Learning Collections of Part Models for Object Recognition

CVPR 2013 Ian EndresKevin J. ShihJohnston JiaaDerek Hoiem

We propose a method to learn a diverse collection of discriminative parts from object bounding box annotations. Part detectors can be trained and applied individually, which simplifies learning and extension to new features or categories... (read more)

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