from an extra single-view image. By leveraging
Xuancheng Zhang +7 more
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Temporal Point Cloud Completion With Pose Disturbance [PDF]
IEEE Robotics and Automation Letters, 2022 Point clouds collected by real-world sensors are always unaligned and sparse, which makes it hard to reconstruct the complete shape of object from a single frame of data. In this work, we manage to provide complete point clouds from sparse input with pose disturbance by limited translation and rotation.
Jieqi Shi +4 more
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HSPC-Net: A hierarchical shape-preserving completion network for machine part point cloud completion [PDF]
PLoS ONEYuchao Jiang, Honghui Fan, Hongjin Zhu
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HyperPocket: Generative Point Cloud Completion
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022 Scanning real-life scenes with modern registration devices typically give incomplete point cloud representations, mostly due to the limitations of the scanning process and 3D occlusions. Therefore, completing such partial representations remains a fundamental challenge of many computer vision applications.
Przemyslaw Spurek +7 more
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Hyperspherical Embedding for Point Cloud Completion
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023 Most real-world 3D measurements from depth sensors are incomplete, and to address this issue the point cloud completion task aims to predict the complete shapes of objects from partial observations. Previous works often adapt an encoder-decoder architecture, where the encoder is trained to extract embeddings that are used as inputs to generate ...
Junming Zhang +3 more
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