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pro vyhledávání: '"Huang, Kaining"'
Autor:
Zhang, Tianyi, Zhi, Weiming, Huang, Kaining, Mangelson, Joshua, Barbalata, Corina, Johnson-Roberson, Matthew
Water caustics are commonly observed in seafloor imaging data from shallow-water areas. Traditional methods that remove caustic patterns from images often rely on 2D filtering or pre-training on an annotated dataset, hindering the performance when ge
Externí odkaz:
http://arxiv.org/abs/2407.10318
DarkGS: Learning Neural Illumination and 3D Gaussians Relighting for Robotic Exploration in the Dark
Publikováno v:
IEEE/RSJ International Conference on Intelligent Robots and Systems 2024
Humans have the remarkable ability to construct consistent mental models of an environment, even under limited or varying levels of illumination. We wish to endow robots with this same capability. In this paper, we tackle the challenge of constructin
Externí odkaz:
http://arxiv.org/abs/2403.10814
Publikováno v:
In Journal of Visual Communication and Image Representation July 2020 70
Publikováno v:
In Signal Processing: Image Communication May 2020 84
Akademický článek
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Publikováno v:
Journal of Visual Communication and Image Representation. 70:102740
Human-computer interaction is the way in which humans and machines communicate information. With the rapid development of deep learning technology, the technology of human-computer interaction has also made a corresponding breakthrough. In the past,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e8de64f208dd722fc8bbff497332470a
https://doi.org/10.1016/j.jvcir.2019.102740
https://doi.org/10.1016/j.jvcir.2019.102740
Publikováno v:
Signal Processing: Image Communication. 84:115807
Intelligently tracking objects with varied shapes, color, lighting conditions, and backgrounds is an extremely useful application in many HCI applications, such as human body motion capture, hand gesture recognition, and virtual reality (VR) games. H
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cf91d8e39dcbcdf6911a9400c32264a5
https://doi.org/10.1016/j.image.2020.115807
https://doi.org/10.1016/j.image.2020.115807