Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Zhu, Lifa"'
Great progress has been made in point cloud classification with learning-based methods. However, complex scene and sensor inaccuracy in real-world application make point cloud data suffer from corruptions, such as occlusion, noise and outliers. In th
Externí odkaz:
http://arxiv.org/abs/2210.15514
In feature-learning based point cloud registration, the correct correspondence construction is vital for the subsequent transformation estimation. However, it is still a challenge to extract discriminative features from point cloud, especially when t
Externí odkaz:
http://arxiv.org/abs/2201.12094
Autor:
Pan, Liang, Wu, Tong, Cai, Zhongang, Liu, Ziwei, Yu, Xumin, Rao, Yongming, Lu, Jiwen, Zhou, Jie, Xu, Mingye, Luo, Xiaoyuan, Fu, Kexue, Gao, Peng, Wang, Manning, Wang, Yali, Qiao, Yu, Zhou, Junsheng, Wen, Xin, Xiang, Peng, Liu, Yu-Shen, Han, Zhizhong, Yan, Yuanjie, An, Junyi, Zhu, Lifa, Lin, Changwei, Liu, Dongrui, Li, Xin, Gómez-Fernández, Francisco, Wang, Qinlong, Yang, Yang
As real-scanned point clouds are mostly partial due to occlusions and viewpoints, reconstructing complete 3D shapes based on incomplete observations becomes a fundamental problem for computer vision. With a single incomplete point cloud, it becomes t
Externí odkaz:
http://arxiv.org/abs/2112.12053
The main goal of point cloud registration in Multi-View Partial (MVP) Challenge 2021 is to estimate a rigid transformation to align a point cloud pair. The pairs in this competition have the characteristics of low overlap, non-uniform density, unrest
Externí odkaz:
http://arxiv.org/abs/2110.09129
Autor:
Zhu, Lifa, Liu, Dongrui, Lin, Changwei, Yan, Rui, Gómez-Fernández, Francisco, Yang, Ninghua, Feng, Ziyong
3D point cloud registration is a fundamental task in robotics and computer vision. Recently, many learning-based point cloud registration methods based on correspondences have emerged. However, these methods heavily rely on such correspondences and m
Externí odkaz:
http://arxiv.org/abs/2107.02583
Electron tomography (ET) allows high-resolution reconstructions of macromolecular complexes at nearnative state. Cellular structures segmentation in the reconstruction data from electron tomographic images is often required for analyzing and visualiz
Externí odkaz:
http://arxiv.org/abs/1811.11729
Publikováno v:
In Nutrition Research August 2021 92:49-61
