Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Julia Guerrero-Viu"'
Autor:
Sandra Malpica, Ana Serrano, Julia Guerrero-Viu, Daniel Martin, Edurne Bernal, Diego Gutierrez, Belen Masia
Publikováno v:
ACM SIGGRAPH 2022 Posters.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a909c57fb83c9643f8e24bc51f5c6f61
https://doi.org/10.1145/3532719.3543220
https://doi.org/10.1145/3532719.3543220
Publikováno v:
Julia Guerrero-Viu
Despite the success of deep learning in disparity estimation, the domain generalization gap remains an issue. We propose a semi-supervised pipeline that successfully adapts DispNet to a real-world domain by joint supervised training on labeled synthe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6cb230fd0f0cdbb9c4692cc5069cd950
http://arxiv.org/abs/2106.00318
http://arxiv.org/abs/2106.00318
Publikováno v:
IEEE International Conference on Robotics and Automation (ICRA 2020)
IEEE International Conference on Robotics and Automation (ICRA 2020), May 2020, Paris, France
ICRA
IEEE International Conference on Robotics and Automation (ICRA 2020), May 2020, Paris, France
ICRA
In the last few years, there has been a growing interest in taking advantage of the 360 panoramic images potential, while managing the new challenges they imply. While several tasks have been improved thanks to the contextual information these images
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::69edc679ed1f4bc23baee983a3f74bbf
https://hal-univ-bourgogne.archives-ouvertes.fr/hal-02470600/file/ICRA2020.pdf
https://hal-univ-bourgogne.archives-ouvertes.fr/hal-02470600/file/ICRA2020.pdf
Autor:
Sergio Izquierdo, Julia Guerrero-Viu, Sven Hauns, Guilherme Miotto, Simon Schrodi, André Biedenkapp, Thomas Elsken, Difan Deng, Marius Lindauer, Frank Hutter
Publikováno v:
Julia Guerrero-Viu
Neural architecture search (NAS) and hyperparameter optimization (HPO) make deep learning accessible to non-experts by automatically finding the architecture of the deep neural network to use and tuning the hyperparameters of the used training pipeli
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8a72347ca91bb115f55d93fdc5551fa5
https://openreview.net/forum?id=yEGlj93aLFY
https://openreview.net/forum?id=yEGlj93aLFY