Y Li, Z Liu, L Yao, X Chang - IEEE Transactions on Multimedia, 2021 - ieeexplore.ieee.org
Zero-shot learning (ZSL) aims to transfer knowledge from seen classes to semantically related unseen classes, which are absent during training. The promising strategies for ZSL …
Y Du, M Shi, F Wei, G Li - IEEE Transactions on Neural …, 2023 - ieeexplore.ieee.org
Zero-shot learning (ZSL) aims to recognize classes that do not have samples in the training set. One representative solution is to directly learn an embedding function associating visual …
Zero-Shot Learning (ZSL) aims to transfer learned knowledge from observed classes to unseen classes via semantic correlations. A promising strategy is to learn a global-local …
K Wang, L Herranz… - Proceedings of the IEEE …, 2021 - openaccess.thecvf.com
Multimodal representations and continual learning are two areas closely related to human intelligence. The former considers the learning of shared representation spaces where …
Abstract Zero-Shot Learning (ZSL) aims to recognise unseen object classes which are not observed during the training phase. Most of the existing methods on ZSL focus on learning a …
Abstract Current approaches in Generalized Zero-Shot Learning (GZSL) are built upon base models which consider only a single class attribute vector representation over the entire …
Recent advancements in attribute localization have showcased its potential in discovering the intrinsic semantic knowledge for visual feature representations, thereby facilitating …
Z Liu, Y Li, L Yao, J McAuley… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Current approaches to zero-shot learning (ZSL) struggle to learn generalizable semantic knowledge capable of capturing complex correlations. Inspired by Spiral Curriculum, which …
Y Li, Z Liu, X Chang, J McAuley… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Zero-Shot Learning (ZSL) aims to transfer classification capability from seen to unseen classes. Recent methods have proved that generalization and specialization are two …