Abstract: Test-time adaptation (TTA) is a technique to improve the performance of a pretrained source model on a target distribution without using any labeled data. However, existing self-trained TTA ...

Abstract: Test time adaptation (TTA) aims to adapt deep neural networks when receiving out of distribution test domain samples. In this setting, the model can only access online unlabeled test samples ...

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