转自https://blog.csdn.net/weixin_41783077/article/details/82020121
转自github，感谢作者mrgloom的整理
链接：https://github.com/mrgloom/awesome-semantic-segmentation
Awesome Semantic Segmentation
Networks by architecture
Semantic segmentation
- U-Net [https://arxiv.org/pdf/1505.04597.pdf] [2015]
<ul><li><a href="https://github.com/zhixuhao/unet" rel="nofollow" data-token="ed4391c9e7ba2271401a1d992299a2dc">https://github.com/zhixuhao/unet</a> [Keras]</li> <li><a href="https://lmb.informatik.uni-freiburg.de/people/ronneber/u-net/" rel="nofollow" data-token="902e15e44de3ff9eb04bc0376fa84f52">https://lmb.informatik.uni-freiburg.de/people/ronneber/u-net/</a> [Caffe + Matlab]</li> <li><a href="https://github.com/jocicmarko/ultrasound-nerve-segmentation" rel="nofollow" data-token="8f2aa2ea7cab73b87f471ca529493d81">https://github.com/jocicmarko/ultrasound-nerve-segmentation</a> [Keras]</li> <li><a href="https://github.com/EdwardTyantov/ultrasound-nerve-segmentation" rel="nofollow" data-token="eb86fbef88b214c4c158f5e2a43f7121">https://github.com/EdwardTyantov/ultrasound-nerve-segmentation</a> [Keras]</li> <li><a href="https://github.com/ZFTurbo/ZF_UNET_224_Pretrained_Model" rel="nofollow" data-token="b6647bfe8fce1b5e0bf47817b39012d3">https://github.com/ZFTurbo/ZF_UNET_224_Pretrained_Model</a> [Keras]</li> <li><a href="https://github.com/yihui-he/u-net" rel="nofollow" data-token="9af8ff1aefb3b757a040db44e33a959a">https://github.com/yihui-he/u-net</a> [Keras]</li> <li><a href="https://github.com/jakeret/tf_unet" rel="nofollow" data-token="f207bf8424ea0146f09e320783135efd">https://github.com/jakeret/tf_unet</a> [Tensorflow]</li> <li><a href="https://github.com/DLTK/DLTK/blob/master/examples/Toy_segmentation/simple_dltk_unet.ipynb" rel="nofollow" data-token="5b1711f9f63e2866b0c90dc88bd5c386">https://github.com/DLTK/DLTK/blob/master/examples/Toy_segmentation/simple_dltk_unet.ipynb</a> [Tensorflow]</li> <li><a href="https://github.com/divamgupta/image-segmentation-keras" rel="nofollow" data-token="a4b8aa890c5ef469366f30c9bc7a6435">https://github.com/divamgupta/image-segmentation-keras</a> [Keras]</li> <li><a href="https://github.com/ZijunDeng/pytorch-semantic-segmentation" rel="nofollow" data-token="a5f77ad954fb2347615e3e079ed0ed03">https://github.com/ZijunDeng/pytorch-semantic-segmentation</a> [PyTorch]</li> <li><a href="https://github.com/akirasosa/mobile-semantic-segmentation" rel="nofollow" data-token="d15d69f949c772ff2698a84d33f18598">https://github.com/akirasosa/mobile-semantic-segmentation</a> [Keras]</li> <li><a href="https://github.com/orobix/retina-unet" rel="nofollow" data-token="d79d95018048974c476a618dd46fd8a7">https://github.com/orobix/retina-unet</a> [Keras]</li> <li><a href="https://github.com/masahi/nnvm-vision-demo/blob/master/unet_segmentation.py" rel="nofollow" data-token="cd792510664bb3ec71d40115822ee9ef">https://github.com/masahi/nnvm-vision-demo/blob/master/unet_segmentation.py</a> [onnx+nnvm]</li> <li><a