Tolerating Annotation Displacement in Dense Object Counting via Point Annotation Probability Map
Counting objects in crowded scenes remains a challenge to computer vision. The current deep learning based approach often formulate it as a Gaussian density regression problem. Such a brute-force regression, though effective, may not consider the annotation displacement properly which arises from th...
Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 32(2023) vom: 16., Seite 6359-6372 |
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Format: | Online-Aufsatz |
Sprache: | English |
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2023
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Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
Schlagworte: | Journal Article |
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