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Add some publish information of implemented models (open-mmlab#508)
* Add some publish information * Fix some readme omission.
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‎README.md‎

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Supported backbones:
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- [x] ResNet
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- [x] ResNeXt
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- [x] [HRNet](configs/hrnet/README.md)
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- [x] [ResNeSt](configs/resnest/README.md)
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- [x] [MobileNetV2](configs/mobilenet_v2/README.md)
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- [x] [MobileNetV3](configs/mobilenet_v3/README.md)
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- [x] ResNet (CVPR'2016)
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- [x] ResNeXt (CVPR'2017)
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- [x] [HRNet (CVPR'2019)](configs/hrnet/README.md)
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- [x] [ResNeSt (ArXiv'2020)](configs/resnest/README.md)
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- [x] [MobileNetV2 (CVPR'2018)](configs/mobilenet_v2/README.md)
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- [x] [MobileNetV3 (ICCV'2019)](configs/mobilenet_v3/README.md)
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Supported methods:
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- [x] [FCN](configs/fcn)
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- [x] [PSPNet](configs/pspnet)
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- [x] [DeepLabV3](configs/deeplabv3)
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- [x] [PSANet](configs/psanet)
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- [x] [DeepLabV3+](configs/deeplabv3plus)
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- [x] [UPerNet](configs/upernet)
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- [x] [NonLocal Net](configs/nonlocal_net)
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- [x] [EncNet](configs/encnet)
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- [x] [CCNet](configs/ccnet)
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- [x] [DANet](configs/danet)
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- [x] [APCNet](configs/apcnet)
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- [x] [GCNet](configs/gcnet)
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- [x] [DMNet](configs/dmnet)
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- [x] [ANN](configs/ann)
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- [x] [OCRNet](configs/ocrnet)
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- [x] [Fast-SCNN](configs/fastscnn)
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- [x] [Semantic FPN](configs/sem_fpn)
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- [x] [PointRend](configs/point_rend)
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- [x] [EMANet](configs/emanet)
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- [x] [DNLNet](configs/dnlnet)
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- [x] [CGNet](configs/cgnet)
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- [x] [Mixed Precision (FP16) Training](configs/fp16/README.md)
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- [x] [FCN (CVPR'2015/TPAMI'2017)](configs/fcn)
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- [x] [UNet (MICCAI'2016/Nat. Methods'2019)](configs/unet)
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- [x] [PSPNet (CVPR'2017)](configs/pspnet)
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- [x] [DeepLabV3 (CVPR'2017)](configs/deeplabv3)
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- [x] [Mixed Precision (FP16) Training (ArXiv'2017)](configs/fp16/README.md)
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- [x] [PSANet (ECCV'2018)](configs/psanet)
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- [x] [DeepLabV3+ (CVPR'2018)](configs/deeplabv3plus)
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- [x] [UPerNet (ECCV'2018)](configs/upernet)
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- [x] [NonLocal Net (CVPR'2018)](configs/nonlocal_net)
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- [x] [EncNet (CVPR'2018)](configs/encnet)
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- [x] [Semantic FPN (CVPR'2019)](configs/sem_fpn)
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- [x] [DANet (CVPR'2019)](configs/danet)
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- [x] [APCNet (CVPR'2019)](configs/apcnet)
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- [x] [EMANet (ICCV'2019)](configs/emanet)
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- [x] [CCNet (ICCV'2019)](configs/ccnet)
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- [x] [DMNet (ICCV'2019)](configs/dmnet)
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- [x] [ANN (ICCV'2019)](configs/ann)
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- [x] [GCNet (ICCVW'2019/TPAMI'2020)](configs/gcnet)
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- [x] [Fast-SCNN (ArXiv'2019)](configs/fastscnn)
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- [x] [OCRNet (ECCV'2020)](configs/ocrnet)
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- [x] [DNLNet (ECCV'2020)](configs/dnlnet)
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- [x] [PointRend (CVPR'2020)](configs/point_rend)
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- [x] [CGNet (TIP'2020)](configs/cgnet)
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## Installation
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‎README_zh-CN.md‎

