6 citations · 10 across the 2 of their papers we have counts for
5 papers
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…
Bookworm continual learning: beyond zero-shot learning and continual learning
Kai Wang, Luis Herranz, Anjan Dutta +1
We propose bookworm continual learning(BCL), a flexible setting where unseen classes can be inferred via a semantic model, and the visual model can be updated continually. Thus BCL…
Simple and effective localized attribute representations for 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 semantic descriptions. Some recent papers have shown the…
Semantic Drift Compensation for Class-Incremental Learning
Lu Yu, Bartłomiej Twardowski, Xialei Liu +5
Class-incremental learning of deep networks sequentially increases the number of classes to be classified. During training, the network has only access to data of one task at a tim…