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pro vyhledávání: '"Pinard, Clément"'
Autor:
Pinard, Clément
Le drone orienté grand public est principalement une caméra volante, stabilisée et de bonne qualité. Ceux-ci ont démocratisé la prise de vue aérienne, mais avec leur succès grandissant, la notion de sécurité est devenue prépondérante.Ce t
Externí odkaz:
http://www.theses.fr/2019SACLY003/document
Autor:
Pinard, Clément, Manzanera, Antoine
We present a protocol to construct your own depth validation dataset for navigation. This protocol, called RDC for Rigid Depth Constructor, aims at being more accessible and cheaper than already existing techniques, requiring only a camera and a Lida
Externí odkaz:
http://arxiv.org/abs/2103.15970
Publikováno v:
European Conference on Mobile Robotics 2017
Using a neural network architecture for depth map inference from monocular stabilized videos with application to UAV videos in rigid scenes, we propose a multi-range architecture for unconstrained UAV flight, leveraging flight data from sensors to ma
Externí odkaz:
http://arxiv.org/abs/1809.04467
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume IV-2/W3, 2017 International Conference on Unmanned Aerial Vehicles in Geomatics, 4-7 September 2017, Bonn, Germany
We propose a depth map inference system from monocular videos based on a novel dataset for navigation that mimics aerial footage from gimbal stabilized monocular camera in rigid scenes. Unlike most navigation datasets, the lack of rotation implies an
Externí odkaz:
http://arxiv.org/abs/1809.04453
This work is based on a questioning of the quality metrics used by deep neural networks performing depth prediction from a single image, and then of the usability of recently published works on unsupervised learning of depth from videos. To overcome
Externí odkaz:
http://arxiv.org/abs/1809.04471
Autor:
Pinard, Clément, Manzanera, Antoine
Publikováno v:
Multimedia Tools & Applications; Nov2023, Vol. 82 Issue 27, p41641-41667, 27p
Autor:
Pinard, Clément
Publikováno v:
Computer Vision and Pattern Recognition [cs.CV]. Université Paris Saclay (COmUE), 2019. English. ⟨NNT : 2019SACLY003⟩
Customer unmanned aerial vehicles (UAVs) are mainly flying cameras. They democratized aerial footage, but with thei success came security concerns.This works aims at improving UAVs security with obstacle avoidance, while keeping a smooth flight. In t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2592::4f28b93e317efb1e9ac329e287c61003
https://pastel.archives-ouvertes.fr/tel-02285215
https://pastel.archives-ouvertes.fr/tel-02285215
Autor:
Clément Pinard, Antoine Manzanera
Publikováno v:
Multimedia Tools and Applications.
We present a protocol to construct your own depth validation dataset for navigation. This protocol, called RDC for Rigid Depth Constructor, aims at being more accessible and cheaper than already existing techniques, requiring only a camera and a Lida
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9b87b45c37a1db001aae42e6035948e9
https://doi.org/10.1007/s11042-023-14743-0
https://doi.org/10.1007/s11042-023-14743-0
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030110147
ECCV Workshops (3)
ECCV GMDL Workshop
ECCV GMDL Workshop, Sep 2018, Munich, Germany
ECCV Workshops (3)
ECCV GMDL Workshop
ECCV GMDL Workshop, Sep 2018, Munich, Germany
International audience; This work is based on a questioning of the quality metrics used by deep neural networks performing depth prediction from a single image, and then of the usability of recently published works on unsu-pervised learning of depth
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::386f7ad63f7b03483878902c84bae06f
Publikováno v:
The European Conference on Mobile Robotics Proceedings
European Conference on Mobile Robotics
European Conference on Mobile Robotics, ENSTA ParisTech, Sep 2017, Paris, France
ECMR
European Conference on Mobile Robotics
European Conference on Mobile Robotics, ENSTA ParisTech, Sep 2017, Paris, France
ECMR
Using a neural network architecture for depth map inference from monocular stabilized videos with application to UAV videos in rigid scenes, we propose a multi-range architecture for unconstrained UAV flight, leveraging flight data from sensors to ma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1ff589a428da044273e4b64f727cb982
https://hal.archives-ouvertes.fr/hal-01587658/document
https://hal.archives-ouvertes.fr/hal-01587658/document