Zobrazeno 1 - 10
of 236
pro vyhledávání: '"Wei Zeyong"'
Autor:
Xue Dongbai, Dun Xiong, Wei Zeyong, Li DongDong, Zhu Jingyuan, Zhang Zhanyi, Wang Zhanshan, Cheng Xinbin
Publikováno v:
Nanophotonics, Vol 13, Iss 8, Pp 1379-1385 (2024)
Collimated flat-top beam shapers primarily consisting of freeform lenses have a wide range of applications and pose challenges in terms of processing and integration when the diameter is less than millimeters. Metasurfaces represent a promising solut
Externí odkaz:
https://doaj.org/article/56b1f787dd69487fab6a3ae37b5f43fe
Autor:
Jiang, Tianshu, Zhang, Chenyu, Zhang, Ruo-Yang, Yu, Yingjuan, Guan, Zhenfu, Wei, Zeyong, Wang, Zhanshan, Cheng, Xinbin, Chan, C. T.
The hybrid skin-topological effect (HSTE) has recently been proposed as a mechanism where topological edge states collapse into corner states under the influence of the non-Hermitian skin effect (NHSE). However, directly observing this effect is chal
Externí odkaz:
http://arxiv.org/abs/2411.13221
Autor:
Li, Xin, Li, Peng, Wei, Zeyong, Zhu, Zhe, Wei, Mingqiang, Hou, Junhui, Nan, Liangliang, Qin, Jing, Xie, Haoran, Wang, Fu Lee
Introducing BERT into cross-modal settings raises difficulties in its optimization for handling multiple modalities. Both the BERT architecture and training objective need to be adapted to incorporate and model information from different modalities.
Externí odkaz:
http://arxiv.org/abs/2312.04891
Self-supervised learning is attracting large attention in point cloud understanding. However, exploring discriminative and transferable features still remains challenging due to their nature of irregularity and sparsity. We propose a geometrically an
Externí odkaz:
http://arxiv.org/abs/2303.13100
Autor:
Si, Huajian, Wei, Zeyong, Zhu, Zhe, Chen, Honghua, Liang, Dong, Wang, Weiming, Wei, Mingqiang
Bilateral filter (BF) is a fast, lightweight and effective tool for image denoising and well extended to point cloud denoising. However, it often involves continual yet manual parameter adjustment; this inconvenience discounts the efficiency and user
Externí odkaz:
http://arxiv.org/abs/2210.15950
Autor:
Chen, Zhaowei, Li, Peng, Wei, Zeyong, Chen, Honghua, Xie, Haoran, Wei, Mingqiang, Wang, Fu Lee
We propose GeoGCN, a novel geometric dual-domain graph convolution network for point cloud denoising (PCD). Beyond the traditional wisdom of PCD, to fully exploit the geometric information of point clouds, we define two kinds of surface normals, one
Externí odkaz:
http://arxiv.org/abs/2210.15913
Low-overlap regions between paired point clouds make the captured features very low-confidence, leading cutting edge models to point cloud registration with poor quality. Beyond the traditional wisdom, we raise an intriguing question: Is it possible
Externí odkaz:
http://arxiv.org/abs/2207.00826
Autor:
Wei, Mingqiang, Wei, Zeyong, Zhou, Haoran, Hu, Fei, Si, Huajian, Chen, Zhilei, Zhu, Zhe, Qiu, Jingbo, Yan, Xuefeng, Guo, Yanwen, Wang, Jun, Qin, Jing
Convolution on 3D point clouds is widely researched yet far from perfect in geometric deep learning. The traditional wisdom of convolution characterises feature correspondences indistinguishably among 3D points, arising an intrinsic limitation of poo
Externí odkaz:
http://arxiv.org/abs/2206.04665
The shape of circle is one of fundamental geometric primitives of man-made engineering objects. Thus, extraction of circles from scanned point clouds is a quite important task in 3D geometry data processing. However, existing circle extraction method
Externí odkaz:
http://arxiv.org/abs/2204.00920
Reflecting light to a pre-determined non-specular direction is an important ability of metasurfaces, which is the basis for a wide range of applications (e.g., beam steering/splitting and imaging). However, anomalous reflection with 100% efficiency h
Externí odkaz:
http://arxiv.org/abs/2111.07232