awesome-semantic-segmentation

by mrgloom

:metal: awesome-semantic-segmentation

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Awesome

Awesome Semantic Segmentation

Networks by architecture

Semantic segmentation

  • U-Net [https://arxiv.org/pdf/1505.04597.pdf] [2015]
    • https://github.com/zhixuhao/unet [Keras]GitHub stars
    • https://github.com/jocicmarko/ultrasound-nerve-segmentation [Keras]GitHub stars
    • https://github.com/EdwardTyantov/ultrasound-nerve-segmentation [Keras]GitHub stars
    • https://github.com/ZFTurbo/ZFUNET224PretrainedModel [Keras]GitHub stars
    • https://github.com/yihui-he/u-net [Keras]GitHub stars
    • https://github.com/jakeret/tfunet [Tensorflow][![GitHub stars](https://img.shields.io/github/stars/jakeret/tfunet.svg?logo=github&label=Stars)](https://github.com/jakeret/tf_unet)
    • https://github.com/divamgupta/image-segmentation-keras [Keras]GitHub stars
    • https://github.com/ZijunDeng/pytorch-semantic-segmentation [PyTorch]GitHub stars
    • https://github.com/akirasosa/mobile-semantic-segmentation [Keras]GitHub stars
    • https://github.com/orobix/retina-unet [Keras]GitHub stars
    • https://github.com/qureai/ultrasound-nerve-segmentation-using-torchnet [Torch]GitHub stars
    • https://github.com/ternaus/TernausNet [PyTorch]GitHub stars
    • https://github.com/qubvel/segmentationmodels [Keras][![GitHub stars](https://img.shields.io/github/stars/qubvel/segmentationmodels.svg?logo=github&label=Stars)](https://github.com/qubvel/segmentation_models)
    • https://github.com/LeeJunHyun/ImageSegmentation#u-net [PyTorch][![GitHub stars](https://img.shields.io/github/stars/LeeJunHyun/ImageSegmentation.svg?logo=github&label=Stars)](https://github.com/LeeJunHyun/Image_Segmentation)
    • https://github.com/yassouali/pytorchsegmentation [PyTorch][![GitHub stars](https://img.shields.io/github/stars/yassouali/pytorchsegmentation.svg?logo=github&label=Stars)](https://github.com/yassouali/pytorch_segmentation)
    • https://lmb.informatik.uni-freiburg.de/people/ronneber/u-net/ [Caffe + Matlab]
  • SegNet [https://arxiv.org/pdf/1511.00561.pdf] [2016]
    • https://github.com/alexgkendall/caffe-segnet [Caffe]
    • https://github.com/developmentseed/caffe/tree/segnet-multi-gpu [Caffe]
    • https://github.com/preddy5/segnet [Keras]
    • https://github.com/imlab-uiip/keras-segnet [Keras]
    • https://github.com/andreaazzini/segnet [Tensorflow]
    • https://github.com/fedor-chervinskii/segnet-torch [Torch]
    • https://github.com/0bserver07/Keras-SegNet-Basic [Keras]
    • https://github.com/tkuanlun350/Tensorflow-SegNet [Tensorflow]
    • https://github.com/divamgupta/image-segmentation-keras [Keras]
    • https://github.com/ZijunDeng/pytorch-semantic-segmentation [PyTorch]
    • https://github.com/chainer/chainercv/tree/master/examples/segnet [Chainer]
    • https://github.com/ykamikawa/keras-SegNet [Keras]
    • https://github.com/ykamikawa/tf-keras-SegNet [Keras]
    • https://github.com/yassouali/pytorchsegmentation [PyTorch][![GitHub stars](https://img.shields.io/github/stars/yassouali/pytorchsegmentation)](https://github.com/yassouali/pytorch_segmentation)
  • DeepLab [https://arxiv.org/pdf/1606.00915.pdf] [2017]
    • https://bitbucket.org/deeplab/deeplab-public/ [Caffe]
    • https://github.com/cdmh/deeplab-public [Caffe]
    • https://bitbucket.org/aquariusjay/deeplab-public-ver2 [Caffe]
    • https://github.com/TheLegendAli/DeepLab-Context [Caffe]
    • https://github.com/msracver/Deformable-ConvNets/tree/master/deeplab [MXNet]
    • https://github.com/DrSleep/tensorflow-deeplab-resnet [Tensorflow]
    • https://github.com/muyang0320/tensorflow-deeplab-resnet-crf [TensorFlow]
