Learning Hash Codes via Hamming Distance Targets

1 Oct 2018 Martin Loncaric Bowei Liu Ryan Weber

We present a powerful new loss function and training scheme for learning binary hash codes with any differentiable model and similarity function. Our loss function improves over prior methods by using log likelihood loss on top of an accurate approximation for the probability that two inputs fall within a Hamming distance target... (read more)

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