42 citations · 44 across the 5 of their papers we have counts for
5 papers
Semantic-Aware Adversarial Training for Reliable Deep Hashing Retrieval
Xu Yuan, Zheng Zhang, Xunguang Wang +1
Deep hashing has been intensively studied and successfully applied in large-scale image retrieval systems due to its efficiency and effectiveness. Recent studies have recognized th…
Reliable and Efficient Evaluation of Adversarial Robustness for Deep Hashing-Based Retrieval
Xunguang Wang, Jiawang Bai, Xinyue Xu +1
Deep hashing has been extensively applied to massive image retrieval due to its efficiency and effectiveness. Recently, several adversarial attacks have been presented to reveal th…
CgAT: Center-Guided Adversarial Training for Deep Hashing-Based Retrieval
Xunguang Wang, Yiqun Lin, Xiaomeng Li
Deep hashing has been extensively utilized in massive image retrieval because of its efficiency and effectiveness. However, deep hashing models are vulnerable to adversarial exampl…
Prototype-supervised Adversarial Network for Targeted Attack of Deep Hashing
Xunguang Wang, Zheng Zhang, Baoyuan Wu +2
Due to its powerful capability of representation learning and high-efficiency computation, deep hashing has made significant progress in large-scale image retrieval. However, deep…
Initializing Perturbations in Multiple Directions for Fast Adversarial Training
Xunguang Wang, Ship Peng Xu, Eric Ke Wang
Recent developments in the filed of Deep Learning have demonstrated that Deep Neural Networks(DNNs) are vulnerable to adversarial examples. Specifically, in image classification, a…