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Self-supervised asymmetric deep hashing with margin-scalable constraint
[article]
2021
arXiv
pre-print
Due to its effectivity and efficiency, deep hashing approaches are widely used for large-scale visual search. However, it is still challenging to produce compact and discriminative hash codes for images associated with multiple semantics for two main reasons, 1) similarity constraints designed in most of the existing methods are based upon an oversimplified similarity assignment(i.e., 0 for instance pairs sharing no label, 1 for instance pairs sharing at least 1 label), 2) the exploration in
arXiv:2012.03820v3
fatcat:fscm4ggdyrct3o6kso53mmriou