EcoTTA: Memory-Efficient Continual Test-Time Adaptation via Self-Distilled Regularization
Korea Advanced Institute of Science and Technology · Qualcomm (United Kingdom) · Kootenay Association for Science & Technology
- 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
- 2023-06-01
- 175
@inproceedings{song2023ecotta,
title = {EcoTTA: Memory-Efficient Continual Test-Time Adaptation via Self-Distilled Regularization},
author = {Junha Song and Jungsoo Lee and In So Kweon and Sungha Choi},
year = {2023},
booktitle = {2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
eprint = {2303.01904},
archivePrefix = {arXiv},
doi = {10.1109/CVPR52729.2023.01147},
url = {https://arxiv.org/abs/2303.01904},
}