55 citations · 174 across the 17 of their papers we have counts for
7 papers · 1 filter
Incremental Meta-Learning via Episodic Replay Distillation for Few-Shot Image Recognition
Kai Wang, Xialei Liu, Andy Bagdanov +3
Most meta-learning approaches assume the existence of a very large set of labeled data available for episodic meta-learning of base knowledge. This contrasts with the more realisti…
HCV: Hierarchy-Consistency Verification for Incremental Implicitly-Refined Classification
Kai Wang, Xialei Liu, Luis Herranz +1
Human beings learn and accumulate hierarchical knowledge over their lifetime. This knowledge is associated with previous concepts for consolidation and hierarchical construction. H…
An Efficient Training Approach for Very Large Scale Face Recognition
Kai Wang, Shuo Wang, Panpan Zhang +7
Face recognition has achieved significant progress in deep learning era due to the ultra-large-scale and welllabeled datasets. However, training on the outsize datasets is time-con…
ACAE-REMIND for Online Continual Learning with Compressed Feature Replay
Kai Wang, Luis Herranz, Joost van de Weijer
Online continual learning aims to learn from a non-IID stream of data from a number of different tasks, where the learner is only allowed to consider data once. Methods are typical…
Learning to Cluster Faces via Transformer
Jinxing Ye, Xioajiang Peng, Baigui Sun +4
Face clustering is a useful tool for applications like automatic face annotation and retrieval. The main challenge is that it is difficult to cluster images from the same identity…
Continual learning in cross-modal retrieval
Kai Wang, Luis Herranz, Joost van de Weijer
Multimodal representations and continual learning are two areas closely related to human intelligence. The former considers the learning of shared representation spaces where infor…
On Implicit Attribute Localization for Generalized Zero-Shot Learning
Shiqi Yang, Kai Wang, Luis Herranz +1
Zero-shot learning (ZSL) aims to discriminate images from unseen classes by exploiting relations to seen classes via their attribute-based descriptions. Since attributes are often…