Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Jerome Revaud"'
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7a65315a4bed9e86d13b21c7479c3ab6
https://doi.org/10.1109/cvpr52688.2022.00390
https://doi.org/10.1109/cvpr52688.2022.00390
Autor:
Jerome Revaud, Martin Humenberger
Publikováno v:
2021 IEEE/CVF International Conference on Computer Vision (ICCV).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7b6e6b9cb292c63ebb6eb941f3c6433f
https://doi.org/10.1109/iccv48922.2021.00451
https://doi.org/10.1109/iccv48922.2021.00451
Publikováno v:
ICCV
Image retrieval can be formulated as a ranking problem where the goal is to order database images by decreasing similarity to the query. Recent deep models for image retrieval have outperformed traditional methods by leveraging ranking-tailored loss
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9717bfc27a876f2461b21fdc8bca24f7
https://doi.org/10.1109/iccv.2019.00521
https://doi.org/10.1109/iccv.2019.00521
Publikováno v:
CVPR
Maps are an increasingly important tool in our daily lives, yet their rich semantic content still largely depends on manual input. Motivated by the broad availability of geo-tagged street-view images, we propose a new task aiming to make the map upda
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::96423ce3bb18d3cb9b8f06d520ca1bba
https://doi.org/10.1109/cvpr.2019.00421
https://doi.org/10.1109/cvpr.2019.00421
Publikováno v:
CVPR 2018-IEEE Conference on Computer Vision and Pattern Recognition
CVPR 2018-IEEE Conference on Computer Vision and Pattern Recognition, Jun 2018, Salt Lake City, United States. pp.7024-7033, ⟨10.1109/CVPR.2018.00734⟩
CVPR
CVPR 2018-IEEE Conference on Computer Vision and Pattern Recognition, Jun 2018, Salt Lake City, United States. pp.7024-7033, ⟨10.1109/CVPR.2018.00734⟩
CVPR
International audience; Most state-of-the-art methods for action recognition rely on a two-stream architecture that processes appearance and motion independently. In this paper, we claim that considering them jointly offers rich information for actio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::166b2eef35f9bb19a87c618eb029ab74
https://inria.hal.science/hal-01764222/document
https://inria.hal.science/hal-01764222/document
Publikováno v:
International Journal of Computer Vision
International Journal of Computer Vision, 2016, 120 (3), pp.300-323. ⟨10.1007/s11263-016-0908-3⟩
International Journal of Computer Vision, Springer Verlag, 2016, 120 (3), pp.300-323. ⟨10.1007/s11263-016-0908-3⟩
International Journal of Computer Vision, 2016, 120 (3), pp.300-323. ⟨10.1007/s11263-016-0908-3⟩
International Journal of Computer Vision, Springer Verlag, 2016, 120 (3), pp.300-323. ⟨10.1007/s11263-016-0908-3⟩
International audience; We introduce a novel matching algorithm, called DeepMatching, to compute dense correspondences between images. DeepMatching relies on a hierarchical, multi-layer, correlational architecture designed for matching images and was
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9be4ea14ac0b435e0643cbaafe88a147
https://inria.hal.science/hal-01148432
https://inria.hal.science/hal-01148432
While deep learning has become a key ingredient in the top performing methods for many computer vision tasks, it has failed so far to bring similar improvements to instance-level image retrieval. In this article, we argue that reasons for the underwh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::71afbe0351ca13c31cb5d44bbbd1a7b2
http://arxiv.org/abs/1610.07940
http://arxiv.org/abs/1610.07940
Publikováno v:
Computer Vision – ECCV 2016 ISBN: 9783319464657
ECCV (6)
ECCV (6)
We propose a novel approach for instance-level image retrieval. It produces a global and compact fixed-length representation for each image by aggregating many region-wise descriptors. In contrast to previous works employing pre-trained deep networks
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6a17ff1cdcd4d9d663857c45aa8a69b7
https://doi.org/10.1007/978-3-319-46466-4_15
https://doi.org/10.1007/978-3-319-46466-4_15
Publikováno v:
International Journal of Computer Vision
International Journal of Computer Vision, Springer Verlag, 2016, 119 (3), pp.291-306. ⟨10.1007/s11263-015-0875-0⟩
International Journal of Computer Vision, 2016, 119 (3), pp.291-306. ⟨10.1007/s11263-015-0875-0⟩
International Journal of Computer Vision, Springer Verlag, 2016, 119 (3), pp.291-306. ⟨10.1007/s11263-015-0875-0⟩
International Journal of Computer Vision, 2016, 119 (3), pp.291-306. ⟨10.1007/s11263-015-0875-0⟩
International audience; We address the problem of specific video event retrieval. Given a query video of a specific event, e.g., a concert of Madonna, the goal is to retrieve other videos of the same event that temporally overlap with the query. Our
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2459b0fd3445e40ad7f88f57485333bc
https://hal.inria.fr/hal-01162603v2/file/paper.pdf
https://hal.inria.fr/hal-01162603v2/file/paper.pdf
Publikováno v:
CVPR-IEEE Conference on Computer Vision & Pattern Recognition
CVPR-IEEE Conference on Computer Vision & Pattern Recognition, Jun 2015, Boston, United States. pp.1164-1172, ⟨10.1109/CVPR.2015.7298720⟩
CVPR
CVPR-IEEE Conference on Computer Vision & Pattern Recognition, Jun 2015, Boston, United States. pp.1164-1172, ⟨10.1109/CVPR.2015.7298720⟩
CVPR
International audience; We propose a novel approach for optical flow estimation , targeted at large displacements with significant oc-clusions. It consists of two steps: i) dense matching by edge-preserving interpolation from a sparse set of matches;
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::08a245f8c4da04168fb26301080a95ba
https://inria.hal.science/hal-01142656/document
https://inria.hal.science/hal-01142656/document