href="https://github.com/qureai/ultrasound-nerve-segmentation-using-torchnet" rel="nofollow" data-token="f60630a7db1dcd7d22043481dc703b4b">https://github.com/qureai/ultrasound-nerve-segmentation-using-torchnet</a> [Torch]</li> <li><a href="https://github.com/ternaus/TernausNet" rel="nofollow" data-token="92663c38f8a2c09bc5ca8d02145a7645">https://github.com/ternaus/TernausNet</a> [PyTorch]</li> </ul></li> <li>SegNet [<a href="https://arxiv.org/pdf/1511.00561.pdf" rel="nofollow" data-token="a7758f3322e6f0b8014840628e3ab326">https://arxiv.org/pdf/1511.00561.pdf</a>] [2016] <ul><li><a href="https://github.com/alexgkendall/caffe-segnet" rel="nofollow" data-token="0e07363b66abc53d58e2c54567f00fe1">https://github.com/alexgkendall/caffe-segnet</a> [Caffe]</li> <li><a href="https://github.com/developmentseed/caffe/tree/segnet-multi-gpu" rel="nofollow" data-token="c0ead8f228c8e6eb3264890b6ab6ca6a">https://github.com/developmentseed/caffe/tree/segnet-multi-gpu</a> [Caffe]</li> <li><a href="https://github.com/preddy5/segnet" rel="nofollow" data-token="cf917a30c8d952064adb7fe565385283">https://github.com/preddy5/segnet</a> [Keras]</li> <li><a href="https://github.com/imlab-uiip/keras-segnet" rel="nofollow" data-token="40c1c5c79c16d8756f38feebea73a83f">https://github.com/imlab-uiip/keras-segnet</a> [Keras]</li> <li><a href="https://github.com/andreaazzini/segnet" rel="nofollow" data-token="65f8e48587cd05350e4a2d628c1c22c4">https://github.com/andreaazzini/segnet</a> [Tensorflow]</li> <li><a href="https://github.com/fedor-chervinskii/segnet-torch" rel="nofollow" data-token="06684361bacfc994ffd510ab38058c17">https://github.com/fedor-chervinskii/segnet-torch</a> [Torch]</li> <li><a href="https://github.com/0bserver07/Keras-SegNet-Basic" rel="nofollow" data-token="eba3146fd1cb18a0892705e37434155c">https://github.com/0bserver07/Keras-SegNet-Basic</a> [Keras]</li> <li><a href="https://github.com/tkuanlun350/Tensorflow-SegNet" rel="nofollow" data-token="849345c7e0b58ba7d533c8437b3300a0">https://github.com/tkuanlun350/Tensorflow-SegNet</a> [Tensorflow]</li> <li><a href="https://github.com/divamgupta/image-segmentation-keras" rel="nofollow" data-token="a4b8aa890c5ef469366f30c9bc7a6435">https://github.com/divamgupta/image-segmentation-keras</a> [Keras]</li> <li><a href="https://github.com/ZijunDeng/pytorch-semantic-segmentation" rel="nofollow" data-token="a5f77ad954fb2347615e3e079ed0ed03">https://github.com/ZijunDeng/pytorch-semantic-segmentation</a> [PyTorch]</li> <li><a href="https://github.com/chainer/chainercv/tree/master/examples/segnet" rel="nofollow" data-token="c178ef694a61fc235bc6a7657e852219">https://github.com/chainer/chainercv/tree/master/examples/segnet</a> [Chainer]</li> <li><a href="https://github.com/ykamikawa/keras-SegNet" rel="nofollow" data-token="85865df97e57f0b1f6d9be47d3a1fc50">https://github.com/ykamikawa/keras-SegNet</a> [Keras]</li> </ul></li> <li>DeepLab [<a href="https://arxiv.org/pdf/1606.00915.pdf" rel="nofollow" data-token="d16e25ee95816e2eedc941aa0520409e">https://arxiv.org/pdf/1606.00915.pdf</a>] [2017] <ul><li><a