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: 9 days ago
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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}

}

```