KO | EN

GitLite

Minimalist Open Source Repository Search Engine

gitlite — search

#dsh #dsh-plugin #ai-agent #developer-tools #codex #typescript #cli #deepseek-harness #claude-code #ai-agents #mcp #rust

ITTA

★ 34 Open GitHub ↗

Official code for the CVPR23 paper: "Improved Test-Time Adaptation for Domain Generalization"

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# Improved Test-Time Adaptation for Domain Generalization (CVPR'23)

Official PyTorch implementation of [Improved Test-Time Adaptation for Domain Generalization](https://arxiv.org/abs/2304.04494).

Liang Chen, Yong Zhang, Yibing Song, Ying Shan, and Lingqiao Liu

## Preparation

### Dependencies

```sh
pip install -r requirements.txt
```

### Datasets

```sh
python -m domainbed.scripts.download --data_dir=/my/datasets/path
```

### Environments

Environment details used for the main experiments. Every main experiment is conducted on a single NVIDIA V100 GPU.

```
Environment:
	Python: 3.7.7
	PyTorch: 1.7.1
	Torchvision: 0.8.2
	CUDA: 10.1
	CUDNN: 7603
	NumPy: 1.21.4
	PIL: 7.2.0
```

## How to run, and collect results

Please refer to details in the original project page: [Domainbed](https://github.com/facebookresearch/DomainBed)

## Citation

```
@inproceedings{chen2023improved,
  title={Improved Test-Time Adaptation for Domain Generalization},
  author={Chen, Liang and Zhang, Yong and Song, Yibing and Shan, Ying and Liu, Lingqiao},
  booktitle={CVPR},
  year={2023}
}

```

Please contact me via email (liangchen527@gmail.com) if your have any questions regarding this project.

ITTA

Explore Similar Repositories

Was this content helpful?

Recent Feedback

Download README