    • https://github.com/isht7/pytorch-deeplab-resnet [PyTorch]
    • https://github.com/bermanmaxim/jaccardSegment [PyTorch]
    • https://github.com/martinkersner/train-DeepLab [Caffe]
    • https://github.com/chenxi116/TF-deeplab [Tensorflow]
    • https://github.com/bonlime/keras-deeplab-v3-plus [Keras]
    • https://github.com/tensorflow/models/tree/master/research/deeplab [Tensorflow]
    • https://github.com/speedinghzl/pytorch-segmentation-toolbox [PyTorch]
    • https://github.com/kazuto1011/deeplab-pytorch [PyTorch]
    • https://github.com/youansheng/torchcv [PyTorch]
    • https://github.com/yassouali/pytorchsegmentation [PyTorch][![GitHub stars](https://img.shields.io/github/stars/yassouali/pytorchsegmentation)](https://github.com/yassouali/pytorch_segmentation)
    • https://github.com/hualin95/Deeplab-v3plus [PyTorch]
  • FCN [https://arxiv.org/pdf/1605.06211.pdf] [2016]
    • https://github.com/vlfeat/matconvnet-fcn [MatConvNet]
    • https://github.com/shelhamer/fcn.berkeleyvision.org [Caffe]
    • https://github.com/MarvinTeichmann/tensorflow-fcn [Tensorflow]
    • https://github.com/aurora95/Keras-FCN [Keras]
    • https://github.com/mzaradzki/neuralnets/tree/master/vggsegmentationkeras [Keras]
    • https://github.com/k3nt0w/FCNviakeras [Keras]
    • https://github.com/shekkizh/FCN.tensorflow [Tensorflow]
    • https://github.com/seewalker/tf-pixelwise [Tensorflow]
    • https://github.com/divamgupta/image-segmentation-keras [Keras]
    • https://github.com/ZijunDeng/pytorch-semantic-segmentation [PyTorch]
    • https://github.com/wkentaro/pytorch-fcn [PyTorch]
    • https://github.com/wkentaro/fcn [Chainer]
    • https://github.com/apache/incubator-mxnet/tree/master/example/fcn-xs [MxNet]
    • https://github.com/muyang0320/tf-fcn [Tensorflow]
    • https://github.com/ycszen/pytorch-seg [PyTorch]
    • https://github.com/Kaixhin/FCN-semantic-segmentation [PyTorch]
    • https://github.com/petrama/VGGSegmentation [Tensorflow]
    • https://github.com/simonguist/testing-fcn-for-cityscapes [Caffe]
    • https://github.com/hellochick/semantic-segmentation-tensorflow [Tensorflow]
    • https://github.com/pierluigiferrari/fcn8s_tensorflow [Tensorflow]
    • https://github.com/theduynguyen/Keras-FCN [Keras]
    • https://github.com/JihongJu/keras-fcn [Keras]
    • https://github.com/yassouali/pytorchsegmentation [PyTorch][![GitHub stars](https://img.shields.io/github/stars/yassouali/pytorchsegmentation)](https://github.com/yassouali/pytorch_segmentation)
  • ENet [https://arxiv.org/pdf/1606.02147.pdf] [2016]
    • https://github.com/TimoSaemann/ENet [Caffe]
    • https://github.com/e-lab/ENet-training [Torch]
    • https://github.com/PavlosMelissinos/enet-keras [Keras]
    • https://github.com/fregu856/segmentation [Tensorflow]
    • https://github.com/kwotsin/TensorFlow-ENet [Tensorflow]
    • https://github.com/davidtvs/PyTorch-ENet [PyTorch]
    • https://github.com/yassouali/pytorchsegmentation [PyTorch][![GitHub stars](https://img.shields.io/github/stars/yassouali/pytorchsegmentation)](https://github.com/yassouali/pytorch_segmentation)
  • LinkNet [https://arxiv.org/pdf/1707.03718.pdf] [2017]
    • https://github.com/e-lab/LinkNet [Torch]
    • https://github.com/qubvel/segmentation_models [Keras]
  • DenseNet [https://arxiv.org/pdf/1611.09326.pdf] [2017]
    • https://github.com/SimJeg/FC-DenseNet [Lasagne]
    • https://github.com/HasnainRaz/FC-DenseNet-TensorFlow [Tensorflow]
    • https://github.com/0bserver07/One-Hundred-Layers-Tiramisu [Keras]
  • DilatedNet [https://arxiv.org/pdf/1511.07122.pdf] [2016]
    • https://github.com/nicolov/segmentation_keras [Keras]
    • https://github.com/fyu/dilation [Caffe]
