Open Compound Domain Adaptation

[Project] [Paper]

Overview

Open Compound Domain Adaptation (OCDA) is the author's re-implementation of the compound domain adaptator described in:
"Open Compound Domain Adaptation"
Ziwei Liu^*,  Zhongqi Miao^*,  Xingang Pan,  Xiaohang Zhan,  Dahua Lin,  Stella X. Yu,  Boqing Gong  (CUHK & Berkeley & Google)  in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2020, Oral Presentation

Further information please contact Zhongqi Miao and Ziwei Liu.

Requirements

• PyTorch (version >= 0.4.1)
• scikit-learn

Data Preparation

Getting Started (Training & Testing)

C-Digits

C-Faces

Reproduced Benchmarks and Model Zoo

C-Digits

Source	MNIST (C)	MNIST-M (C)	USPS (C)	SymNum (O)	Avg. Acc	Download
SVHN						model

C-Faces

Source	C08 (C)	C09 (C)	C13 (C)	C14 (C)	C19 (O)	Avg. Acc	Download
C05							model

License and Citation

The use of this software is released under BSD-3.

@inproceedings{compounddomainadaptation,
  title={Open Compound Domain Adaptation},
  author={Liu, Ziwei and Miao, Zhongqi and Pan, Xingang and Zhan, Xiaohang and Lin, Dahua and Yu, Stella X. and Gong, Boqing},
  booktitle={IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2020}
}