Centralized Adversarial Learning for Robust Deep Hashing. (arXiv:2204.10779v1 [cs.CV])

Deep hashing has been extensively utilized in massive image retrieval because
of its efficiency and effectiveness. Recently, it becomes a hot issue to study
adversarial examples which poses a security challenge to deep hashing models.
However, there is still a critical bottleneck: how to find a superior and exact
semantic representative as the guide to further enhance the adversarial attack
and defense in deep hashing based retrieval. We, for the first time, attempt to
design an effective adversarial learning with …

adversarial hashing