    • https://github.com/fyu/drn#semantic-image-segmentataion [PyTorch]
    • https://github.com/hangzhaomit/semantic-segmentation-pytorch [PyTorch]
  • PixelNet [https://arxiv.org/pdf/1609.06694.pdf] [2016]
    • https://github.com/aayushbansal/PixelNet [Caffe]
  • ICNet [https://arxiv.org/pdf/1704.08545.pdf] [2017]
    • https://github.com/hszhao/ICNet [Caffe]
    • https://github.com/aitorzip/Keras-ICNet [Keras]
    • https://github.com/hellochick/ICNet-tensorflow [Tensorflow]
    • https://github.com/oandrienko/fast-semantic-segmentation [Tensorflow]
    • https://github.com/supervisely/supervisely/tree/master/plugins/nn/icnet [PyTorch]
  • ERFNet [http://www.robesafe.uah.es/personal/eduardo.romera/pdfs/Romera17iv.pdf] [?]
    • https://github.com/Eromera/erfnet [Torch]
    • https://github.com/Eromera/erfnet_pytorch [PyTorch]
  • RefineNet [https://arxiv.org/pdf/1611.06612.pdf] [2016]
    • https://github.com/guosheng/refinenet [MatConvNet]
  • PSPNet [https://arxiv.org/pdf/1612.01105.pdf,https://hszhao.github.io/projects/pspnet/] [2017]
    • https://github.com/hszhao/PSPNet [Caffe]
    • https://github.com/ZijunDeng/pytorch-semantic-segmentation [PyTorch]
    • https://github.com/mitmul/chainer-pspnet [Chainer]
    • https://github.com/Vladkryvoruchko/PSPNet-Keras-tensorflow [Keras/Tensorflow]
    • https://github.com/pudae/tensorflow-pspnet [Tensorflow]
    • https://github.com/hellochick/PSPNet-tensorflow [Tensorflow]
    • https://github.com/hellochick/semantic-segmentation-tensorflow [Tensorflow]
    • https://github.com/qubvel/segmentation_models [Keras]
    • https://github.com/oandrienko/fast-semantic-segmentation [Tensorflow]
    • https://github.com/speedinghzl/pytorch-segmentation-toolbox [PyTorch]
    • https://github.com/youansheng/torchcv [PyTorch]
    • https://github.com/yassouali/pytorchsegmentation [PyTorch][![GitHub stars](https://img.shields.io/github/stars/yassouali/pytorchsegmentation)](https://github.com/yassouali/pytorch_segmentation)
    • https://github.com/holyseven/PSPNet-TF-Reproduce [Tensorflow]GitHub stars
    • https://github.com/kazuto1011/pspnet-pytorch [PyTorch]
  • DeconvNet [https://arxiv.org/pdf/1505.04366.pdf] [2015]
    • http://cvlab.postech.ac.kr/research/deconvnet/ [Caffe]
    • https://github.com/HyeonwooNoh/DeconvNet [Caffe]
    • https://github.com/fabianbormann/Tensorflow-DeconvNet-Segmentation [Tensorflow]
  • FRRN [https://arxiv.org/pdf/1611.08323.pdf] [2016]
    • https://github.com/TobyPDE/FRRN [Lasagne]
  • GCN [https://arxiv.org/pdf/1703.02719.pdf] [2017]
    • https://github.com/ZijunDeng/pytorch-semantic-segmentation [PyTorch]
    • https://github.com/ycszen/pytorch-seg [PyTorch]
    • https://github.com/yassouali/pytorchsegmentation [PyTorch][![GitHub stars](https://img.shields.io/github/stars/yassouali/pytorchsegmentation)](https://github.com/yassouali/pytorch_segmentation)
  • LRR [https://arxiv.org/pdf/1605.02264.pdf] [2016]
    • https://github.com/golnazghiasi/LRR [Matconvnet]
  • DUC, HDC [https://arxiv.org/pdf/1702.08502.pdf] [2017]
    • https://github.com/ZijunDeng/pytorch-semantic-segmentation [PyTorch]
    • https://github.com/ycszen/pytorch-seg [PyTorch]
    • https://github.com/yassouali/pytorchsegmentation [PyTorch][![GitHub stars](https://img.shields.io/github/stars/yassouali/pytorchsegmentation)](https://github.com/yassouali/pytorch_segmentation)
  • MultiNet [https://arxiv.org/pdf/1612.07695.pdf] [2016]
    • https://github.com/MarvinTeichmann/MultiNet
    • https://github.com/MarvinTeichmann/KittiSeg
  • Segaware [https://arxiv.org/pdf/1708.04607.pdf] [2017]
    • https://github.com/aharley/segaware [Caffe]
  • Semantic Segmentation using Adversarial Networks [https://arxiv.org/pdf/1611.08408.pdf] [2016]
