Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Johanna Delanoy"'
Autor:
Cyril Bertheaux, Eliott Zimmermann, Mathis Gazel, Johanna Delanoy, Pierre Raimbaud, Guillaume Lavoué
Publikováno v:
Frontiers in Human Neuroscience, Vol 17 (2024)
IntroductionDesigners know that part of the appreciation of a product comes from the properties of its materials. These materials define the object’s appearance and produce emotional reactions that can influence the act of purchase. Although known
Externí odkaz:
https://doaj.org/article/01a5a6ed5ed14be48f846aefa982b0e2
Autor:
Clément Colin, Corentin Gautier, Diego Vinasco-Alvarez, Johanna Delanoy, Gilles Gesquière, John Samuel, Sylvie Servigne, Éric Boix, Thibault Dupont, Mathieu Livebardon, Valentin Machado, Lorenzo Marnat
Publikováno v:
M@ppemonde, Vol 135
Cet article présente la plateforme UD-SV (Urban Data Services and Visualization) développée au laboratoire LIRIS. UD-SV regroupe un ensemble de composants s’appuyant sur du code ouvert permettant de stocker, de visualiser, d’interagir, de navi
Externí odkaz:
https://doaj.org/article/e17136652baf46fca5c0fd9c6b094726
Autor:
Clément Colin, Corentin Gautier, Diego Vinasco-Alvarez, Johanna Delanoy, Gilles Gesquière, John Samuel, Sylvie Servigne, Éric Boix, Thibault Dupont, Mathieu Livebardon, Valentin Machado, Lorenzo Marnat
Cet article présente la plateforme UD-SV (Urban Data Services and Visualization) développée au laboratoire LIRIS. UD-SV regroupe un ensemble de composants s’appuyant sur du code ouvert permettant de stocker, de visualiser, d’interagir, de navi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2a3b77c81295b36392bc3eb31befbf6b
http://journals.openedition.org/mappemonde/8265
http://journals.openedition.org/mappemonde/8265
Autor:
Jorge Condor Lacambra, Manuel Lagunas Arto, Johanna Delanoy, Belén Masiá Corcoy, Diego Gutiérrez Pérez
Publikováno v:
Jornada de Jóvenes Investigadores del I3A. 9
We propose a method to estimate normal maps of objects in the wild, from just a single RGB image. Our approach is based on deep learning, and we use synthetic data to train our network. Lastly, we show its applicability by improving the results of im
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::57a880bfe7116bc502ca8abd1aa07048
https://doi.org/10.26754/jjii3a.20215977
https://doi.org/10.26754/jjii3a.20215977
Publikováno v:
Journal of Vision
Zaguán. Repositorio Digital de la Universidad de Zaragoza
instname
Zaguán. Repositorio Digital de la Universidad de Zaragoza
instname
Painters are masters in replicating the visual appearance of materials.While the perception of material appearance is not yet fully understood, painters seem to have acquired an implicit understanding of the key visual cues that we need to accurately
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d8b9704336ca52bd37d5686d613550fb
http://europepmc.org/articles/PMC8131993
http://europepmc.org/articles/PMC8131993
Autor:
Johanna Delanoy, Belen Masia, Ana Serrano, Manuel Lagunas, Diego Gutierrez, Roland W. Fleming, Ignacio Galve
Publikováno v:
ACM SIGGRAPH 2020 Posters
SIGGRAPH Posters
SIGGRAPH Posters
Establishing a robust measure for material similarity that correlates well with human perception is a long-standing problem. A recent work presented a deep learning model trained to produce a feature space that aligns with human perception by gatheri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0ae63431128c3184a30314796646f840
Publikováno v:
Computers and Graphics
Computers and Graphics, 2019, Proceedings of Shape Modeling International 2019, 82, pp.65--72. ⟨10.1016/j.cag.2019.05.024⟩
Computers & Graphics
Computers and Graphics, Elsevier, 2019, Proceedings of Shape Modeling International 2019, 82, pp.65--72. ⟨10.1016/j.cag.2019.05.024⟩
Computers and Graphics, 2019, Proceedings of Shape Modeling International 2019, 82, pp.65--72. ⟨10.1016/j.cag.2019.05.024⟩
Computers & Graphics
Computers and Graphics, Elsevier, 2019, Proceedings of Shape Modeling International 2019, 82, pp.65--72. ⟨10.1016/j.cag.2019.05.024⟩
International audience; Recent works on data-driven sketch-based modeling use either voxel grids or normal/depth maps as geometric representations compatible with convolutional neural networks. While voxel grids can represent complete objects-includi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8210dd8bd1c5d21663b453438e5d37bc
https://hal.science/hal-02141469/document
https://hal.science/hal-02141469/document
Publikováno v:
Proceedings of the ACM on Computer Graphics and Interactive Techniques
Proceedings of the ACM on Computer Graphics and Interactive Techniques, ACM, In press, 1 (21), 〈10.1145/3203197〉
Proceedings of the ACM on Computer Graphics and Interactive Techniques, ACM, 2018, 1 (1), pp.1-22. ⟨10.1145/3203197⟩
Proceedings of the ACM on Computer Graphics and Interactive Techniques, 2018, 1 (1), pp.1-22. ⟨10.1145/3203197⟩
Proceedings of the ACM on Computer Graphics and Interactive Techniques, ACM, In press, 1 (21), 〈10.1145/3203197〉
Proceedings of the ACM on Computer Graphics and Interactive Techniques, ACM, 2018, 1 (1), pp.1-22. ⟨10.1145/3203197⟩
Proceedings of the ACM on Computer Graphics and Interactive Techniques, 2018, 1 (1), pp.1-22. ⟨10.1145/3203197⟩
Sketch-based modeling strives to bring the ease and immediacy of drawing to the 3D world. However, while drawings are easy for humans to create, they are very challenging for computers to interpret due to their sparsity and ambiguity. We propose a da
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::32c20c502fa61a5db02e360647980865
https://hal.inria.fr/hal-01799600/document
https://hal.inria.fr/hal-01799600/document