Semi-supervised domain generalization with stochastic styleMatch

Ideally, visual learning algorithms should be generalizable, for dealing with any unseen domain shift when deployed in a new target environment; and data-efficient, for reducing development costs by using as little labels as possible. To this end, we study semi-supervised domain generalization (SSDG...

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Bibliographic Details
Main Authors: Zhou, Kaiyang, Loy, Chen Change, Liu, Ziwei
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2023
Subjects:
Online Access:https://hdl.handle.net/10356/170127
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Institution: Nanyang Technological University
Language: English
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