169 citations · 255 across the 16 of their papers we have counts for
17 papers · 1 filter
Doubly Contrastive Deep Clustering
Zhiyuan Dang, Cheng Deng, Xu Yang +1
Deep clustering successfully provides more effective features than conventional ones and thus becomes an important technique in current unsupervised learning. However, most deep cl…
Incremental Embedding Learning via Zero-Shot Translation
Kun Wei, Cheng Deng, Xu Yang +1
Modern deep learning methods have achieved great success in machine learning and computer vision fields by learning a set of pre-defined datasets. Howerver, these methods perform u…
Towards Improved and Interpretable Deep Metric Learning via Attentive Grouping
Xinyi Xu, Zhengyang Wang, Cheng Deng +2
Grouping has been commonly used in deep metric learning for computing diverse features. However, current methods are prone to overfitting and lack interpretability. In this work, w…
Projection & Probability-Driven Black-Box Attack
Jie Li, Rongrong Ji, Hong Liu +4
Generating adversarial examples in a black-box setting retains a significant challenge with vast practical application prospects. In particular, existing black-box attacks suffer f…
Multi-task Collaborative Network for Joint Referring Expression Comprehension and Segmentation
Gen Luo, Yiyi Zhou, Xiaoshuai Sun +4
Referring expression comprehension (REC) and segmentation (RES) are two highly-related tasks, which both aim at identifying the referent according to a natural language expression.…
DistillHash: Unsupervised Deep Hashing by Distilling Data Pairs
Erkun Yang, Tongliang Liu, Cheng Deng +2
Due to the high storage and search efficiency, hashing has become prevalent for large-scale similarity search. Particularly, deep hashing methods have greatly improved the search p…