Scale-Aware Crowd Counting Network With Annotation Error Modeling
Traditional crowd-counting networks suffer from information loss when feature maps are reduced by pooling layers, leading to inaccuracies in counting crowds at a distance. Existing methods often assume correct annotations during training, disregarding the impact of noisy annotations, especially in c...
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Détails bibliographiques
| Publié dans: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 34(2025) vom: 08., Seite 2750-2764
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| Auteur principal: |
Hsieh, Yi-Kuan
(Auteur) |
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| Autres auteurs: |
Hsieh, Jun-Wei,
Li, Xin,
Zhang, Yu-Ming,
Tseng, Yu-Chee,
Chang, Ming-Ching |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2025
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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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