Content-Attribute Disentanglement for Generalized Zero-Shot Learning

Content-Attribute Disentanglement for Generalized Zero-Shot Learning

Humans can recognize or infer unseen classes of objects using descriptions explaining the characteristics (semantic information) of the classes. However, conventional deep learning models trained in a supervised manner cannot classify classes that were unseen during training. Hence, many studies hav...

Full description

Bibliographic Details
Main Authors: Yoojin An, Sangyeon Kim, Yuxuan Liang, Roger Zimmermann, Dongho Kim, Jihie Kim
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Computer vision
deep learning
disentangled representation
generalized zero-shot learning
Online Access:https://ieeexplore.ieee.org/document/9784824/

Internet

https://ieeexplore.ieee.org/document/9784824/

Similar Items