CWFA, a channel-wise global-average feature perturbation, improves robustness of Transformer segmentation models to common corruptions without hurting clean accuracy.
Twins: Re- visiting the design of spatial attention in vision transformers
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Global Average Feature Augmentation for Robust Semantic Segmentation with Transformers
CWFA, a channel-wise global-average feature perturbation, improves robustness of Transformer segmentation models to common corruptions without hurting clean accuracy.