Zero-shot learning for action recognition using synthesized features

The major disadvantage of supervised methods for action recognition is the need for a large amount of annotated data, where the data is matched to its label accurately. To address this issue, Zero-Shot Learning (ZSL) is introduced. Zero short learning primarily uses data that is synthesized to compe...

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Veröffentlicht in:	Neurocomputing (Amsterdam) Jg. 390; S. 117 - 130
Hauptverfasser:	Mishra, Ashish, Pandey, Anubha, Murthy, Hema A.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 21.05.2020
Schlagworte:	Bi-directional generative adversarial network Generalized zero shot learning Inductive ZSL setting Inverse autoregressive flow Transductive ZSL setting Transductive ZSL setting Inverse autoregressive flow Generalized zero shot learning Bi-directional generative adversarial network Inductive ZSL setting
ISSN:	0925-2312, 1872-8286
Online-Zugang:	Volltext
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