Weakly supervised scale-invariant learning of models for visual recognition

We investigate a method for learning object categories in a weakly supervised manner. Given a set of images known to contain the target category from a similar viewpoint, learning is translation and scale-invariant; does not require alignment or correspondence between the training images, and is rob...

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Bibliografski detalji
Glavni autori: Fergus, R, Perona, P, Zisserman, A
Format: Journal article
Jezik:English
Izdano: Springer Nature 2006