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已支持的骨干网络：
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- [x] ResNet
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- [x] ResNeXt
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- [x] [HRNet](configs/hrnet/README.md)
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- [x] [ResNeSt](configs/resnest/README.md)
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- [x] [MobileNetV2](configs/mobilenet_v2/README.md)
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- [x] [MobileNetV3](configs/mobilenet_v3/README.md)
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- [x] ResNet (CVPR'2016)
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- [x] ResNeXt (CVPR'2017)
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- [x] [HRNet (CVPR'2019)](configs/hrnet/README.md)
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- [x] [ResNeSt (ArXiv'2020)](configs/resnest/README.md)
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- [x] [MobileNetV2 (CVPR'2018)](configs/mobilenet_v2/README.md)
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- [x] [MobileNetV3 (ICCV'2019)](configs/mobilenet_v3/README.md)
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已支持的算法：
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- [x] [FCN](configs/fcn)
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- [x] [PSPNet](configs/pspnet)
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- [x] [DeepLabV3](configs/deeplabv3)
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- [x] [PSANet](configs/psanet)
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- [x] [DeepLabV3+](configs/deeplabv3plus)
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- [x] [UPerNet](configs/upernet)
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- [x] [NonLocal Net](configs/nonlocal_net)
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- [x] [EncNet](configs/encnet)
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- [x] [CCNet](configs/ccnet)
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- [x] [DANet](configs/danet)
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- [x] [APCNet](configs/apcnet)
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- [x] [GCNet](configs/gcnet)
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- [x] [DMNet](configs/dmnet)
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- [x] [ANN](configs/ann)
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- [x] [OCRNet](configs/ocrnet)
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- [x] [Fast-SCNN](configs/fastscnn)
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- [x] [Semantic FPN](configs/sem_fpn)
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- [x] [PointRend](configs/point_rend)
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- [x] [EMANet](configs/emanet)
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- [x] [DNLNet](configs/dnlnet)
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- [x] [CGNet](configs/cgnet)
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- [x] [Mixed Precision (FP16) Training](configs/fp16/README.md)
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- [x] [FCN (CVPR'2015/TPAMI'2017)](configs/fcn)
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- [x] [PSPNet (CVPR'2017)](configs/pspnet)
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- [x] [DeepLabV3 (CVPR'2017)](configs/deeplabv3)
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- [x] [Mixed Precision (FP16) Training (ArXiv'2017)](configs/fp16/README.md)
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- [x] [PSANet (ECCV'2018)](configs/psanet)
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- [x] [DeepLabV3+ (CVPR'2018)](configs/deeplabv3plus)
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- [x] [UPerNet (ECCV'2018)](configs/upernet)
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- [x] [NonLocal Net (CVPR'2018)](configs/nonlocal_net)
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- [x] [EncNet (CVPR'2018)](configs/encnet)
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- [x] [Semantic FPN (CVPR'2019)](configs/sem_fpn)
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- [x] [DANet (CVPR'2019)](configs/danet)
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- [x] [APCNet (CVPR'2019)](configs/apcnet)
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- [x] [EMANet (ICCV'2019)](configs/emanet)
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- [x] [CCNet (ICCV'2019)](configs/ccnet)
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- [x] [DMNet (ICCV'2019)](configs/dmnet)
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- [x] [ANN (ICCV'2019)](configs/ann)
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- [x] [GCNet (ICCVW'2019/TPAMI'2020)](configs/gcnet)
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- [x] [Fast-SCNN (ArXiv'2019)](configs/fastscnn)
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- [x] [OCRNet (ECCV'2020)](configs/ocrnet)
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- [x] [DNLNet (ECCV'2020)](configs/dnlnet)
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- [x] [PointRend (CVPR'2020)](configs/point_rend)
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- [x] [CGNet (TIP'2020)](configs/cgnet)
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## 安装
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‎configs/cgnet/README.md‎

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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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author={Wu, Tianyi and Tang, Sheng and Zhang, Rui and Zhang, Yongdong},
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journal={arXiv preprint arXiv:1811.08201},
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year={2018}
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@article{wu2020cgnet,
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title={Cgnet: A light-weight context guided network for semantic segmentation},
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author={Wu, Tianyi and Tang, Sheng and Zhang, Rui and Cao, Juan and Zhang, Yongdong},
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journal={IEEE Transactions on Image Processing},
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volume={30},
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pages={1169--1179},
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year={2020},
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publisher={IEEE}
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}
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```
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‎configs/point_rend/README.md‎

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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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author={Alexander Kirillov and Yuxin Wu and Kaiming He and Ross Girshick},
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year={2019},
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eprint={1912.08193},
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archivePrefix={arXiv},
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primaryClass={cs.CV}
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@inproceedings{kirillov2020pointrend,
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title={Pointrend: Image segmentation as rendering},
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author={Kirillov, Alexander and Wu, Yuxin and He, Kaiming and Girshick, Ross},
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booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
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pages={9799--9808},
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year={2020}
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}
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```
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‎configs/unet/README.md‎