    • https://github.com/oyam/Semantic-Segmentation-using-Adversarial-Networks [Chainer]
  • PixelDCN [https://arxiv.org/pdf/1705.06820.pdf] [2017]
    • https://github.com/HongyangGao/PixelDCN [Tensorflow]
  • ShuffleSeg [https://arxiv.org/pdf/1803.03816.pdf] [2018]
    • https://github.com/MSiam/TFSegmentation [TensorFlow]
  • AdaptSegNet [https://arxiv.org/pdf/1802.10349.pdf] [2018]
    • https://github.com/wasidennis/AdaptSegNet [PyTorch]
  • TuSimple-DUC [https://arxiv.org/pdf/1702.08502.pdf] [2018]
    • https://github.com/TuSimple/TuSimple-DUC [MxNet]
  • FPN [http://presentations.cocodataset.org/COCO17-Stuff-FAIR.pdf] [2017]
    • https://github.com/qubvel/segmentation_models [Keras]
  • R2U-Net [https://arxiv.org/ftp/arxiv/papers/1802/1802.06955.pdf] [2018]
    • https://github.com/LeeJunHyun/Image_Segmentation#r2u-net [PyTorch]
  • Attention U-Net [https://arxiv.org/pdf/1804.03999.pdf] [2018]
    • https://github.com/LeeJunHyun/Image_Segmentation#attention-u-net [PyTorch]
    • https://github.com/ozan-oktay/Attention-Gated-Networks [PyTorch]
  • DANet [https://arxiv.org/pdf/1809.02983.pdf] [2018]
    • https://github.com/junfu1115/DANet [PyTorch]
  • ShelfNet [https://arxiv.org/pdf/1811.11254.pdf] [2018]
    • https://github.com/juntang-zhuang/ShelfNet [PyTorch]
  • LadderNet [https://arxiv.org/pdf/1810.07810.pdf] [2018]
    • https://github.com/juntang-zhuang/LadderNet [PyTorch]
  • BiSeNet [https://arxiv.org/pdf/1808.00897.pdf] [2018]
    • https://github.com/ooooverflow/BiSeNet [PyTorch]
    • https://github.com/ycszen/TorchSeg [PyTorch]
    • https://github.com/zllrunning/face-parsing.PyTorch [PyTorch]
  • ESPNet [https://arxiv.org/pdf/1803.06815.pdf] [2018]
    • https://github.com/sacmehta/ESPNet [PyTorch]
  • DFN [https://arxiv.org/pdf/1804.09337.pdf] [2018]
    • https://github.com/ycszen/TorchSeg [PyTorch]
  • CCNet [https://arxiv.org/pdf/1811.11721.pdf] [2018]
    • https://github.com/speedinghzl/CCNet [PyTorch]
  • DenseASPP [http://openaccess.thecvf.com/contentcvpr2018/papers/YangDenseASPPforSemanticCVPR2018paper.pdf] [2018]
    • https://github.com/youansheng/torchcv [PyTorch]
  • Fast-SCNN [https://arxiv.org/pdf/1902.04502.pdf] [2019]
    • https://github.com/DeepVoltaire/Fast-SCNN [PyTorch]
  • HRNet [https://arxiv.org/pdf/1904.04514.pdf] [2019]
    • https://github.com/HRNet/HRNet-Semantic-Segmentation [PyTorch]
  • PSANet [https://hszhao.github.io/papers/eccv18_psanet.pdf] [2018]
    • https://github.com/hszhao/PSANet [Caffe]
  • UPSNet [https://arxiv.org/pdf/1901.03784.pdf] [2019]
    • https://github.com/uber-research/UPSNet [PyTorch]
  • ConvCRF [https://arxiv.org/pdf/1805.04777.pdf] [2018]
    • https://github.com/MarvinTeichmann/ConvCRF [PyTorch]
  • Multi-scale Guided Attention for Medical Image Segmentation [https://arxiv.org/pdf/1906.02849.pdf] [2019]
    • https://github.com/sinAshish/Multi-Scale-Attention [PyTorch]
  • DFANet [https://arxiv.org/pdf/1904.02216.pdf] [2019]
    • https://github.com/huaifeng1993/DFANet [PyTorch]
  • ExtremeC3Net [https://arxiv.org/pdf/1908.03093.pdf] [2019]
    • https://github.com/HYOJINPARK/ExtPortraitSeg [PyTorch]
  • EncNet [https://arxiv.org/pdf/1803.08904.pdf] [2018]
    • https://github.com/zhanghang1989/PyTorch-Encoding [PyTorch]
  • Unet++ [https://arxiv.org/pdf/1807.10165.pdf] [2018]
    • https://github.com/MrGiovanni/UNetPlusPlus [Keras]
    • https://github.com/4uiiurz1/pytorch-nested-unet [PyTorch]
  • FastFCN [https://arxiv.org/pdf/1903.11816.pdf] [2019]
    • https://github.com/wuhuikai/FastFCN [PyTorch]
  • PortraitNet [https://www.yongliangyang.net/docs/mobilePotrait_c&g19.pdf] [2019]
    • https://github.com/dong-x16/PortraitNet [PyTorch]

