Decoupled self-supervised label augmentation for fully-supervised image classification
Self-supervised label augmentation has emerged as an effective means to overcome the data scarcity problem for supervised vision tasks. Existing rotation-based self-supervised label augmentation methods either impose or relax the rotation invariance constraint on the primary classifier, which omit n...
Main Authors: | , , , , |
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Other Authors: | |
Format: | Journal Article |
Language: | English |
Published: |
2024
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/178584 |