Semi-Supervised Human Detection via Region Proposal Networks Aided by Verification
In this paper, we explore how to leverage readily available unlabeled data to improve semi-supervised human detection performance. For this purpose, we specifically modify the region proposal network (RPN) for learning on a partially labeled dataset. Based on commonly observed false positive types,...
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Détails bibliographiques
| Publié dans: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - (2019) vom: 03. Okt.
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| Auteur principal: |
Wu, Si
(Auteur) |
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| Autres auteurs: |
Wu, Wenhao,
Lei, Shiyao,
Lin, Sihao,
Li, Rui,
Yu, Zhiwen,
Wong, Hau-San |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2019
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| Accès à la collection: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
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| Sujets: | Journal Article |
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