Zobrazeno 1 - 10
of 85
pro vyhledávání: '"Xian, Chuhua"'
Reduced-order simulation is an emerging method for accelerating physical simulations with high DOFs, and recently developed neural-network-based methods with nonlinear subspaces have been proven effective in diverse applications as more concise subsp
Externí odkaz:
http://arxiv.org/abs/2409.03807
Autor:
Zhang, Zitian, Xian, Chuhua
In this paper, we aim to solve the problem of consistent depth prediction in complex scenes under various illumination conditions. The existing indoor datasets based on RGB-D sensors or virtual rendering have two critical limitations - sparse depth m
Externí odkaz:
http://arxiv.org/abs/2112.08006
Limited by the cost and technology, the resolution of depth map collected by depth camera is often lower than that of its associated RGB camera. Although there have been many researches on RGB image super-resolution (SR), a major problem with depth m
Externí odkaz:
http://arxiv.org/abs/2011.11865
Using the raw data from consumer-level RGB-D cameras as input, we propose a deep-learning based approach to efficiently generate RGB-D images with completed information in high resolution. To process the input images in low resolution with missing re
Externí odkaz:
http://arxiv.org/abs/2002.05067
Publikováno v:
In Journal of Information Security and Applications May 2022 66
Akademický článek
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Publikováno v:
In Computers & Graphics November 2021 100:43-53
Autor:
Xian, Chuhua1 (AUTHOR), Zhang, Jun1 (AUTHOR), Yang, Wenhao2 (AUTHOR), Zhang, Yunbo2,3 (AUTHOR) ywzeie@rit.edu
Publikováno v:
Journal of Intelligent Manufacturing. Jun2024, Vol. 35 Issue 5, p2119-2135. 17p.
Publikováno v:
In Computers & Graphics February 2021 94:43-51
Handle-driven deformation based on linear blending is widely used in many applications because of its merits in intuitiveness, efficiency and easiness of implementation. We provide a meshfree method to compute the smooth weights of linear blending fo
Externí odkaz:
http://arxiv.org/abs/1507.02800