A Quadruplet Loss for Enforcing Semantically Coherent Embeddings in Multi-output Classification Problems

This paper describes one objective function for learning semantically coherent feature embeddings in multi-output classification problems, i.e., when the response variables have dimension higher than one. In particular, we consider the problems of identity retrieval and soft biometrics labelling in visual surveillance environments, which have been attracting growing interests... (read more)

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