Instance aware segmentation

  • FCIS [https://arxiv.org/pdf/1611.07709.pdf]
    • https://github.com/msracver/FCIS [MxNet]
  • MNC [https://arxiv.org/pdf/1512.04412.pdf]
    • https://github.com/daijifeng001/MNC [Caffe]
  • DeepMask [https://arxiv.org/pdf/1506.06204.pdf]
    • https://github.com/facebookresearch/deepmask [Torch]
  • SharpMask [https://arxiv.org/pdf/1603.08695.pdf]
    • https://github.com/facebookresearch/deepmask [Torch]
  • Mask-RCNN [https://arxiv.org/pdf/1703.06870.pdf]
    • https://github.com/CharlesShang/FastMaskRCNN [Tensorflow]
    • https://github.com/jasjeetIM/Mask-RCNN [Caffe]
    • https://github.com/TuSimple/mx-maskrcnn [MxNet]
    • https://github.com/matterport/Mask_RCNN [Keras]
    • https://github.com/facebookresearch/maskrcnn-benchmark [PyTorch]
    • https://github.com/open-mmlab/mmdetection [PyTorch]
    • https://github.com/ZFTurbo/Keras-Mask-RCNN-for-Open-Images-2019-Instance-Segmentation [Keras]
  • RIS [https://arxiv.org/pdf/1511.08250.pdf]
    • https://github.com/bernard24/RIS [Torch]
  • FastMask [https://arxiv.org/pdf/1612.08843.pdf]
    • https://github.com/voidrank/FastMask [Caffe]
  • BlitzNet [https://arxiv.org/pdf/1708.02813.pdf]
    • https://github.com/dvornikita/blitznet [Tensorflow]
  • PANet [https://arxiv.org/pdf/1803.01534.pdf] [2018]
    • https://github.com/ShuLiu1993/PANet [Caffe]
  • PAN [https://arxiv.org/pdf/1805.10180.pdf] [2018]
    • https://github.com/JaveyWang/Pyramid-Attention-Networks-pytorch [PyTorch]
  • TernausNetV2 [https://arxiv.org/pdf/1806.00844.pdf] [2018]
    • https://github.com/ternaus/TernausNetV2 [PyTorch]
  • MS R-CNN [https://arxiv.org/pdf/1903.00241.pdf] [2019]
    • https://github.com/zjhuang22/maskscoring_rcnn [PyTorch]
  • AdaptIS [https://arxiv.org/pdf/1909.07829.pdf] [2019]
    • https://github.com/saic-vul/adaptis [MxNet][PyTorch]
  • Pose2Seg [https://arxiv.org/pdf/1803.10683.pdf] [2019]
    • https://github.com/liruilong940607/Pose2Seg [PyTorch]
  • YOLACT [https://arxiv.org/pdf/1904.02689.pdf] [2019]
    • https://github.com/dbolya/yolact [PyTorch]
  • CenterMask [https://arxiv.org/pdf/1911.06667.pdf] [2019]
    • https://github.com/youngwanLEE/CenterMask [PyTorch]
    • https://github.com/youngwanLEE/centermask2 [PyTorch]
  • InstaBoost [https://arxiv.org/pdf/1908.07801.pdf] [2019]
    • https://github.com/GothicAi/Instaboost [PyTorch]
  • SOLO [https://arxiv.org/pdf/1912.04488.pdf] [2019]
    • https://github.com/WXinlong/SOLO [PyTorch]
  • SOLOv2 [https://arxiv.org/pdf/2003.10152.pdf] [2020]
    • https://github.com/WXinlong/SOLO [PyTorch]
  • D2Det [https://openaccess.thecvf.com/contentCVPR2020/papers/CaoD2DetTowardsHighQualityObjectDetectionandInstanceSegmentationCVPR2020paper.pdf] [2020] +https://github.com/JialeCao001/D2Det [PyTorch]