href="https://bitbucket.org/deeplab/deeplab-public/" rel="nofollow" data-token="57659e6e5817695606be8edf07406982">https://bitbucket.org/deeplab/deeplab-public/</a> [Caffe]</li> <li><a href="https://github.com/cdmh/deeplab-public" rel="nofollow" data-token="4b1270d74ba62d2571f49c1a7d011f1b">https://github.com/cdmh/deeplab-public</a> [Caffe]</li> <li><a href="https://bitbucket.org/aquariusjay/deeplab-public-ver2" rel="nofollow" data-token="6745fe909b69799d8ea980697321ff34">https://bitbucket.org/aquariusjay/deeplab-public-ver2</a> [Caffe]</li> <li><a href="https://github.com/TheLegendAli/DeepLab-Context" rel="nofollow" data-token="fd6fc608d3ec514104a2e7a5d50e56b5">https://github.com/TheLegendAli/DeepLab-Context</a> [Caffe]</li> <li><a href="https://github.com/msracver/Deformable-ConvNets/tree/master/deeplab" rel="nofollow" data-token="1ed054c93b890519c1c3bb3dfeac3c71">https://github.com/msracver/Deformable-ConvNets/tree/master/deeplab</a> [MXNet]</li> <li><a href="https://github.com/DrSleep/tensorflow-deeplab-resnet" rel="nofollow" data-token="a0a25cc4a5fb47bf7d5c6c36255c8794">https://github.com/DrSleep/tensorflow-deeplab-resnet</a> [Tensorflow]</li> <li><a href="https://github.com/muyang0320/tensorflow-deeplab-resnet-crf" rel="nofollow" data-token="26af77245c2a30bdcb3382c539f5c760">https://github.com/muyang0320/tensorflow-deeplab-resnet-crf</a> [TensorFlow]</li> <li><a href="https://github.com/isht7/pytorch-deeplab-resnet" rel="nofollow" data-token="0c7e0655027411cc10fc8ad3f27c347f">https://github.com/isht7/pytorch-deeplab-resnet</a> [PyTorch]</li> <li><a href="https://github.com/bermanmaxim/jaccardSegment" rel="nofollow" data-token="3bcb1cf9bee837620d177ce953ebdb6f">https://github.com/bermanmaxim/jaccardSegment</a> [PyTorch]</li> <li><a href="https://github.com/martinkersner/train-DeepLab" rel="nofollow" data-token="ca6acd3e9610e6d8b394c159a7f88183">https://github.com/martinkersner/train-DeepLab</a> [Caffe]</li> <li><a href="https://github.com/chenxi116/TF-deeplab" rel="nofollow" data-token="9595082382c189485a3d1e115202992a">https://github.com/chenxi116/TF-deeplab</a> [Tensorflow]</li> <li><a href="https://github.com/bonlime/keras-deeplab-v3-plus" rel="nofollow" data-token="c07aaee7d70e0841a489b55e1261813b">https://github.com/bonlime/keras-deeplab-v3-plus</a> [Keras]</li> </ul></li> <li>FCN [<a href="https://arxiv.org/pdf/1605.06211.pdf" rel="nofollow" data-token="f5ad36524a21d0490dbb99724748b3c5">https://arxiv.org/pdf/1605.06211.pdf</a>] [2016] <ul><li><a href="https://github.com/vlfeat/matconvnet-fcn" rel="nofollow" data-token="181da9813a7dd6ba6d6dba9979f2aa52">https://github.com/vlfeat/matconvnet-fcn</a> [MatConvNet]</li> <li><a href="https://github.com/shelhamer/fcn.berkeleyvision.org" rel="nofollow" data-token="f1fcdbf59422adf825c2146247fbc22d">https://github.com/shelhamer/fcn.berkeleyvision.org</a> [Caffe]</li> <li><a href="https://github.com/MarvinTeichmann/tensorflow-fcn" rel="nofollow" data-token="18ba115f0aa392737dd543b2a16ae3bb">https://github.com/MarvinTeichmann/tensorflow-fcn</a> [Tensorflow]</li> <li><a