Attribute-Induced Bias Eliminating for Transductive Zero-Shot Learning
نویسندگان
چکیده
منابع مشابه
Transductive Unbiased Embedding for Zero-Shot Learning
Most existing Zero-Shot Learning (ZSL) methods have the strong bias problem, in which instances of unseen (target) classes tend to be categorized as one of the seen (source) classes. So they yield poor performance after being deployed in the generalized ZSL settings. In this paper, we propose a straightforward yet effective method named Quasi-Fully Supervised Learning (QFSL) to alleviate the bi...
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ژورنال
عنوان ژورنال: IEEE Transactions on Multimedia
سال: 2021
ISSN: 1520-9210,1941-0077
DOI: 10.1109/tmm.2021.3074252