diff --git a/README.md b/README.md
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 PaddleClas is a toolset for image classification tasks prepared for the industry and academia. It helps users train better computer vision models and apply them in real scenarios.
 
+
+**Note**: Baidu proposed a new image classification network structure **`Hs-ResNet`**, which reaches 81.3% on ImageNet-1k dataset, while its `params` is almost same as `ResNet50`.The arxiv link is here: [HS-ResNet: Hierarchical-Split Block on Convolutional Neural Network](https://arxiv.org/pdf/2010.07621.pdf). The model structure and the pretrained weights are coming soon!
+
 **Recent update**
 - 2020.09.17 Add `Res2Net50_vd_26w_4s_ssld` pretrained model, whose Top-1 Acc on ImageNet-1k dataset reaches 83.1%. Add `Res2Net101_vd_26w_4s_ssld` pretrained model, whose Top-1 Acc on ImageNet-1k dataset reaches 83.9%.
 - 2020.10.12 Add Paddle-Lite demo。
diff --git a/README_cn.md b/README_cn.md
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 飞桨图像分类套件PaddleClas是飞桨为工业界和学术界所准备的一个图像分类任务的工具集，助力使用者训练出更好的视觉模型和应用落地。
 
+
+**注意**: 百度提出了一个新的图像分类网络结构**`HS-ResNet`**，基于ImageNet-1k数据集，`Hs-ResNet`在与`ResNet`的params相近的情况下，Top-1 Acc达到了81.3%，相应的Arxiv文章链接可以参考这里：[HS-ResNet: Hierarchical-Split Block on Convolutional Neural Network](https://arxiv.org/pdf/2010.07621.pdf)，模型结构和预训练模型参数即将开源，敬请期待！
+
 **近期更新**
 - 2020.10.20 添加 `Res2Net50_vd_26w_4s_ssld `模型，在ImageNet-1k上Top-1 Acc可达83.1%；添加 `Res2Net101_vd_26w_4s_ssld `模型，在ImageNet-1k上Top-1 Acc可达83.9%。
 - 2020.10.12 添加Paddle-Lite demo。
diff --git a/docs/images/models/T4_benchmark/t4.fp32.bs4.main_fps_top1.png b/docs/images/models/T4_benchmark/t4.fp32.bs4.main_fps_top1.png
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