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Adversarial Domain Adaptation with Domain Mixup
<p align="center"> <img src="docs/model.png" /> </p> <br>This is the implementation of Adversarial Domain Adaptation with Domain Mixup in PyTorch. This work is accepted as Oral presentation at AAAI 2020.
Adversarial Domain Adaptation with Domain Mixup: [Paper (arxiv)].
<br>Getting Started
- We combine Domain Mixup strategy with a classical adversarial domain adaptation method, RevGrad, to showcase its effectiveness on boosting feature alignment. Details are presented in the Mixup_RevGrad folder.
- The proposed DM-ADA approach utilizes a VAE-GAN based framework and performs Domain Mixup on both pixel and feature level. Details are presented in the DM-ADA folder. Some typical generations from source, target and mixup features are as follows (VisDA-2017 dataset is employed).
Citation
If this work helps your research, please cite the following paper.
@inproceedings{xu2020adversarial,
author = {Minghao Xu and Jian Zhang and Bingbing Ni and Teng Li and Chengjie Wang and Qi Tian and Wenjun Zhang},
title = {Adversarial Domain Adaptation with Domain Mixup},
booktitle = {The Thirty-Fourth AAAI Conference on Artificial Intelligence},
pages = {6502--6509},
publisher = {AAAI Press},
year = {2020}
}