href="https://github.com/aurora95/Keras-FCN" rel="nofollow" data-token="c243abc2865c9a736d96181e6f066aa4">https://github.com/aurora95/Keras-FCN</a> [Keras]</li> <li><a href="https://github.com/mzaradzki/neuralnets/tree/master/vgg_segmentation_keras" rel="nofollow" data-token="bc03590f667e3cb602a459c4d3d742b8">https://github.com/mzaradzki/neuralnets/tree/master/vgg_segmentation_keras</a> [Keras]</li> <li><a href="https://github.com/k3nt0w/FCN_via_keras" rel="nofollow" data-token="878d68db6114f4f9eebe10b013da622c">https://github.com/k3nt0w/FCN_via_keras</a> [Keras]</li> <li><a href="https://github.com/shekkizh/FCN.tensorflow" rel="nofollow" data-token="8b08ae56272d69fbe7177452cef53563">https://github.com/shekkizh/FCN.tensorflow</a> [Tensorflow]</li> <li><a href="https://github.com/seewalker/tf-pixelwise" rel="nofollow" data-token="5cc7e402971e22d05cca77ed38f242b0">https://github.com/seewalker/tf-pixelwise</a> [Tensorflow]</li> <li><a href="https://github.com/divamgupta/image-segmentation-keras" rel="nofollow" data-token="a4b8aa890c5ef469366f30c9bc7a6435">https://github.com/divamgupta/image-segmentation-keras</a> [Keras]</li> <li><a href="https://github.com/ZijunDeng/pytorch-semantic-segmentation" rel="nofollow" data-token="a5f77ad954fb2347615e3e079ed0ed03">https://github.com/ZijunDeng/pytorch-semantic-segmentation</a> [PyTorch]</li> <li><a href="https://github.com/wkentaro/pytorch-fcn" rel="nofollow" data-token="8e56300c626733168342b06bf9db8e76">https://github.com/wkentaro/pytorch-fcn</a> [PyTorch]</li> <li><a href="https://github.com/wkentaro/fcn" rel="nofollow" data-token="9a13ef465a0d0be419d0e06f28bf50cb">https://github.com/wkentaro/fcn</a> [Chainer]</li> <li><a href="https://github.com/apache/incubator-mxnet/tree/master/example/fcn-xs" rel="nofollow" data-token="c94a5634d5c98675964ec3a501764b9c">https://github.com/apache/incubator-mxnet/tree/master/example/fcn-xs</a> [MxNet]</li> <li><a href="https://github.com/muyang0320/tf-fcn" rel="nofollow" data-token="41097a0d9e577214a68b70e359604e94">https://github.com/muyang0320/tf-fcn</a> [Tensorflow]</li> <li><a href="https://github.com/ycszen/pytorch-seg" rel="nofollow" data-token="01fc983c7d719e729103260422840c54">https://github.com/ycszen/pytorch-seg</a> [PyTorch]</li> <li><a href="https://github.com/Kaixhin/FCN-semantic-segmentation" rel="nofollow" data-token="2ba8659ad08bacff47ef799216d1b8d4">https://github.com/Kaixhin/FCN-semantic-segmentation</a> [PyTorch]</li> <li><a href="https://github.com/petrama/VGGSegmentation" rel="nofollow" data-token="0ad6a391607415357be4d24242ecfcfc">https://github.com/petrama/VGGSegmentation</a> [Tensorflow]</li> <li><a href="https://github.com/simonguist/testing-fcn-for-cityscapes" rel="nofollow" data-token="e8ebc2e53e5587343224449d6fb4670d">https://github.com/simonguist/testing-fcn-for-cityscapes</a> [Caffe]</li> <li><a href="https://github.com/hellochick/semantic-segmentation-tensorflow" rel="nofollow" data-token="ac2d46961dd04a76c662c4a9414c58d9">https://github.com/hellochick/semantic-segmentation-tensorflow</a> [Tensorflow]</li> <li><a