Results 41 to 50 of about 381,180 (306)
SymmCompletion: High-Fidelity and High-Consistency Point Cloud Completion with Symmetry Guidance [PDF]
AAAI Conference on Artificial IntelligencePoint cloud completion aims to recover a complete point shape from a partial point cloud. Although existing methods can form satisfactory point clouds in global completeness, they often lose the original geometry details and face the problem of geometric
Hongyu Yan +4 more
semanticscholar +1 more source
Morphing and Sampling Network for Dense Point Cloud Completion [PDF]
AAAI Conference on Artificial Intelligence, 2019 3D point cloud completion, the task of inferring the complete geometric shape from a partial point cloud, has been attracting attention in the community. For acquiring high-fidelity dense point clouds and avoiding uneven distribution, blurred details, or
Minghua Liu +4 more
semanticscholar +1 more source
High-Resolution Shape Completion Using Deep Neural Networks for Global Structure and Local Geometry Inference [PDF]
, 2017 We propose a data-driven method for recovering miss-ing parts of 3D shapes. Our method is based on a new deep learning architecture consisting of two sub-networks: a global structure inference network and a local geometry refinement network.
Han, Xiaoguang +4 more
core +2 more sources
2023 IEEE International Conference on Robotics and Automation (ICRA), 2023 In the practical application of point cloud completion tasks, real data quality is usually much worse than the CAD datasets used for training. A small amount of noisy data will usually significantly impact the overall system's accuracy. In this paper, we propose a quality evaluation network to score the point clouds and help judge the quality of the ...
Shi, Jieqi +3 more
openaire +2 more sources
From Noisy Point Clouds to Complete Ear Shapes: Unsupervised Pipeline [PDF]
IEEE Access, 2021 Ears are a particularly difficult region of the human face to model, not only due to the non-rigid deformations existing between shapes but also to the challenges in processing the retrieved data. The first step towards obtaining a good model is to have complete scans in correspondence, but these usually present a higher amount of occlusions, noise and
Filipa Valdeira +3 more
openaire +4 more sources
Grasping unknown objects in clutter by superquadric representation [PDF]
, 2017 © 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new ...
Makhal, Abhijit +2 more
core +2 more sources
Point Cloud Completion: A Survey [PDF]
IEEE Transactions on Visualization and Computer GraphicsPoint cloud completion is the task of producing a complete 3D shape given an input of a partial point cloud. It has become a vital process in 3D computer graphics, vision and applications such as autonomous driving, robotics, and augmented reality. These applications often rely on the presence of a complete 3D representation of the environment.
Keneni W. Tesema +4 more
openaire +3 more sources
Sparse-to-Dense Multi-Encoder Shape Completion of Unstructured Point Cloud
IEEE Access, 2020 Unstructured point clouds are a representative shape representation of real-world scenes in 3D vision and graphics. Incompletion inevitably arises, due to the way the set of unorganized points is captured, e.g., as fusion of depth images, merged laser ...
Yanjun Peng +6 more
doaj +1 more source
Two-branch Shape Complement Network for Feature Missing Splicing Mode
Journal of Harbin University of Science and Technology, 2023 Aiming at the problem of low fidelity of reverse geometric reconstruction of bowl-shaped cultural relics model due to the missing fragments , a 3D point cloud shape completion network based on double discrimination decoder is proposed.
SUNJin, MAHaotian, LEIZhenting, LIANGLi
doaj +1 more source
Multi-Branch and Multi-Scale Point Cloud Completion Network [PDF]
Jisuanji gongchengThis paper proposes a point cloud completion network based on multi-branch multi-scale feature fusion because the existing networks cannot extract high-quality global and local features of point clouds simultaneously and lose point cloud detail and ...
CHEN Xiaolei, WANG Rong
doaj +1 more source