CVOct 9, 2019
MixMatch Domain Adaptaion: Prize-winning solution for both tracks of VisDA 2019 challenge
arXiv:1910.03903v113 citationsHas Code
Originality Synthesis-oriented
AI Analysis
This work addresses domain adaptation for computer vision tasks, but it is incremental as it builds on existing methods to win a specific challenge.
The paper tackled domain adaptation in multi-source and semi-supervised settings, achieving 2nd place on the multi-source track and 3rd place on the semi-supervised track of the VisDA 2019 challenge.
We present a domain adaptation (DA) system that can be used in multi-source and semi-supervised settings. Using the proposed method we achieved 2nd place on multi-source track and 3rd place on semi-supervised track of the VisDA 2019 challenge (http://ai.bu.edu/visda-2019/). The source code of the method is available at https://github.com/filaPro/visda2019.