Ensemble Deep Manifold Similarity Learning Using Hard Proxies

CVPR 2019 Nicolas Aziere Sinisa Todorovic

This paper is about learning deep representations of images such that images belonging to the same class have more similar representations than those belonging to different classes. For this goal, prior work typically uses the triplet or N-pair loss, specified in terms of either l2-distances or dot-products between deep features... (read more)

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