[
  {
    "path": "README.md",
    "content": "[![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)\n\n# Awesome Semantic Segmentation\n\n## Networks by architecture\n### Semantic segmentation\n- U-Net [https://arxiv.org/pdf/1505.04597.pdf] [2015]\n\t+ https://github.com/zhixuhao/unet [Keras][![GitHub stars](https://img.shields.io/github/stars/zhixuhao/unet.svg?logo=github&label=Stars)](https://github.com/zhixuhao/unet)\n\t+ https://github.com/jocicmarko/ultrasound-nerve-segmentation [Keras][![GitHub stars](https://img.shields.io/github/stars/jocicmarko/ultrasound-nerve-segmentation.svg?logo=github&label=Stars)](https://github.com/jocicmarko/ultrasound-nerve-segmentation)\n\t+ https://github.com/EdwardTyantov/ultrasound-nerve-segmentation [Keras][![GitHub stars](https://img.shields.io/github/stars/EdwardTyantov/ultrasound-nerve-segmentation.svg?logo=github&label=Stars)](https://github.com/EdwardTyantov/ultrasound-nerve-segmentation)\n\t+ https://github.com/ZFTurbo/ZF_UNET_224_Pretrained_Model [Keras][![GitHub stars](https://img.shields.io/github/stars/ZFTurbo/ZF_UNET_224_Pretrained_Model.svg?logo=github&label=Stars)](https://github.com/ZFTurbo/ZF_UNET_224_Pretrained_Model)\n\t+ https://github.com/yihui-he/u-net [Keras][![GitHub stars](https://img.shields.io/github/stars/yihui-he/u-net.svg?logo=github&label=Stars)](https://github.com/yihui-he/u-net)\n\t+ https://github.com/jakeret/tf_unet [Tensorflow][![GitHub stars](https://img.shields.io/github/stars/jakeret/tf_unet.svg?logo=github&label=Stars)](https://github.com/jakeret/tf_unet)\n\t+ https://github.com/divamgupta/image-segmentation-keras [Keras][![GitHub stars](https://img.shields.io/github/stars/divamgupta/image-segmentation-keras.svg?logo=github&label=Stars)](https://github.com/divamgupta/image-segmentation-keras)\n\t+ https://github.com/ZijunDeng/pytorch-semantic-segmentation [PyTorch][![GitHub stars](https://img.shields.io/github/stars/ZijunDeng/pytorch-semantic-segmentation.svg?logo=github&label=Stars)](https://github.com/ZijunDeng/pytorch-semantic-segmentation)\n\t+ https://github.com/akirasosa/mobile-semantic-segmentation [Keras][![GitHub stars](https://img.shields.io/github/stars/akirasosa/mobile-semantic-segmentation.svg?logo=github&label=Stars)](https://github.com/akirasosa/mobile-semantic-segmentation)\n\t+ https://github.com/orobix/retina-unet [Keras][![GitHub stars](https://img.shields.io/github/stars/orobix/retina-unet.svg?logo=github&label=Stars)](https://github.com/orobix/retina-unet)\n\t+ https://github.com/qureai/ultrasound-nerve-segmentation-using-torchnet [Torch][![GitHub stars](https://img.shields.io/github/stars/qureai/ultrasound-nerve-segmentation-using-torchnet.svg?logo=github&label=Stars)](https://github.com/orobix/retina-unet)\n\t+ https://github.com/ternaus/TernausNet [PyTorch][![GitHub stars](https://img.shields.io/github/stars/ternaus/TernausNet.svg?logo=github&label=Stars)](https://github.com/ternaus/TernausNet)\n\t+ https://github.com/qubvel/segmentation_models [Keras][![GitHub stars](https://img.shields.io/github/stars/qubvel/segmentation_models.svg?logo=github&label=Stars)](https://github.com/qubvel/segmentation_models)\n\t+ https://github.com/LeeJunHyun/Image_Segmentation#u-net [PyTorch][![GitHub stars](https://img.shields.io/github/stars/LeeJunHyun/Image_Segmentation.svg?logo=github&label=Stars)](https://github.com/LeeJunHyun/Image_Segmentation)\n\t+ https://github.com/yassouali/pytorch_segmentation [PyTorch][![GitHub stars](https://img.shields.io/github/stars/yassouali/pytorch_segmentation.svg?logo=github&label=Stars)](https://github.com/yassouali/pytorch_segmentation)\n\t+ https://lmb.informatik.uni-freiburg.de/people/ronneber/u-net/ [Caffe + Matlab]\n- SegNet [https://arxiv.org/pdf/1511.00561.pdf] [2016]\n\t+ https://github.com/alexgkendall/caffe-segnet [Caffe]\n\t+ https://github.com/developmentseed/caffe/tree/segnet-multi-gpu [Caffe]\n\t+ https://github.com/preddy5/segnet [Keras]\n\t+ https://github.com/imlab-uiip/keras-segnet [Keras]\n\t+ https://github.com/andreaazzini/segnet [Tensorflow]\n\t+ https://github.com/fedor-chervinskii/segnet-torch [Torch]\n\t+ https://github.com/0bserver07/Keras-SegNet-Basic [Keras]\n\t+ https://github.com/tkuanlun350/Tensorflow-SegNet [Tensorflow]\n\t+ https://github.com/divamgupta/image-segmentation-keras [Keras]\n\t+ https://github.com/ZijunDeng/pytorch-semantic-segmentation [PyTorch]\n\t+ https://github.com/chainer/chainercv/tree/master/examples/segnet [Chainer]\n\t+ https://github.com/ykamikawa/keras-SegNet [Keras]\n\t+ https://github.com/ykamikawa/tf-keras-SegNet [Keras]\n\t+ https://github.com/yassouali/pytorch_segmentation [PyTorch][![GitHub stars](https://img.shields.io/github/stars/yassouali/pytorch_segmentation)](https://github.com/yassouali/pytorch_segmentation)\n- DeepLab [https://arxiv.org/pdf/1606.00915.pdf] [2017]\n\t+ https://bitbucket.org/deeplab/deeplab-public/ [Caffe]\n\t+ https://bitbucket.org/aquariusjay/deeplab-public-ver2 [Caffe]\n\t+ https://github.com/TheLegendAli/DeepLab-Context [Caffe]\n\t+ https://github.com/msracver/Deformable-ConvNets/tree/master/deeplab [MXNet]\n\t+ https://github.com/DrSleep/tensorflow-deeplab-resnet [Tensorflow]\n\t+ https://github.com/muyang0320/tensorflow-deeplab-resnet-crf [TensorFlow]\n\t+ https://github.com/isht7/pytorch-deeplab-resnet [PyTorch]\n\t+ https://github.com/bermanmaxim/jaccardSegment [PyTorch]\n\t+ https://github.com/martinkersner/train-DeepLab [Caffe]\n\t+ https://github.com/chenxi116/TF-deeplab [Tensorflow]\n\t+ https://github.com/bonlime/keras-deeplab-v3-plus [Keras]\n\t+ https://github.com/tensorflow/models/tree/master/research/deeplab [Tensorflow]\n\t+ https://github.com/speedinghzl/pytorch-segmentation-toolbox [PyTorch]\n\t+ https://github.com/kazuto1011/deeplab-pytorch [PyTorch]\n\t+ https://github.com/youansheng/torchcv [PyTorch]\n\t+ https://github.com/yassouali/pytorch_segmentation [PyTorch][![GitHub stars](https://img.shields.io/github/stars/yassouali/pytorch_segmentation)](https://github.com/yassouali/pytorch_segmentation)\n\t+ https://github.com/hualin95/Deeplab-v3plus [PyTorch]\n- FCN [https://arxiv.org/pdf/1605.06211.pdf] [2016]\n\t+ https://github.com/vlfeat/matconvnet-fcn [MatConvNet]\n\t+ https://github.com/shelhamer/fcn.berkeleyvision.org [Caffe]\n\t+ https://github.com/MarvinTeichmann/tensorflow-fcn [Tensorflow]\n\t+ https://github.com/aurora95/Keras-FCN [Keras]\n\t+ https://github.com/mzaradzki/neuralnets/tree/master/vgg_segmentation_keras [Keras]\n\t+ https://github.com/k3nt0w/FCN_via_keras [Keras]\n\t+ https://github.com/shekkizh/FCN.tensorflow [Tensorflow]\n\t+ https://github.com/seewalker/tf-pixelwise [Tensorflow]\n\t+ https://github.com/divamgupta/image-segmentation-keras [Keras]\n\t+ https://github.com/ZijunDeng/pytorch-semantic-segmentation [PyTorch]\n\t+ https://github.com/wkentaro/pytorch-fcn [PyTorch]\n\t+ https://github.com/wkentaro/fcn [Chainer]\n\t+ https://github.com/apache/incubator-mxnet/tree/master/example/fcn-xs [MxNet]\n\t+ https://github.com/muyang0320/tf-fcn [Tensorflow]\n\t+ https://github.com/ycszen/pytorch-seg [PyTorch]\n\t+ https://github.com/Kaixhin/FCN-semantic-segmentation [PyTorch]\n\t+ https://github.com/petrama/VGGSegmentation [Tensorflow]\n\t+ https://github.com/simonguist/testing-fcn-for-cityscapes [Caffe]\n\t+ https://github.com/hellochick/semantic-segmentation-tensorflow [Tensorflow]\n\t+ https://github.com/pierluigiferrari/fcn8s_tensorflow [Tensorflow]\n\t+ https://github.com/theduynguyen/Keras-FCN [Keras]\n\t+ https://github.com/JihongJu/keras-fcn [Keras]\n\t+ https://github.com/yassouali/pytorch_segmentation [PyTorch][![GitHub stars](https://img.shields.io/github/stars/yassouali/pytorch_segmentation)](https://github.com/yassouali/pytorch_segmentation)\n- ENet [https://arxiv.org/pdf/1606.02147.pdf] [2016]\n \t+ https://github.com/TimoSaemann/ENet [Caffe]\n\t+ https://github.com/e-lab/ENet-training [Torch]\n\t+ https://github.com/PavlosMelissinos/enet-keras [Keras]\n\t+ https://github.com/fregu856/segmentation [Tensorflow]\n\t+ https://github.com/kwotsin/TensorFlow-ENet [Tensorflow]\n\t+ https://github.com/davidtvs/PyTorch-ENet [PyTorch]\n\t+ https://github.com/yassouali/pytorch_segmentation [PyTorch][![GitHub stars](https://img.shields.io/github/stars/yassouali/pytorch_segmentation)](https://github.com/yassouali/pytorch_segmentation)\n- LinkNet [https://arxiv.org/pdf/1707.03718.pdf] [2017]\n\t+ https://github.com/e-lab/LinkNet [Torch]\n\t+ https://github.com/qubvel/segmentation_models [Keras]\n- DenseNet [https://arxiv.org/pdf/1611.09326.pdf] [2017]\n\t+ https://github.com/SimJeg/FC-DenseNet [Lasagne]\n\t+ https://github.com/HasnainRaz/FC-DenseNet-TensorFlow [Tensorflow]\n\t+ https://github.com/0bserver07/One-Hundred-Layers-Tiramisu [Keras]\n- DilatedNet [https://arxiv.org/pdf/1511.07122.pdf] [2016]\n\t+ https://github.com/nicolov/segmentation_keras [Keras]\n\t+ https://github.com/fyu/dilation [Caffe]\n\t+ https://github.com/fyu/drn#semantic-image-segmentataion [PyTorch]\n\t+ https://github.com/hangzhaomit/semantic-segmentation-pytorch [PyTorch]\n- PixelNet [https://arxiv.org/pdf/1609.06694.pdf] [2016]\n\t+ https://github.com/aayushbansal/PixelNet [Caffe]\n- ICNet [https://arxiv.org/pdf/1704.08545.pdf] [2017]\n\t+ https://github.com/hszhao/ICNet [Caffe]\n\t+ https://github.com/aitorzip/Keras-ICNet [Keras]\n\t+ https://github.com/hellochick/ICNet-tensorflow [Tensorflow]\n\t+ https://github.com/oandrienko/fast-semantic-segmentation [Tensorflow]\n\t+ https://github.com/supervisely/supervisely/tree/master/plugins/nn/icnet [PyTorch]\n- ERFNet [http://www.robesafe.uah.es/personal/eduardo.romera/pdfs/Romera17iv.pdf] [?]\n\t+ https://github.com/Eromera/erfnet [Torch]\n\t+ https://github.com/Eromera/erfnet_pytorch [PyTorch]\n- RefineNet [https://arxiv.org/pdf/1611.06612.pdf] [2016]\n\t+ https://github.com/guosheng/refinenet [MatConvNet]\n- PSPNet [https://arxiv.org/pdf/1612.01105.pdf,https://hszhao.github.io/projects/pspnet/] [2017]\n\t+ https://github.com/hszhao/PSPNet [Caffe]\n\t+ https://github.com/ZijunDeng/pytorch-semantic-segmentation [PyTorch]\n\t+ https://github.com/mitmul/chainer-pspnet [Chainer]\n\t+ https://github.com/Vladkryvoruchko/PSPNet-Keras-tensorflow [Keras/Tensorflow]\n\t+ https://github.com/pudae/tensorflow-pspnet [Tensorflow]\n\t+ https://github.com/hellochick/PSPNet-tensorflow [Tensorflow]\n\t+ https://github.com/hellochick/semantic-segmentation-tensorflow [Tensorflow]\n\t+ https://github.com/qubvel/segmentation_models [Keras]\n\t+ https://github.com/oandrienko/fast-semantic-segmentation [Tensorflow]\n\t+ https://github.com/speedinghzl/pytorch-segmentation-toolbox [PyTorch]\n\t+ https://github.com/youansheng/torchcv [PyTorch]\n\t+ https://github.com/yassouali/pytorch_segmentation [PyTorch][![GitHub stars](https://img.shields.io/github/stars/yassouali/pytorch_segmentation)](https://github.com/yassouali/pytorch_segmentation)\n\t+ https://github.com/holyseven/PSPNet-TF-Reproduce [Tensorflow][![GitHub stars](https://img.shields.io/github/stars/holyseven/PSPNet-TF-Reproduce)](https://github.com/holyseven/PSPNet-TF-Reproduce)\n\t+ https://github.com/kazuto1011/pspnet-pytorch [PyTorch]\n- DeconvNet [https://arxiv.org/pdf/1505.04366.pdf] [2015]\n\t+ http://cvlab.postech.ac.kr/research/deconvnet/ [Caffe]\n\t+ https://github.com/HyeonwooNoh/DeconvNet [Caffe]\n\t+ https://github.com/fabianbormann/Tensorflow-DeconvNet-Segmentation [Tensorflow]\n- FRRN [https://arxiv.org/pdf/1611.08323.pdf] [2016]\n\t+ https://github.com/TobyPDE/FRRN [Lasagne]\n- GCN [https://arxiv.org/pdf/1703.02719.pdf] [2017]\n\t+ https://github.com/ZijunDeng/pytorch-semantic-segmentation [PyTorch]\n\t+ https://github.com/ycszen/pytorch-seg [PyTorch]\n\t+ https://github.com/yassouali/pytorch_segmentation [PyTorch][![GitHub stars](https://img.shields.io/github/stars/yassouali/pytorch_segmentation)](https://github.com/yassouali/pytorch_segmentation)\n- LRR [https://arxiv.org/pdf/1605.02264.pdf] [2016]\n\t+ https://github.com/golnazghiasi/LRR [Matconvnet]\n- DUC, HDC [https://arxiv.org/pdf/1702.08502.pdf] [2017]\n\t+ https://github.com/ZijunDeng/pytorch-semantic-segmentation [PyTorch]\n\t+ https://github.com/ycszen/pytorch-seg [PyTorch]\n\t+ https://github.com/yassouali/pytorch_segmentation [PyTorch][![GitHub stars](https://img.shields.io/github/stars/yassouali/pytorch_segmentation)](https://github.com/yassouali/pytorch_segmentation)\n- MultiNet [https://arxiv.org/pdf/1612.07695.pdf] [2016]\n\t+ https://github.com/MarvinTeichmann/MultiNet\n\t+ https://github.com/MarvinTeichmann/KittiSeg\n- Segaware [https://arxiv.org/pdf/1708.04607.pdf] [2017]\n\t+ https://github.com/aharley/segaware [Caffe]\n- Semantic Segmentation using Adversarial Networks [https://arxiv.org/pdf/1611.08408.pdf] [2016]\n\t+ https://github.com/oyam/Semantic-Segmentation-using-Adversarial-Networks [Chainer]\n- PixelDCN [https://arxiv.org/pdf/1705.06820.pdf] [2017]\n\t+ https://github.com/HongyangGao/PixelDCN [Tensorflow]\n- ShuffleSeg [https://arxiv.org/pdf/1803.03816.pdf] [2018]\n\t+ https://github.com/MSiam/TFSegmentation [TensorFlow]\n- AdaptSegNet [https://arxiv.org/pdf/1802.10349.pdf] [2018]\n\t+ https://github.com/wasidennis/AdaptSegNet [PyTorch]\n- TuSimple-DUC [https://arxiv.org/pdf/1702.08502.pdf] [2018]\n\t+ https://github.com/TuSimple/TuSimple-DUC [MxNet]\n- FPN [http://presentations.cocodataset.org/COCO17-Stuff-FAIR.pdf] [2017]\n\t+ https://github.com/qubvel/segmentation_models [Keras]\n- R2U-Net [https://arxiv.org/ftp/arxiv/papers/1802/1802.06955.pdf] [2018]\n\t+ https://github.com/LeeJunHyun/Image_Segmentation#r2u-net [PyTorch]\n- Attention U-Net [https://arxiv.org/pdf/1804.03999.pdf] [2018]\n\t+ https://github.com/LeeJunHyun/Image_Segmentation#attention-u-net [PyTorch]\n\t+ https://github.com/ozan-oktay/Attention-Gated-Networks [PyTorch]\n- DANet [https://arxiv.org/pdf/1809.02983.pdf] [2018]\n\t+ https://github.com/junfu1115/DANet [PyTorch]\n- ShelfNet [https://arxiv.org/pdf/1811.11254.pdf] [2018]\n\t+ https://github.com/juntang-zhuang/ShelfNet [PyTorch]\n- LadderNet [https://arxiv.org/pdf/1810.07810.pdf] [2018]\n\t+ https://github.com/juntang-zhuang/LadderNet [PyTorch]\n- BiSeNet [https://arxiv.org/pdf/1808.00897.pdf] [2018]\n\t+ https://github.com/ooooverflow/BiSeNet [PyTorch]\n\t+ https://github.com/ycszen/TorchSeg [PyTorch]\n\t+ https://github.com/zllrunning/face-parsing.PyTorch [PyTorch]\n- ESPNet [https://arxiv.org/pdf/1803.06815.pdf] [2018]\n\t+ https://github.com/sacmehta/ESPNet [PyTorch]\n- DFN [https://arxiv.org/pdf/1804.09337.pdf] [2018]\n\t+ https://github.com/ycszen/TorchSeg [PyTorch]\n- CCNet [https://arxiv.org/pdf/1811.11721.pdf] [2018]\n\t+ https://github.com/speedinghzl/CCNet [PyTorch]\n- DenseASPP [http://openaccess.thecvf.com/content_cvpr_2018/papers/Yang_DenseASPP_for_Semantic_CVPR_2018_paper.pdf] [2018]\n\t+ https://github.com/youansheng/torchcv [PyTorch]\n- Fast-SCNN [https://arxiv.org/pdf/1902.04502.pdf] [2019]\n\t+ https://github.com/DeepVoltaire/Fast-SCNN [PyTorch]\n- HRNet [https://arxiv.org/pdf/1904.04514.pdf] [2019]\n\t+ https://github.com/HRNet/HRNet-Semantic-Segmentation [PyTorch]\n- PSANet [https://hszhao.github.io/papers/eccv18_psanet.pdf] [2018]\n\t+ https://github.com/hszhao/PSANet [Caffe]\n- UPSNet [https://arxiv.org/pdf/1901.03784.pdf] [2019]\n\t+ https://github.com/uber-research/UPSNet [PyTorch]\n- ConvCRF [https://arxiv.org/pdf/1805.04777.pdf] [2018]\n\t+ https://github.com/MarvinTeichmann/ConvCRF [PyTorch]\n- Multi-scale Guided Attention for Medical Image Segmentation [https://arxiv.org/pdf/1906.02849.pdf] [2019]\n\t+ https://github.com/sinAshish/Multi-Scale-Attention [PyTorch]\n- DFANet [https://arxiv.org/pdf/1904.02216.pdf] [2019]\n\t+ https://github.com/huaifeng1993/DFANet [PyTorch]\n- ExtremeC3Net [https://arxiv.org/pdf/1908.03093.pdf] [2019]\n\t+ https://github.com/HYOJINPARK/ExtPortraitSeg [PyTorch]\n- EncNet [https://arxiv.org/pdf/1803.08904.pdf] [2018]\n\t+ https://github.com/zhanghang1989/PyTorch-Encoding [PyTorch]\n- Unet++ [https://arxiv.org/pdf/1807.10165.pdf] [2018]\n\t+ https://github.com/MrGiovanni/UNetPlusPlus [Keras]\n\t+ https://github.com/4uiiurz1/pytorch-nested-unet [PyTorch]\n- FastFCN [https://arxiv.org/pdf/1903.11816.pdf] [2019]\n\t+ https://github.com/wuhuikai/FastFCN [PyTorch]\n- PortraitNet [https://www.yongliangyang.net/docs/mobilePotrait_c&g19.pdf] [2019]\n\t+ https://github.com/dong-x16/PortraitNet [PyTorch]\n- GSCNN [https://arxiv.org/pdf/1907.05740.pdf] [2019]\n\t+ https://github.com/nv-tlabs/gscnn [PyTorch]\n\t\n### Instance aware segmentation\n- FCIS [https://arxiv.org/pdf/1611.07709.pdf]\n\t+ https://github.com/msracver/FCIS [MxNet]\n- MNC [https://arxiv.org/pdf/1512.04412.pdf]\n\t+ https://github.com/daijifeng001/MNC [Caffe]\n- DeepMask [https://arxiv.org/pdf/1506.06204.pdf]\n\t+ https://github.com/facebookresearch/deepmask [Torch]\n- SharpMask [https://arxiv.org/pdf/1603.08695.pdf]\n\t+ https://github.com/facebookresearch/deepmask [Torch]\n- Mask-RCNN [https://arxiv.org/pdf/1703.06870.pdf]\n\t+ https://github.com/CharlesShang/FastMaskRCNN [Tensorflow]\n\t+ https://github.com/jasjeetIM/Mask-RCNN [Caffe]\n\t+ https://github.com/TuSimple/mx-maskrcnn [MxNet]\n\t+ https://github.com/matterport/Mask_RCNN [Keras]\n\t+ https://github.com/facebookresearch/maskrcnn-benchmark [PyTorch]\n\t+ https://github.com/open-mmlab/mmdetection [PyTorch]\n\t+ https://github.com/ZFTurbo/Keras-Mask-RCNN-for-Open-Images-2019-Instance-Segmentation [Keras]\n- RIS [https://arxiv.org/pdf/1511.08250.pdf]\n  + https://github.com/bernard24/RIS [Torch]\n- FastMask [https://arxiv.org/pdf/1612.08843.pdf]\n  + https://github.com/voidrank/FastMask [Caffe]\n- BlitzNet [https://arxiv.org/pdf/1708.02813.pdf]\n  + https://github.com/dvornikita/blitznet [Tensorflow]\n- PANet [https://arxiv.org/pdf/1803.01534.pdf] [2018]\n  + https://github.com/ShuLiu1993/PANet [Caffe]\n- PAN [https://arxiv.org/pdf/1805.10180.pdf] [2018]\n  + https://github.com/JaveyWang/Pyramid-Attention-Networks-pytorch [PyTorch]\n- TernausNetV2 [https://arxiv.org/pdf/1806.00844.pdf] [2018]\n\t+ https://github.com/ternaus/TernausNetV2 [PyTorch]\n- MS R-CNN [https://arxiv.org/pdf/1903.00241.pdf] [2019]\n\t+ https://github.com/zjhuang22/maskscoring_rcnn [PyTorch]\n- AdaptIS [https://arxiv.org/pdf/1909.07829.pdf] [2019]\n\t+ https://github.com/saic-vul/adaptis [MxNet][PyTorch]\n- Pose2Seg [https://arxiv.org/pdf/1803.10683.pdf] [2019]\n\t+ https://github.com/liruilong940607/Pose2Seg [PyTorch]\n- YOLACT [https://arxiv.org/pdf/1904.02689.pdf] [2019]\n\t+ https://github.com/dbolya/yolact [PyTorch]\n- CenterMask [https://arxiv.org/pdf/1911.06667.pdf] [2019]\n\t+ https://github.com/youngwanLEE/CenterMask [PyTorch]\n\t+ https://github.com/youngwanLEE/centermask2 [PyTorch]\n- InstaBoost [https://arxiv.org/pdf/1908.07801.pdf] [2019]\n\t+ https://github.com/GothicAi/Instaboost [PyTorch]\n- SOLO [https://arxiv.org/pdf/1912.04488.pdf] [2019]\n\t+ https://github.com/WXinlong/SOLO [PyTorch]\n- SOLOv2 [https://arxiv.org/pdf/2003.10152.pdf] [2020]\n\t+ https://github.com/WXinlong/SOLO [PyTorch]\n- D2Det [https://openaccess.thecvf.com/content_CVPR_2020/papers/Cao_D2Det_Towards_High_Quality_Object_Detection_and_Instance_Segmentation_CVPR_2020_paper.pdf] [2020]\n\t+https://github.com/JialeCao001/D2Det [PyTorch]\n\t\n### Weakly-supervised segmentation\n- SEC [https://arxiv.org/pdf/1603.06098.pdf]\n  + https://github.com/kolesman/SEC [Caffe]\n\n## RNN\n- ReNet [https://arxiv.org/pdf/1505.00393.pdf]\n  + https://github.com/fvisin/reseg [Lasagne]\n- ReSeg [https://arxiv.org/pdf/1511.07053.pdf]\n  + https://github.com/Wizaron/reseg-pytorch [PyTorch]\n  + https://github.com/fvisin/reseg [Lasagne]\n- RIS [https://arxiv.org/pdf/1511.08250.pdf]\n  + https://github.com/bernard24/RIS [Torch]\n- CRF-RNN [http://www.robots.ox.ac.uk/%7Eszheng/papers/CRFasRNN.pdf]\n  + https://github.com/martinkersner/train-CRF-RNN [Caffe]\n  + https://github.com/torrvision/crfasrnn [Caffe]\n  + https://github.com/NP-coder/CLPS1520Project [Tensorflow]\n  + https://github.com/renmengye/rec-attend-public [Tensorflow]\n  + https://github.com/sadeepj/crfasrnn_keras [Keras]\n\n## GANS\n- pix2pix [https://arxiv.org/pdf/1611.07004.pdf] [2018]\n  + https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix [Pytorch]\n  + https://github.com/affinelayer/pix2pix-tensorflow [Tensorflow]\n- pix2pixHD [https://arxiv.org/pdf/1711.11585.pdf] [2018]\n  + https://github.com/NVIDIA/pix2pixHD\n- Probalistic Unet [https://arxiv.org/pdf/1806.05034.pdf] [2018]\n  + https://github.com/SimonKohl/probabilistic_unet\n\n\n## Graphical Models (CRF, MRF)\n  + https://github.com/cvlab-epfl/densecrf\n  + http://vladlen.info/publications/efficient-inference-in-fully-connected-crfs-with-gaussian-edge-potentials/\n  + http://www.philkr.net/home/densecrf\n  + http://graphics.stanford.edu/projects/densecrf/\n  + https://github.com/amiltonwong/segmentation/blob/master/segmentation.ipynb\n  + https://github.com/jliemansifry/super-simple-semantic-segmentation\n  + http://users.cecs.anu.edu.au/~jdomke/JGMT/\n  + https://www.quora.com/How-can-one-train-and-test-conditional-random-field-CRF-in-Python-on-our-own-training-testing-dataset\n  + https://github.com/tpeng/python-crfsuite\n  + https://github.com/chokkan/crfsuite\n  + https://sites.google.com/site/zeppethefake/semantic-segmentation-crf-baseline\n  + https://github.com/lucasb-eyer/pydensecrf\n\n## Datasets:\n  + [Stanford Background Dataset](http://dags.stanford.edu/projects/scenedataset.html)\n  + [Sift Flow Dataset](http://people.csail.mit.edu/celiu/SIFTflow/)\n  + [Barcelona Dataset](http://www.cs.unc.edu/~jtighe/Papers/ECCV10/)\n  + [Microsoft COCO dataset](http://mscoco.org/)\n  + [MSRC Dataset](http://research.microsoft.com/en-us/projects/objectclassrecognition/)\n  + [LITS Liver Tumor Segmentation Dataset](https://competitions.codalab.org/competitions/15595)\n  + [KITTI](http://www.cvlibs.net/datasets/kitti/eval_road.php)\n  + [Pascal Context](http://www.cs.stanford.edu/~roozbeh/pascal-context/)\n  + [Data from Games dataset](https://download.visinf.tu-darmstadt.de/data/from_games/)\n  + [Human parsing dataset](https://github.com/lemondan/HumanParsing-Dataset)\n  + [Mapillary Vistas Dataset](https://www.mapillary.com/dataset/vistas)\n  + [Microsoft AirSim](https://github.com/Microsoft/AirSim)\n  + [MIT Scene Parsing Benchmark](http://sceneparsing.csail.mit.edu/)\n  + [COCO 2017 Stuff Segmentation Challenge](http://cocodataset.org/#stuff-challenge2017)\n  + [ADE20K Dataset](http://groups.csail.mit.edu/vision/datasets/ADE20K/)\n  + [INRIA Annotations for Graz-02](http://lear.inrialpes.fr/people/marszalek/data/ig02/)\n  + [Daimler dataset](http://www.gavrila.net/Datasets/Daimler_Pedestrian_Benchmark_D/daimler_pedestrian_benchmark_d.html)\n  + [ISBI Challenge: Segmentation of neuronal structures in EM stacks](http://brainiac2.mit.edu/isbi_challenge/)\n  + [INRIA Annotations for Graz-02 (IG02)](https://lear.inrialpes.fr/people/marszalek/data/ig02/)\n  + [Pratheepan Dataset](http://cs-chan.com/downloads_skin_dataset.html)\n  + [Clothing Co-Parsing (CCP) Dataset](https://github.com/bearpaw/clothing-co-parsing)\n  + [ApolloScape](http://apolloscape.auto/scene.html)\n  + [UrbanMapper3D](https://community.topcoder.com/longcontest/?module=ViewProblemStatement&rd=17007&pm=14703)\n  + [RoadDetector](https://community.topcoder.com/longcontest/?module=ViewProblemStatement&rd=17036&pm=14735)\n  + [Cityscapes](https://www.cityscapes-dataset.com/)\n  + [CamVid](http://mi.eng.cam.ac.uk/research/projects/VideoRec/CamVid/)\n  + [Inria Aerial Image Labeling](https://project.inria.fr/aerialimagelabeling/)\n\n## Benchmarks\n  + https://github.com/openseg-group/openseg.pytorch [PyTorch]\n  + https://github.com/open-mmlab/mmsegmentation [PyTorch]\n  + https://github.com/ZijunDeng/pytorch-semantic-segmentation [PyTorch]\n  + https://github.com/meetshah1995/pytorch-semseg [PyTorch]\n  + https://github.com/GeorgeSeif/Semantic-Segmentation-Suite [Tensorflow]\n  + https://github.com/MSiam/TFSegmentation [Tensorflow]\n  + https://github.com/CSAILVision/sceneparsing [Caffe+Matlab]\n  + https://github.com/BloodAxe/segmentation-networks-benchmark [PyTorch]\n  + https://github.com/warmspringwinds/pytorch-segmentation-detection [PyTorch]\n  + https://github.com/ycszen/TorchSeg [PyTorch]\n  + https://github.com/qubvel/segmentation_models [Keras]\n  + https://github.com/qubvel/segmentation_models.pytorch [PyTorch]\n  + https://github.com/Tramac/awesome-semantic-segmentation-pytorch [PyTorch]\n  + https://github.com/hszhao/semseg [PyTorch]\n  + https://github.com/yassouali/pytorch_segmentation [PyTorch]\n  + https://github.com/divamgupta/image-segmentation-keras [Keras]\n  + https://github.com/CSAILVision/semantic-segmentation-pytorch [PyTorch]\n  + https://github.com/thuyngch/Human-Segmentation-PyTorch [PyTorch]\n  + https://github.com/PaddlePaddle/PaddleSeg [PaddlePaddle]\n\n## Evaluation code\n  + [Cityscapes dataset] https://github.com/phillipi/pix2pix/tree/master/scripts/eval_cityscapes\n\n## Starter code\n  + https://github.com/mrgloom/keras-semantic-segmentation-example\n\n## Annotation Tools:\n\n  + https://github.com/AKSHAYUBHAT/ImageSegmentation\n  + https://github.com/kyamagu/js-segment-annotator\n  + https://github.com/CSAILVision/LabelMeAnnotationTool\n  + https://github.com/seanbell/opensurfaces-segmentation-ui\n  + https://github.com/lzx1413/labelImgPlus\n  + https://github.com/wkentaro/labelme\n  + https://github.com/labelbox/labelbox\n  + https://github.com/Deep-Magic/COCO-Style-Dataset-Generator-GUI\n  + https://github.com/Labelbox/Labelbox\n  + https://github.com/opencv/cvat\n  + https://github.com/saic-vul/fbrs_interactive_segmentation\n\n## Results:\n\n  + [MSRC-21](http://rodrigob.github.io/are_we_there_yet/build/semantic_labeling_datasets_results.html)\n  + [Cityscapes](https://www.cityscapes-dataset.com/benchmarks/)\n  + [VOC2012](http://host.robots.ox.ac.uk:8080/leaderboard/displaylb.php?challengeid=11&compid=6)\n  + https://paperswithcode.com/task/semantic-segmentation\n\n## Metrics\n  + https://github.com/martinkersner/py_img_seg_eval\n\n## Losses\n  + https://github.com/JunMa11/SegLoss \n  + http://www.cs.umanitoba.ca/~ywang/papers/isvc16.pdf\n  + https://arxiv.org/pdf/1705.08790.pdf\n  + https://arxiv.org/pdf/1707.03237.pdf\n  + http://www.bmva.org/bmvc/2013/Papers/paper0032/paper0032.pdf\n    \n## Other lists\n  + https://paperswithcode.com/task/semantic-segmentation\n  + https://github.com/tangzhenyu/SemanticSegmentation_DL\n  + https://github.com/nightrome/really-awesome-semantic-segmentation\n  + https://github.com/JackieZhangdx/InstanceSegmentationList\n  + https://github.com/damminhtien/awesome-semantic-segmentation\n\n## Medical image segmentation:\n\n- DIGITS\n  + https://github.com/NVIDIA/DIGITS/tree/master/examples/medical-imaging\n  \n- U-Net: Convolutional Networks for Biomedical Image Segmentation\n  + http://lmb.informatik.uni-freiburg.de/people/ronneber/u-net/\n  + https://github.com/dmlc/mxnet/issues/1514\n  + https://github.com/orobix/retina-unet\n  + https://github.com/fvisin/reseg\n  + https://github.com/yulequan/melanoma-recognition\n  + http://www.andrewjanowczyk.com/use-case-1-nuclei-segmentation/\n  + https://github.com/junyanz/MCILBoost\n  + https://github.com/imlab-uiip/lung-segmentation-2d\n  + https://github.com/scottykwok/cervix-roi-segmentation-by-unet\n  + https://github.com/WeidiXie/cell_counting_v2\n  + https://github.com/yandexdataschool/YSDA_deeplearning17/blob/master/Seminar6/Seminar%206%20-%20segmentation.ipynb\n  \n- Cascaded-FCN\n  + https://github.com/IBBM/Cascaded-FCN\n  \n- Keras\n  + https://github.com/jocicmarko/ultrasound-nerve-segmentation\n  + https://github.com/EdwardTyantov/ultrasound-nerve-segmentation\n  + https://github.com/intact-project/ild-cnn\n  + https://github.com/scottykwok/cervix-roi-segmentation-by-unet\n  + https://github.com/lishen/end2end-all-conv\n  \n- Tensorflow\n  + https://github.com/imatge-upc/liverseg-2017-nipsws\n  + https://github.com/DLTK/DLTK/tree/master/examples/applications/MRBrainS13_tissue_segmentation\n  \n- Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA)\n  + https://github.com/ecobost/cnn4brca\n  \n- Papers:\n  + https://www2.warwick.ac.uk/fac/sci/dcs/people/research/csrkbb/tmi2016_ks.pdf\n  + Sliding window approach\n\t  - http://people.idsia.ch/~juergen/nips2012.pdf\n  + https://github.com/albarqouni/Deep-Learning-for-Medical-Applications#segmentation\n\t\n - Data:\n   - https://luna16.grand-challenge.org/\n   - https://camelyon16.grand-challenge.org/\n   - https://github.com/beamandrew/medical-data\n\n## Satellite images segmentation\n\n  + https://github.com/mshivaprakash/sat-seg-thesis\n  + https://github.com/KGPML/Hyperspectral\n  + https://github.com/lopuhin/kaggle-dstl\n  + https://github.com/mitmul/ssai\n  + https://github.com/mitmul/ssai-cnn\n  + https://github.com/azavea/raster-vision\n  + https://github.com/nshaud/DeepNetsForEO\n  + https://github.com/trailbehind/DeepOSM\n  + https://github.com/mapbox/robosat\n  + https://github.com/datapink/robosat.pink\n\n - Data:\n  \t+ https://github.com/RSIA-LIESMARS-WHU/RSOD-Dataset-\n\t+ SpaceNet[https://spacenetchallenge.github.io/]\n\t+ https://github.com/chrieke/awesome-satellite-imagery-datasets\n\n## Video segmentation\n\n  + https://github.com/shelhamer/clockwork-fcn\n  + https://github.com/JingchunCheng/Seg-with-SPN\n\n## Autonomous driving\n\n  + https://github.com/MarvinTeichmann/MultiNet\n  + https://github.com/MarvinTeichmann/KittiSeg\n  + https://github.com/vxy10/p5_VehicleDetection_Unet [Keras]\n  + https://github.com/ndrplz/self-driving-car\n  + https://github.com/mvirgo/MLND-Capstone\n  + https://github.com/zhujun98/semantic_segmentation/tree/master/fcn8s_road\n  + https://github.com/MaybeShewill-CV/lanenet-lane-detection\n\n### Other\n\n## Networks by framework (Older list)\n- Keras\n\t+ https://github.com/gakarak/FCN_MSCOCO_Food_Segmentation\n\t+ https://github.com/abbypa/NNProject_DeepMask\n\n- TensorFlow\n\t+ https://github.com/warmspringwinds/tf-image-segmentation\n\t\n- Caffe\n\t+ https://github.com/xiaolonw/nips14_loc_seg_testonly\n\t+ https://github.com/naibaf7/caffe_neural_tool\n\t\n- torch\n\t+ https://github.com/erogol/seg-torch\n\t+ https://github.com/phillipi/pix2pix\n\t\n- MXNet\n\t+ https://github.com/itijyou/ademxapp\n\n## Papers and Code (Older list)\n\n- Simultaneous detection and segmentation\n\n  + http://www.eecs.berkeley.edu/Research/Projects/CS/vision/shape/sds/\n  + https://github.com/bharath272/sds_eccv2014\n  \n- Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation\n\n  + https://github.com/HyeonwooNoh/DecoupledNet\n  \n- Learning to Propose Objects\n\n  + http://vladlen.info/publications/learning-to-propose-objects/ \n  + https://github.com/philkr/lpo\n  \n- Nonparametric Scene Parsing via Label Transfer\n\n  + http://people.csail.mit.edu/celiu/LabelTransfer/code.html\n  \n- Other\n  + https://github.com/cvjena/cn24\n  + http://lmb.informatik.uni-freiburg.de/resources/software.php\n  + https://github.com/NVIDIA/DIGITS/tree/master/examples/semantic-segmentation\n  + http://jamie.shotton.org/work/code.html \n  + https://github.com/amueller/textonboost\n  \n## To look at\n  + https://github.com/fchollet/keras/issues/6538\n  + https://github.com/warmspringwinds/tensorflow_notes\n  + https://github.com/kjw0612/awesome-deep-vision#semantic-segmentation\n  + https://github.com/desimone/segmentation-models\n  + https://github.com/nightrome/really-awesome-semantic-segmentation\n  + https://github.com/kjw0612/awesome-deep-vision#semantic-segmentation\n  + http://www.it-caesar.com/list-of-contemporary-semantic-segmentation-datasets/\n  + https://github.com/MichaelXin/Awesome-Caffe#23-image-segmentation\n  + https://github.com/warmspringwinds/pytorch-segmentation-detection\n  + https://github.com/neuropoly/axondeepseg\n  + https://github.com/petrochenko-pavel-a/segmentation_training_pipeline\n\n\n## Blog posts, other:\n\n  + https://handong1587.github.io/deep_learning/2015/10/09/segmentation.html\n  + http://www.andrewjanowczyk.com/efficient-pixel-wise-deep-learning-on-large-images/\n  + https://devblogs.nvidia.com/parallelforall/image-segmentation-using-digits-5/\n  + https://github.com/NVIDIA/DIGITS/tree/master/examples/binary-segmentation\n  + https://github.com/NVIDIA/DIGITS/tree/master/examples/semantic-segmentation\n  + http://blog.qure.ai/notes/semantic-segmentation-deep-learning-review\n  + https://medium.com/@barvinograd1/instance-embedding-instance-segmentation-without-proposals-31946a7c53e1\n\n"
  }
]