TransMix: attend to mix for Vision Transformers
Mixup-based augmentation has been found to be effective for generalizing models during training, especially for Vision Transformers (ViTs) since they can easily overfit. However, previous mixup-based methods have an underlying prior knowledge that the linearly interpolated ratio of targets should be...
Main Authors: | Chen, J-N, Sun, S, He, J, Torr, P, Yuille, A, Bai, S |
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Format: | Conference item |
Language: | English |
Published: |
IEEE
2022
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