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### CHASE_DB1
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| Backbone | Head | Image Size | Crop Size | Stride | Lr schd | Mem (GB) | Inf time (fps) | Dice | download |
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| ----------- | --------- | ---------- | --------- | -----: | ------- | -------- | -------------: | ----: | ------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| Backbone | Head | Image Size | Crop Size | Stride | Lr schd | Mem (GB) | Inf time (fps) | Dice | config | download |
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| ----------- | --------- | ---------- | --------- | -----: | ------- | -------- | -------------: | ----: | -------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
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| UNet-S5-D16 | FCN | 960x999 | 128x128 | 85x85 | 40000 | 0.968 | - | 80.24 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/unet/fcn_unet_s5-d16_128x128_40k_chase_db1.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/fcn_unet_s5-d16_128x128_40k_chase_db1/fcn_unet_s5-d16_128x128_40k_chase_db1_20201223_191051-95852f45.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/fcn_unet_s5-d16_128x128_40k_chase_db1/fcn_unet_s5-d16_128x128_40k_chase_db1-20201223_191051.log.json) |
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| UNet-S5-D16 | PSPNet | 960x999 | 128x128 | 85x85 | 40000 | 0.982 | - | 80.36 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/unet/pspnet_unet_s5-d16_128x128_40k_chase_db1.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/pspnet_unet_s5-d16_128x128_40k_chase_db1/pspnet_unet_s5-d16_128x128_40k_chase_db1_20201227_181818-68d4e609.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/pspnet_unet_s5-d16_128x128_40k_chase_db1/pspnet_unet_s5-d16_128x128_40k_chase_db1-20201227_181818.log.json) |
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| UNet-S5-D16 | DeepLabV3 | 960x999 | 128x128 | 85x85 | 40000 | 0.999 | - | 80.47 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/unet/deeplabv3_unet_s5-d16_128x128_40k_chase_db1.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/deeplabv3_unet_s5-d16_128x128_40k_chase_db1/deeplabv3_unet_s5-d16_128x128_40k_chase_db1_20201226_094047-4c5aefa3.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/deeplabv3_unet_s5-d16_128x128_40k_chase_db1/deeplabv3_unet_s5-d16_128x128_40k_chase_db1-20201226_094047.log.json) |
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### HRF
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| Backbone | Head | Image Size | Crop Size | Stride | Lr schd | Mem (GB) | Inf time (fps) | Dice | download |
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| ----------- | --------- | ---------- | --------- | ------: | ------- | -------- | -------------: | ----: | ------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| Backbone | Head | Image Size | Crop Size | Stride | Lr schd | Mem (GB) | Inf time (fps) | Dice | config | download |
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| ----------- | --------- | ---------- | --------- | -----: | ------- | -------- | -------------: | ----: | -------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
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| UNet-S5-D16 | FCN | 2336x3504 | 256x256 | 170x170 | 40000 | 2.525 | - | 79.45 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/unet/fcn_unet_s5-d16_256x256_40k_hrf.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/fcn_unet_s5-d16_256x256_40k_hrf/fcn_unet_s5-d16_256x256_40k_hrf_20201223_173724-df3ec8c4.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/fcn_unet_s5-d16_256x256_40k_hrf/fcn_unet_s5-d16_256x256_40k_hrf-20201223_173724.log.json) |
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| UNet-S5-D16 | PSPNet | 2336x3504 | 256x256 | 170x170 | 40000 | 2.588 | - | 80.07 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/unet/pspnet_unet_s5-d16_256x256_40k_hrf.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/pspnet_unet_s5-d16_256x256_40k_hrf/pspnet_unet_s5-d16_256x256_40k_hrf_20201227_181818-fdb7e29b.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/pspnet_unet_s5-d16_256x256_40k_hrf/pspnet_unet_s5-d16_256x256_40k_hrf-20201227_181818.log.json) |
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| UNet-S5-D16 | DeepLabV3 | 2336x3504 | 256x256 | 170x170 | 40000 | 2.604 | - | 80.21 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/unet/deeplabv3_unet_s5-d16_256x256_40k_hrf.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/deeplabv3_unet_s5-d16_256x256_40k_hrf/deeplabv3_unet_s5-d16_256x256_40k_hrf_20201226_094047-3a1fdf85.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/deeplabv3_unet_s5-d16_256x256_40k_hrf/deeplabv3_unet_s5-d16_256x256_40k_hrf-20201226_094047.log.json) |

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