Weakly-supervised segmentation

  • SEC [https://arxiv.org/pdf/1603.06098.pdf]
    • https://github.com/kolesman/SEC [Caffe]

RNN

  • ReNet [https://arxiv.org/pdf/1505.00393.pdf]
    • https://github.com/fvisin/reseg [Lasagne]
  • ReSeg [https://arxiv.org/pdf/1511.07053.pdf]
    • https://github.com/Wizaron/reseg-pytorch [PyTorch]
    • https://github.com/fvisin/reseg [Lasagne]
  • RIS [https://arxiv.org/pdf/1511.08250.pdf]
    • https://github.com/bernard24/RIS [Torch]
  • CRF-RNN [http://www.robots.ox.ac.uk/%7Eszheng/papers/CRFasRNN.pdf]
    • https://github.com/martinkersner/train-CRF-RNN [Caffe]
    • https://github.com/torrvision/crfasrnn [Caffe]
    • https://github.com/NP-coder/CLPS1520Project [Tensorflow]
    • https://github.com/renmengye/rec-attend-public [Tensorflow]
    • https://github.com/sadeepj/crfasrnn_keras [Keras]

GANS

  • pix2pix [https://arxiv.org/pdf/1611.07004.pdf] [2018]
    • https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix [Pytorch]
    • https://github.com/affinelayer/pix2pix-tensorflow [Tensorflow]
  • pix2pixHD [https://arxiv.org/pdf/1711.11585.pdf] [2018]
    • https://github.com/NVIDIA/pix2pixHD
  • Probalistic Unet [https://arxiv.org/pdf/1806.05034.pdf] [2018]
    • https://github.com/SimonKohl/probabilistic_unet

Graphical Models (CRF, MRF)

  • https://github.com/cvlab-epfl/densecrf
  • http://vladlen.info/publications/efficient-inference-in-fully-connected-crfs-with-gaussian-edge-potentials/
  • http://www.philkr.net/home/densecrf
  • http://graphics.stanford.edu/projects/densecrf/
  • https://github.com/amiltonwong/segmentation/blob/master/segmentation.ipynb
  • https://github.com/jliemansifry/super-simple-semantic-segmentation
  • http://users.cecs.anu.edu.au/~jdomke/JGMT/
  • https://www.quora.com/How-can-one-train-and-test-conditional-random-field-CRF-in-Python-on-our-own-training-testing-dataset
  • https://github.com/tpeng/python-crfsuite
  • https://github.com/chokkan/crfsuite
  • https://sites.google.com/site/zeppethefake/semantic-segmentation-crf-baseline
  • https://github.com/lucasb-eyer/pydensecrf

Datasets:

Benchmarks

  • https://github.com/openseg-group/openseg.pytorch [PyTorch]
  • https://github.com/open-mmlab/mmsegmentation [PyTorch]
  • https://github.com/ZijunDeng/pytorch-semantic-segmentation [PyTorch]
  • https://github.com/meetshah1995/pytorch-semseg [PyTorch]
  • https://github.com/GeorgeSeif/Semantic-Segmentation-Suite [Tensorflow]
  • https://github.com/MSiam/TFSegmentation [Tensorflow]
  • https://github.com/CSAILVision/sceneparsing [Caffe+Matlab]
  • https://github.com/BloodAxe/segmentation-networks-benchmark [PyTorch]
  • https://github.com/warmspringwinds/pytorch-segmentation-detection [PyTorch]
  • https://github.com/ycszen/TorchSeg [PyTorch]
  • https://github.com/qubvel/segmentation_models [Keras]
  • https://github.com/qubvel/segmentation_models.pytorch [PyTorch]
  • https://github.com/Tramac/awesome-semantic-segmentation-pytorch [PyTorch]
  • https://github.com/hszhao/semseg [PyTorch]
  • https://github.com/yassouali/pytorch_segmentation [PyTorch]
  • https://github.com/divamgupta/image-segmentation-keras [Keras]
  • https://github.com/CSAILVision/semantic-segmentation-pytorch [PyTorch]
  • https://github.com/thuyngch/Human-Segmentation-PyTorch [PyTorch]

