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 ### Recent Update
 
-  **`2018.02.07`**: We evaluate LFW,CFP,AgeDB-30 again after removing training set overlaps, the results almost stay the same. See [Results](#results) for detail.
+  **`2018.02.13`**: We achieved state-of-the-art performance on [MegaFace-Challenge-1](http://megaface.cs.washington.edu/results/facescrub.html), at `98.06%`. Also note that the training set we used has NO identities overlap with facescrub, please check our paper for detail.
+
+  **`2018.02.07`**: We evaluate LFW,CFP,AgeDB-30 again after removing training set overlaps, the results almost stay the same. See [Results](#results) for detail.
 
   **`2018.01.30`**: We provide a *LResNet50E-IR* model which can achieve **`99.80@LFW`** and **`97.64%`** at MegaFace 1M Acc. See [Pretrained-Models](#pretrained-models) for detail.