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## Introduction
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[ALGORITHM]
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```latex
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@inproceedings{annn,
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author = {Zhen Zhu and
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## Introduction
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[ALGORITHM]
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```latex
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@InProceedings{He_2019_CVPR,
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author = {He, Junjun and Deng, Zhongying and Zhou, Lei and Wang, Yali and Qiao, Yu},
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## Introduction
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[ALGORITHM]
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```latex
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@article{huang2018ccnet,
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title={CCNet: Criss-Cross Attention for Semantic Segmentation},
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## Introduction
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[ALGORITHM]
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```latext
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@article{wu2018cgnet,
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title={CGNet: A Light-weight Context Guided Network for Semantic Segmentation},
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## Introduction
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[ALGORITHM]
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```latex
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@article{fu2018dual,
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title={Dual Attention Network for Scene Segmentation},
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## Introduction
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[ALGORITHM]
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```latext
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@article{chen2017rethinking,
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title={Rethinking atrous convolution for semantic image segmentation},
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## Introduction
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[ALGORITHM]
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```latex
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@inproceedings{deeplabv3plus2018,
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title={Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation},
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## Introduction
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[ALGORITHM]
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```latex
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@InProceedings{He_2019_ICCV,
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author = {He, Junjun and Deng, Zhongying and Qiao, Yu},
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## Introduction
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[ALGORITHM]
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This example is to reproduce ["Disentangled Non-Local Neural Networks"](https://arxiv.org/abs/2006.06668) for semantic segmentation. It is still in progress.
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## Citation
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## Introduction
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[ALGORITHM]
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```latex
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@inproceedings{li2019expectation,
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title={Expectation-maximization attention networks for semantic segmentation},
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## Introduction
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[ALGORITHM]
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```latex
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@InProceedings{Zhang_2018_CVPR,
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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
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[ALGORITHM]
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```latex
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@article{poudel2019fast,
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title={Fast-scnn: Fast semantic segmentation network},
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## Introduction
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[ALGORITHM]
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```latex
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@article{shelhamer2017fully,
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title={Fully convolutional networks for semantic segmentation},
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## Introduction
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[ALGORITHM]
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```latex
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@article{micikevicius2017mixed,
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title={Mixed precision training},
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## Introduction
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[ALGORITHM]
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```latex
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@inproceedings{cao2019gcnet,
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title={Gcnet: Non-local networks meet squeeze-excitation networks and beyond},
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## Introduction
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[ALGORITHM]
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```latext
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@inproceedings{SunXLW19,
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title={Deep High-Resolution Representation Learning for Human Pose Estimation},
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## Introduction
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[ALGORITHM]
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```latex
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@inproceedings{sandler2018mobilenetv2,
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title={Mobilenetv2: Inverted residuals and linear bottlenecks},
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## Introduction
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[ALGORITHM]
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```latex
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@inproceedings{Howard_2019_ICCV,
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title={Searching for MobileNetV3},
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## Introduction
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[ALGORITHM]
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```latex
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@inproceedings{wang2018non,
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title={Non-local neural networks},
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## Introduction
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[ALGORITHM]
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```latex
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@article{YuanW18,
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title={Ocnet: Object context network for scene parsing},
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## Introduction
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[ALGORITHM]
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```
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@misc{alex2019pointrend,
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title={PointRend: Image Segmentation as Rendering},
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## Introduction
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[ALGORITHM]
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```latex
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@inproceedings{zhao2018psanet,
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title={Psanet: Point-wise spatial attention network for scene parsing},
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## Introduction
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[ALGORITHM]
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```latex
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@inproceedings{zhao2017pspnet,
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title={Pyramid Scene Parsing Network},
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## Introduction
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[ALGORITHM]
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```latex
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@article{zhang2020resnest,
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title={ResNeSt: Split-Attention Networks},
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## Introduction
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[ALGORITHM]
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```latex
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@article{Kirillov_2019,
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title={Panoptic Feature Pyramid Networks},
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## Introduction
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[ALGORITHM]
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```latex
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@inproceedings{ronneberger2015u,
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title={U-net: Convolutional networks for biomedical image segmentation},
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## Introduction
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[ALGORITHM]
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```latex
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@inproceedings{xiao2018unified,
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title={Unified perceptual parsing for scene understanding},
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