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README.md

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@@ -8,6 +8,9 @@ The *official* implementation for the [Mutual Mean-Teaching: Pseudo Label Refine
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![framework](figs/framework.png)
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## What's New
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#### [Jul 1st, 2020]
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+ We did the code refactoring to support distributed training and more features. Please see [OpenUnReID](https://github.com/open-mmlab/OpenUnReID).
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#### [Mar 27th, 2020]
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+ We wrote a Chinese blog about this paper at [[Zhihu]](https://zhuanlan.zhihu.com/p/116074945).
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+ We discovered **a minor hint**, changing the setting of `--dropout` from `0` to `0.5` will achieve supervising improvements in MMT. Intuitively, the dual models are more de-coupled with independent dropout functions.
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+ A reminder here, changing the hyper-parameter `--soft-tri-weight 0.8` to `--soft-tri-weight 1.0` may achieve better performance in some cases. Please refer to ablation study results in Table 2 in our paper.
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## Installation
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```shell
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*Source-domain pre-trained models and all our MMT models in the paper can be downloaded from the [link](https://drive.google.com/open?id=1WC4JgbkaAr40uEew_JEqjUxgKIiIQx-W).*
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![results](figs/results.png)
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## TODO
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- [x] Support DBSCAN-based training
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- [ ] Further accelerate the clustering process
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- [ ] Support training with more datasets
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- [ ] Support pure unsupervised training
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## Citation

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