NCNet: Neighbourhood Consensus Networks for Estimating Image Correspondences
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| Published in: | IEEE Transactions on Pattern Analysis and Machine Intelligence Vol. 44; pp. 1020 - 1034 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | Japanese |
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Institute of Electrical and Electronics Engineers (IEEE)
01.02.2022
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| ISSN: | 0162-8828, 1939-3539 |
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| Author | Relja Arandjelovic Akihiko Torii Josef Sivic Ignacio Rocco Tomas Pajdla Mircea Cimpoi |
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| Author_xml | – sequence: 1 fullname: Ignacio Rocco – sequence: 2 orcidid: 0000-0002-5624-7593 fullname: Mircea Cimpoi – sequence: 3 fullname: Relja Arandjelovic – sequence: 4 fullname: Akihiko Torii – sequence: 5 fullname: Tomas Pajdla – sequence: 6 fullname: Josef Sivic |
| BackLink | https://cir.nii.ac.jp/crid/1872835442444219392$$DView record in CiNii |
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| Contributor | DeepMind [London] ; DeepMind Technologies This work was partially supported by JSPS KAKENHI Grant Numbers 15H05313, 16KK0002, EU-H2020 project LADIO No. 731970, ERCgrant LEAP No. 336845, CIFAR Learning in Machines & Brains program and the European Regional Development Fund under the project IMPACT (reg. no. CZ.02.1.01/0.0/0.0/15 003/0000468), and the French government under management of Agence Nationale de la Recherche as part of the "Investissements d'avenir" program, reference ANR-19-P3IA-0001 (PRAIRIE 3IA Institute). We gratefully acknowledge the support of NVIDIA Corporation with the donation of Quadro P6000 GPU Models of visual object recognition and scene understanding (WILLOW) ; Inria de Paris ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Département d'informatique - ENS Paris (DI-ENS) ; Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informa |
| Contributor_xml | – sequence: 1 fullname: Département d'informatique - ENS Paris (DI-ENS) ; École normale supérieure - Paris (ENS-PSL) ; Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS) – sequence: 2 fullname: Models of visual object recognition and scene understanding (WILLOW) ; Département d'informatique - ENS Paris (DI-ENS) ; École normale supérieure - Paris (ENS-PSL) ; Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL) ; Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria de Paris ; Institut National de Recherche en Informatique et en Automatique (Inria) – sequence: 3 fullname: Czech Institute of Informatics, Robotics and Cybernetics [Prague] (CIIRC) ; Czech Technical University in Prague (CTU) – sequence: 4 fullname: DeepMind [London] ; DeepMind Technologies – sequence: 5 fullname: Tokyo Institute of Technology [Tokyo] (TITECH) – sequence: 6 fullname: This work was partially supported by JSPS KAKENHI Grant Numbers 15H05313, 16KK0002, EU-H2020 project LADIO No. 731970, ERCgrant LEAP No. 336845, CIFAR Learning in Machines & Brains program and the European Regional Development Fund under the project IMPACT (reg. no. CZ.02.1.01/0.0/0.0/15 003/0000468), and the French government under management of Agence Nationale de la Recherche as part of the "Investissements d'avenir" program, reference ANR-19-P3IA-0001 (PRAIRIE 3IA Institute). We gratefully acknowledge the support of NVIDIA Corporation with the donation of Quadro P6000 GPU – sequence: 7 fullname: ANR-19-P3IA-0001,PRAIRIE,PaRis Artificial Intelligence Research InstitutE – sequence: 8 fullname: European Project: 336845,EC:FP7:ERC,ERC-2013-StG,LEAP – sequence: 9 fullname: Département d'informatique - ENS Paris (DI-ENS) ; Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Paris (ENS Paris) ; Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL) – sequence: 10 fullname: Models of visual object recognition and scene understanding (WILLOW) ; Inria de Paris ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Département d'informatique - ENS Paris (DI-ENS) ; Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Paris (ENS Paris) ; Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris) ; Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL) – sequence: 11 fullname: DeepMind ; DeepMind Technologies – sequence: 12 fullname: Département d'informatique de l'École normale supérieure (DI-ENS) ; École normale supérieure - Paris (ENS Paris) ; Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS) – sequence: 13 fullname: Models of visual object recognition and scene understanding (WILLOW) ; Inria de Paris ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Département d'informatique de l'École normale supérieure (DI-ENS) ; École normale supérieure - Paris (ENS Paris) ; Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris) ; Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS) – sequence: 14 fullname: Czech Institute of Informatics, Robotics and Cybernetics (CIIRC) ; Czech Technical University in Prague (CTU) – sequence: 15 fullname: This work was partially supported by JSPS KAKENHI Grant Numbers 15H05313, 16KK0002, EU-H2020 project LADIO No. 731970, ERC grant LEAP No. 336845, CIFAR Learning in Machines & Brains program and the European Regional Development Fund under the project IMPACT(reg. no. CZ.02.1.01/0.0/0.0/15 003/0000468). We gratefully acknowledge the support of NVIDIA Corporation with the donation of Quadro P6000 GPU – sequence: 16 fullname: Département d'informatique - ENS Paris (DI-ENS) ; École normale supérieure - Paris (ENS-PSL) ; Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS) – sequence: 17 fullname: Models of visual object recognition and scene understanding (WILLOW) ; Département d'informatique - ENS Paris (DI-ENS) ; École normale supérieure - Paris (ENS-PSL) ; Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL) ; Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria de Paris ; Institut National de Recherche en Informatique et en Automatique (Inria) |
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| SubjectTerms | [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] category-level matching Geometric matching image alignment Neighbourhood consensus Nighbourhood consensus |
| Title | NCNet: Neighbourhood Consensus Networks for Estimating Image Correspondences |
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