Official repository of the ICCV 2023 paper "ClusT3: Information Invariant Test-Time Training", by Gustavo A. Vargas Hakim, David Osowiechi, Mehrdad Noori, Milad Cheraghalikhani, Ali Bahri, Ismail Ben Ayed, and Christian Desrosiers. The whole article can be found here. This work was greatly inspired by the code in TTTFlow.
We propose a novel unsupervised TTT technique based on the maximization of Mutual Information between multi-scale feature maps and a discrete latent representation, which can be integrated to the standard training as an auxiliary clustering task.
The repository is divided into two directories: one for the datasets under CIFAR-10 and CIFAR-100 and one for the dataset ViSDA-C. Details of how each code works can be found in their respective READMEs.
If you found this repository, or its related paper useful for your research, you can cite this work as:
@inproceedings{ClusT32023,
title={ClusT3: Information Invariant Test-Time Training},
author={Gustavo A. Vargas Hakim and David Osowiechi and Mehrdad Noori and Milad Cheraghalikhani and Ali Bahri and Ismail Ben Ayed and Christian Desrosiers},
booktitle={***},
pages={},
month={October},
year={2023}
}