Learning Reasoning-Decision Networks for Robust Face Alignment
In this paper, we propose an end-to-end reasoning-decision networks (RDN) approach for robust face alignment via policy gradient. Unlike the conventional coarse-to-fine approaches which likely lead to bias prediction due to poor initialization, our approach aims to learn a policy by leveraging raw p...
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Détails bibliographiques
| Publié dans: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 42(2020), 3 vom: 15. März, Seite 679-693
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| Auteur principal: |
Liu, Hao
(Auteur) |
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| Autres auteurs: |
Lu, Jiwen,
Guo, Minghao,
Wu, Suping,
Zhou, Jie |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2020
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| Accès à la collection: | IEEE transactions on pattern analysis and machine intelligence
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| Sujets: | Journal Article |
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