Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/tim-learn/awesome-test-time-adaptation
Collection of awesome test-time (domain/batch/instance) adaptation methods
https://github.com/tim-learn/awesome-test-time-adaptation
List: awesome-test-time-adaptation
continual-test-time-adaptation distribution-shift domain-adaptation domain-generalization source-free-domain-adaptation test-time-adaptation test-time-augmentation test-time-training transfer-learning
Last synced: 7 days ago
JSON representation
Collection of awesome test-time (domain/batch/instance) adaptation methods
- Host: GitHub
- URL: https://github.com/tim-learn/awesome-test-time-adaptation
- Owner: tim-learn
- License: mit
- Created: 2021-12-14T06:14:08.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2024-05-10T02:43:34.000Z (6 months ago)
- Last Synced: 2024-05-19T14:00:56.759Z (6 months ago)
- Topics: continual-test-time-adaptation, distribution-shift, domain-adaptation, domain-generalization, source-free-domain-adaptation, test-time-adaptation, test-time-augmentation, test-time-training, transfer-learning
- Homepage:
- Size: 734 KB
- Stars: 521
- Watchers: 16
- Forks: 40
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Awesome Test-Time Adaptation [![Awesome](https://awesome.re/badge.svg)](https://awesome.re)
A curated list of awesome test-time (**domain/ batch/ instance/ online/ prior**) adaptation resources. Your contributions are always welcome!
## Problem
![avatar](TTA.png)## Contents
- [Test-Time (Source-Free) Domain Adaptation (SFDA)](./TTA-SFDA.md)- [Test-Time Batch Adaptation (TTBA)](./TTA-TTBA.md/#Batch-level)
- [Test-Time Instance Adaptation (TTIA)](./TTA-TTBA.md/#Instance-level)
- [Online Test-Time Adaptation (OTTA)](./TTA-OTTA.md)
- [Test-Time Prior Adaptation (TTPA)](./TTA-TTPA.md)
## Datasets
A list of commonly used datasets in TTA is available in [Google Sheets](https://docs.google.com/spreadsheets/d/10tOlFDA5hLSpyv5Wv8zRcXSbUEDLfxP-YhU82AZvYJo/edit?usp=sharing).## Citation
If you find our survey and repository useful for your research, please consider citing our paper:
```bibtex
@article{liang2023ttasurvey,
title={A Comprehensive Survey on Test-Time Adaptation under Distribution Shifts},
author={Liang, Jian and He, Ran and Tan, Tieniu},
journal={International Journal Of Computer Vision},
year={2023}
}
```