Enhancing Semantic-Consistent Features and Transforming Discriminative Features for Generalized Zero-Shot Classifications

Enhancing Semantic-Consistent Features and Transforming Discriminative Features for Generalized Zero-Shot Classifications

Generalized zero-shot learning (GZSL) aims to classify classes that do not appear during training. Recent state-of-the-art approaches rely on generative models, which use correlating semantic embeddings to synthesize unseen classes visual features; however, these approaches ignore the semantic and v...

书目详细资料
Main Authors:	Guan Yang, Ayou Han, Xiaoming Liu, Yang Liu, Tao Wei, Zhiyuan Zhang
格式:	文件
语言:	English
出版:	MDPI AG 2022-12-01
丛编:	Applied Sciences
主题:	generalized zero-shot learning disentangled representation semantic consistency enhanced features
在线阅读:	https://www.mdpi.com/2076-3417/12/24/12642

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