Learning to detect partially overlapping instances
The objective of this work is to detect all instances of a class (such as cells or people) in an image. The instances may be partially overlapping and clustered, and hence quite challenging for traditional detectors, which aim at localizing individual instances. Our approach is to propose a set of c...
Main Authors: | Arteta, C, Lempitsky, V, Noble, JA, Zisserman, A |
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Format: | Conference item |
Language: | English |
Published: |
IEEE
2013
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