7 citations · 9 across the 2 of their papers we have counts for
4 papers
HoMM: Higher-order Moment Matching for Unsupervised Domain Adaptation
Chao Chen, Zhihang Fu, Zhihong Chen +4
Minimizing the discrepancy of feature distributions between different domains is one of the most promising directions in unsupervised domain adaptation. From the perspective of dis…
SSAH: Semi-supervised Adversarial Deep Hashing with Self-paced Hard Sample Generation
Sheng Jin, Shangchen Zhou, Yao Liu +4
Deep hashing methods have been proved to be effective and efficient for large-scale Web media search. The success of these data-driven methods largely depends on collecting suffici…
Deep Saliency Hashing
Sheng Jin, Hongxun Yao, Xiaoshuai Sun +3
In recent years, hashing methods have been proved to be effective and efficient for the large-scale Web media search. However, the existing general hashing methods have limited dis…
Unsupervised Semantic Deep Hashing
Sheng Jin
In recent years, deep hashing methods have been proved to be efficient since it employs convolutional neural network to learn features and hashing codes simultaneously. However, th…