[Improvement] Add tags for each README.md (#340)

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## Introduction
[ALGORITHM]
```latex
@inproceedings{annn,
author = {Zhen Zhu and

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## Introduction
[ALGORITHM]
```latex
@InProceedings{He_2019_CVPR,
author = {He, Junjun and Deng, Zhongying and Zhou, Lei and Wang, Yali and Qiao, Yu},

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## Introduction
[ALGORITHM]
```latex
@article{huang2018ccnet,
title={CCNet: Criss-Cross Attention for Semantic Segmentation},

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## Introduction
[ALGORITHM]
```latext
@article{wu2018cgnet,
title={CGNet: A Light-weight Context Guided Network for Semantic Segmentation},

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## Introduction
[ALGORITHM]
```latex
@article{fu2018dual,
title={Dual Attention Network for Scene Segmentation},

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## Introduction
[ALGORITHM]
```latext
@article{chen2017rethinking,
title={Rethinking atrous convolution for semantic image segmentation},

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## Introduction
[ALGORITHM]
```latex
@inproceedings{deeplabv3plus2018,
title={Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation},

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## Introduction
[ALGORITHM]
```latex
@InProceedings{He_2019_ICCV,
author = {He, Junjun and Deng, Zhongying and Qiao, Yu},

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## Introduction
[ALGORITHM]
This example is to reproduce ["Disentangled Non-Local Neural Networks"](https://arxiv.org/abs/2006.06668) for semantic segmentation. It is still in progress.
## Citation

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## Introduction
[ALGORITHM]
```latex
@inproceedings{li2019expectation,
title={Expectation-maximization attention networks for semantic segmentation},

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## Introduction
[ALGORITHM]
```latex
@InProceedings{Zhang_2018_CVPR,
author = {Zhang, Hang and Dana, Kristin and Shi, Jianping and Zhang, Zhongyue and Wang, Xiaogang and Tyagi, Ambrish and Agrawal, Amit},

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## Introduction
[ALGORITHM]
```latex
@article{poudel2019fast,
title={Fast-scnn: Fast semantic segmentation network},

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## Introduction
[ALGORITHM]
```latex
@article{shelhamer2017fully,
title={Fully convolutional networks for semantic segmentation},

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## Introduction
[ALGORITHM]
```latex
@article{micikevicius2017mixed,
title={Mixed precision training},

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## Introduction
[ALGORITHM]
```latex
@inproceedings{cao2019gcnet,
title={Gcnet: Non-local networks meet squeeze-excitation networks and beyond},

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## Introduction
[ALGORITHM]
```latext
@inproceedings{SunXLW19,
title={Deep High-Resolution Representation Learning for Human Pose Estimation},

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## Introduction
[ALGORITHM]
```latex
@inproceedings{sandler2018mobilenetv2,
title={Mobilenetv2: Inverted residuals and linear bottlenecks},

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## Introduction
[ALGORITHM]
```latex
@inproceedings{Howard_2019_ICCV,
title={Searching for MobileNetV3},

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## Introduction
[ALGORITHM]
```latex
@inproceedings{wang2018non,
title={Non-local neural networks},

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## Introduction
[ALGORITHM]
```latex
@article{YuanW18,
title={Ocnet: Object context network for scene parsing},

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## Introduction
[ALGORITHM]
```
@misc{alex2019pointrend,
title={PointRend: Image Segmentation as Rendering},

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## Introduction
[ALGORITHM]
```latex
@inproceedings{zhao2018psanet,
title={Psanet: Point-wise spatial attention network for scene parsing},

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## Introduction
[ALGORITHM]
```latex
@inproceedings{zhao2017pspnet,
title={Pyramid Scene Parsing Network},

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## Introduction
[ALGORITHM]
```latex
@article{zhang2020resnest,
title={ResNeSt: Split-Attention Networks},

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## Introduction
[ALGORITHM]
```latex
@article{Kirillov_2019,
title={Panoptic Feature Pyramid Networks},

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## Introduction
[ALGORITHM]
```latex
@inproceedings{ronneberger2015u,
title={U-net: Convolutional networks for biomedical image segmentation},

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## Introduction
[ALGORITHM]
```latex
@inproceedings{xiao2018unified,
title={Unified perceptual parsing for scene understanding},