Feb 13, 2024 · In this paper, we introduce VCoTTA, a variational Bayesian approach to measure uncertainties in CTTA. At the source stage, we transform a pre- ...
The objective of this paper is to devise a test-time adaptation procedure that not only enhances predictive accuracy under distribution shifts but also ...
This paper proposes a novel test-time adaptation strategy that adjusts the model pre-trained on the source domain using only unlabeled online data from the ...
A curated list of awesome online test-time adaptation resources. Your contributions are always welcome!
The objective of Continual Test-time Domain Adaptation. (CTDA) is to gradually adapt a pre-trained model to a se- quence of target domains without accessing ...
Awesome Continual Test-Time Adaptation. This repository organizes papers related to the CTTA(Continual-Test-Time-Adaptation) by SUSI-Lab.
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We aim for source-free domain adaptation, where the task is to deploy a model pre-trained on source domains to target domains. The challenges stem from the.
Dec 5, 2023 · The paper suggests a new large-scale continual test-time adaptation benchmark dataset, considering corruption interpolation, scale variation, and repetition.
Missing: Variational | Show results with:Variational
Sep 12, 2024 · Continual Test-Time Adaptation (CTTA) is an emerging and challenging task where a model trained in a source domain must adapt to ...
We propose a continual test-time adaptation approach which can effectively adapt off-the-shelf source pre- trained models to continually changing target data. • ...
Missing: Variational | Show results with:Variational