10 citations · 23 across the 5 of their papers we have counts for
7 papers
Cross-Modal Retrieval: A Systematic Review of Methods and Future Directions
Tianshi Wang, Fengling Li, Lei Zhu +3
With the exponential surge in diverse multi-modal data, traditional uni-modal retrieval methods struggle to meet the needs of users seeking access to data across various modalities…
GSMFlow: Generation Shifts Mitigating Flow for Generalized Zero-Shot Learning
Zhi Chen, Yadan Luo, Sen Wang +2
Generalized Zero-Shot Learning (GZSL) aims to recognize images from both the seen and unseen classes by transferring semantic knowledge from seen to unseen classes. It is a promisi…
Two-pronged Strategy: Lightweight Augmented Graph Network Hashing for Scalable Image Retrieval
Hui Cui, Lei Zhu, Jingjing Li +2
Hashing learns compact binary codes to store and retrieve massive data efficiently. Particularly, unsupervised deep hashing is supported by powerful deep neural networks and has th…
Semantics Disentangling for Generalized Zero-Shot Learning
Zhi Chen, Yadan Luo, Ruihong Qiu +4
Generalized zero-shot learning (GZSL) aims to classify samples under the assumption that some classes are not observable during training. To bridge the gap between the seen and uns…
Learning from the Past: Continual Meta-Learning via Bayesian Graph Modeling
Yadan Luo, Zi Huang, Zheng Zhang +3
Meta-learning for few-shot learning allows a machine to leverage previously acquired knowledge as a prior, thus improving the performance on novel tasks with only small amounts of…
Deep Collaborative Discrete Hashing with Semantic-Invariant Structure
Zijian Wang, Zheng Zhang, Yadan Luo +1
Existing deep hashing approaches fail to fully explore semantic correlations and neglect the effect of linguistic context on visual attention learning, leading to inferior performa…