Evaluation code

  • [Cityscapes dataset] https://github.com/phillipi/pix2pix/tree/master/scripts/eval_cityscapes

Starter code

  • https://github.com/mrgloom/keras-semantic-segmentation-example

Annotation Tools:

  • https://github.com/AKSHAYUBHAT/ImageSegmentation
  • https://github.com/kyamagu/js-segment-annotator
  • https://github.com/CSAILVision/LabelMeAnnotationTool
  • https://github.com/seanbell/opensurfaces-segmentation-ui
  • https://github.com/lzx1413/labelImgPlus
  • https://github.com/wkentaro/labelme
  • https://github.com/labelbox/labelbox
  • https://github.com/Deep-Magic/COCO-Style-Dataset-Generator-GUI
  • https://github.com/Labelbox/Labelbox
  • https://github.com/opencv/cvat
  • https://github.com/saic-vul/fbrsinteractivesegmentation

Results:

Metrics

  • https://github.com/martinkersner/pyimgseg_eval

Losses

  • https://github.com/JunMa11/SegLoss
  • http://www.cs.umanitoba.ca/~ywang/papers/isvc16.pdf
  • https://arxiv.org/pdf/1705.08790.pdf
  • https://arxiv.org/pdf/1707.03237.pdf
  • http://www.bmva.org/bmvc/2013/Papers/paper0032/paper0032.pdf

Other lists

  • https://github.com/tangzhenyu/SemanticSegmentation_DL
  • https://github.com/nightrome/really-awesome-semantic-segmentation
  • https://github.com/JackieZhangdx/InstanceSegmentationList

Medical image segmentation:

  • DIGITS

    • https://github.com/NVIDIA/DIGITS/tree/master/examples/medical-imaging
  • U-Net: Convolutional Networks for Biomedical Image Segmentation

    • http://lmb.informatik.uni-freiburg.de/people/ronneber/u-net/
    • https://github.com/dmlc/mxnet/issues/1514
    • https://github.com/orobix/retina-unet
    • https://github.com/fvisin/reseg
    • https://github.com/yulequan/melanoma-recognition
    • http://www.andrewjanowczyk.com/use-case-1-nuclei-segmentation/
    • https://github.com/junyanz/MCILBoost
    • https://github.com/imlab-uiip/lung-segmentation-2d
    • https://github.com/scottykwok/cervix-roi-segmentation-by-unet
    • https://github.com/WeidiXie/cellcountingv2
    • https://github.com/yandexdataschool/YSDA_deeplearning17/blob/master/Seminar6/Seminar%206%20-%20segmentation.ipynb
  • Cascaded-FCN

    • https://github.com/IBBM/Cascaded-FCN
  • Keras

    • https://github.com/jocicmarko/ultrasound-nerve-segmentation
    • https://github.com/EdwardTyantov/ultrasound-nerve-segmentation
    • https://github.com/intact-project/ild-cnn
    • https://github.com/scottykwok/cervix-roi-segmentation-by-unet
    • https://github.com/lishen/end2end-all-conv
  • Tensorflow

    • https://github.com/imatge-upc/liverseg-2017-nipsws
    • https://github.com/DLTK/DLTK/tree/master/examples/applications/MRBrainS13tissuesegmentation
  • Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA)

    • https://github.com/ecobost/cnn4brca
  • Papers:

    • https://www2.warwick.ac.uk/fac/sci/dcs/people/research/csrkbb/tmi2016_ks.pdf
    • Sliding window approach
      • http://people.idsia.ch/~juergen/nips2012.pdf
    • https://github.com/albarqouni/Deep-Learning-for-Medical-Applications#segmentation
    • Data:
    • https://luna16.grand-challenge.org/
    • https://camelyon16.grand-challenge.org/
    • https://github.com/beamandrew/medical-data

