Zobrazeno 1 - 10
of 64
pro vyhledávání: '"Belen Masia"'
Autor:
Sandra Malpica, Belen Masia, Laura Herman, Gordon Wetzstein, David M. Eagleman, Diego Gutierrez, Zoya Bylinskii, Qi Sun
Publikováno v:
PLoS ONE, Vol 17, Iss 3 (2022)
Time perception is fluid and affected by manipulations to visual inputs. Previous literature shows that changes to low-level visual properties alter time judgments at the millisecond-level. At longer intervals, in the span of seconds and minutes, hig
Externí odkaz:
https://doaj.org/article/c3fc3a0f425941b4a0baec104cc37123
Publikováno v:
Visual Informatics, Vol 1, Iss 1, Pp 65-79 (2017)
Transient imaging has recently made a huge impact in the computer graphics and computer vision fields. By capturing, reconstructing, or simulating light transport at extreme temporal resolutions, researchers have proposed novel techniques to show mov
Externí odkaz:
https://doaj.org/article/23197eb7b3054389a584969b26f44ac3
Publikováno v:
IEEE Transactions on Visualization and Computer Graphics. 29:2446-2455
Publikováno v:
Computers & Graphics. 106:200-209
Publikováno v:
Zaguán. Repositorio Digital de la Universidad de Zaragoza
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Virtual reality (VR) is rapidly growing, with the potential to change the way we create and consume content. In VR, users integrate multimodal sensory information they receive, to create a unified perception of the virtual world. In this survey, we r
Publikováno v:
ACM SIGGRAPH 2022 Posters.
Autor:
Sandra Malpica, Ana Serrano, Julia Guerrero-Viu, Daniel Martin, Edurne Bernal, Diego Gutierrez, Belen Masia
Publikováno v:
ACM SIGGRAPH 2022 Posters.
Publikováno v:
Jornada de Jóvenes Investigadores del I3A. 10
We present a deep learning approach to visual attention prediction in 360º videos. We resort to recurrent neural networks to model the inherent spatio-temporal features of visual behavior, while tailoring our model to the particularities of 360º co
Akademický článek
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Publikováno v:
Zaguán. Repositorio Digital de la Universidad de Zaragoza
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Understanding and modeling the dynamics of human gaze behavior in 360° environments is crucial for creating, improving, and developing emerging virtual reality applications. However, recruiting human observers and acquiring enough data to analyze th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::82a81bfe44f827b339568f866abd73de
http://zaguan.unizar.es/record/117683
http://zaguan.unizar.es/record/117683