Satellite images segmentation

  • https://github.com/mshivaprakash/sat-seg-thesis
  • https://github.com/KGPML/Hyperspectral
  • https://github.com/lopuhin/kaggle-dstl
  • https://github.com/mitmul/ssai
  • https://github.com/mitmul/ssai-cnn
  • https://github.com/azavea/raster-vision
  • https://github.com/nshaud/DeepNetsForEO
  • https://github.com/trailbehind/DeepOSM
  • https://github.com/mapbox/robosat
  • https://github.com/datapink/robosat.pink

    • Data:
    • https://github.com/RSIA-LIESMARS-WHU/RSOD-Dataset-
    • SpaceNet[https://spacenetchallenge.github.io/]
    • https://github.com/chrieke/awesome-satellite-imagery-datasets

Video segmentation

  • https://github.com/shelhamer/clockwork-fcn
  • https://github.com/JingchunCheng/Seg-with-SPN

Autonomous driving

  • https://github.com/MarvinTeichmann/MultiNet
  • https://github.com/MarvinTeichmann/KittiSeg
  • https://github.com/vxy10/p5VehicleDetectionUnet [Keras]
  • https://github.com/ndrplz/self-driving-car
  • https://github.com/mvirgo/MLND-Capstone
  • https://github.com/zhujun98/semanticsegmentation/tree/master/fcn8sroad
  • https://github.com/MaybeShewill-CV/lanenet-lane-detection

Other

Networks by framework (Older list)

  • Keras

    • https://github.com/gakarak/FCNMSCOCOFood_Segmentation
    • https://github.com/abbypa/NNProject_DeepMask
  • TensorFlow

    • https://github.com/warmspringwinds/tf-image-segmentation
  • Caffe

    • https://github.com/xiaolonw/nips14locseg_testonly
    • https://github.com/naibaf7/caffeneuraltool
  • torch

    • https://github.com/erogol/seg-torch
    • https://github.com/phillipi/pix2pix
  • MXNet

    • https://github.com/itijyou/ademxapp

Papers and Code (Older list)

  • Simultaneous detection and segmentation

    • http://www.eecs.berkeley.edu/Research/Projects/CS/vision/shape/sds/
    • https://github.com/bharath272/sds_eccv2014
  • Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation

    • https://github.com/HyeonwooNoh/DecoupledNet
  • Learning to Propose Objects

    • http://vladlen.info/publications/learning-to-propose-objects/
    • https://github.com/philkr/lpo
  • Nonparametric Scene Parsing via Label Transfer

    • http://people.csail.mit.edu/celiu/LabelTransfer/code.html
  • Other

    • https://github.com/cvjena/cn24
    • http://lmb.informatik.uni-freiburg.de/resources/software.php
    • https://github.com/NVIDIA/DIGITS/tree/master/examples/semantic-segmentation
    • http://jamie.shotton.org/work/code.html
    • https://github.com/amueller/textonboost

To look at

  • https://github.com/fchollet/keras/issues/6538
  • https://github.com/warmspringwinds/tensorflow_notes
  • https://github.com/kjw0612/awesome-deep-vision#semantic-segmentation
  • https://github.com/desimone/segmentation-models
  • https://github.com/nightrome/really-awesome-semantic-segmentation
  • https://github.com/kjw0612/awesome-deep-vision#semantic-segmentation
  • http://www.it-caesar.com/list-of-contemporary-semantic-segmentation-datasets/
  • https://github.com/MichaelXin/Awesome-Caffe#23-image-segmentation
  • https://github.com/warmspringwinds/pytorch-segmentation-detection
  • https://github.com/neuropoly/axondeepseg
  • https://github.com/petrochenko-pavel-a/segmentationtrainingpipeline

Blog posts, other:

  • https://handong1587.github.io/deep_learning/2015/10/09/segmentation.html
  • http://www.andrewjanowczyk.com/efficient-pixel-wise-deep-learning-on-large-images/
  • https://devblogs.nvidia.com/parallelforall/image-segmentation-using-digits-5/
  • https://github.com/NVIDIA/DIGITS/tree/master/examples/binary-segmentation
  • https://github.com/NVIDIA/DIGITS/tree/master/examples/semantic-segmentation
  • http://blog.qure.ai/notes/semantic-segmentation-deep-learning-review
  • https://medium.com/@barvinograd1/instance-embedding-instance-segmentation-without-proposals-31946a7c53e1

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