href="https://github.com/pierluigiferrari/fcn8s_tensorflow" rel="nofollow" data-token="825b5ea6acbf4c3eec881bac8da5787a">https://github.com/pierluigiferrari/fcn8s_tensorflow</a> [Tensorflow]</li> </ul></li> <li>ENet [<a href="https://arxiv.org/pdf/1606.02147.pdf" rel="nofollow" data-token="be5b77979b6e058642b9c8646a7a7c1a">https://arxiv.org/pdf/1606.02147.pdf</a>] [2016] <ul><li><a href="https://github.com/TimoSaemann/ENet" rel="nofollow" data-token="5a2e0661fd37d5168626f175fac51019">https://github.com/TimoSaemann/ENet</a> [Caffe]</li> <li><a href="https://github.com/e-lab/ENet-training" rel="nofollow" data-token="1594ed6e0d01142220c315d230803c5f">https://github.com/e-lab/ENet-training</a> [Torch]</li> <li><a href="https://github.com/PavlosMelissinos/enet-keras" rel="nofollow" data-token="c864e0212f6fe6d1ddd0d378a9a96181">https://github.com/PavlosMelissinos/enet-keras</a> [Keras]</li> <li><a href="https://github.com/fregu856/segmentation" rel="nofollow" data-token="08eac7c3efde382afe683a52993a67e9">https://github.com/fregu856/segmentation</a> [Tensorflow]</li> <li><a href="https://github.com/kwotsin/TensorFlow-ENet" rel="nofollow" data-token="ff62933c69e1a793ac5ee73ce2cbecf4">https://github.com/kwotsin/TensorFlow-ENet</a> [Tensorflow]</li> </ul></li> <li>LinkNet [<a href="https://arxiv.org/pdf/1707.03718.pdf" rel="nofollow" data-token="d060ff448186ee3ba7d586e37a83b042">https://arxiv.org/pdf/1707.03718.pdf</a>] [2017] <ul><li><a href="https://github.com/e-lab/LinkNet" rel="nofollow" data-token="f3e81a016a3673a9e25b1c0e954831dc">https://github.com/e-lab/LinkNet</a> [Torch]</li> </ul></li> <li>DenseNet [<a href="https://arxiv.org/pdf/1608.06993.pdf" rel="nofollow" data-token="9d025b41211a9755f653e59ecf2f7ef7">https://arxiv.org/pdf/1608.06993.pdf</a>] [2018] <ul><li><a href="https://github.com/flyyufelix/DenseNet-Keras" rel="nofollow" data-token="0b3647e87644ce0a25c807480f1f98b0">https://github.com/flyyufelix/DenseNet-Keras</a> [Keras]</li> </ul></li> <li>Tiramisu [<a href="https://arxiv.org/pdf/1611.09326.pdf" rel="nofollow" data-token="b7d6c7fadb19b6285020d3a054ac33bb">https://arxiv.org/pdf/1611.09326.pdf</a>] [2017] <ul><li><a href="https://github.com/0bserver07/One-Hundred-Layers-Tiramisu" rel="nofollow" data-token="de8ff8e04615749d3da0a6bbda790383">https://github.com/0bserver07/One-Hundred-Layers-Tiramisu</a> [Keras]</li> <li><a href="https://github.com/SimJeg/FC-DenseNet" rel="nofollow" data-token="7e46986bcdb380cb493b85fbf5696d4b">https://github.com/SimJeg/FC-DenseNet</a> [Lasagne]</li> </ul></li> <li>DilatedNet [<a href="https://arxiv.org/pdf/1511.07122.pdf" rel="nofollow" data-token="a07af65215c6b791de0d66a8e5c7226d">https://arxiv.org/pdf/1511.07122.pdf</a>] [2016] <ul><li><a href="https://github.com/nicolov/segmentation_keras" rel="nofollow" data-token="ce57098c5db1f4af57b3efe14088277e">https://github.com/nicolov/segmentation_keras</a> [Keras]</li> <li><a href="https://github.com/fyu/dilation" rel="nofollow" data-token="2e9632bf3938d2fa90e11fc61e6876d8">https://github.com/fyu/dilation</a> [Caffe]</li> <li><a href="https://github.com/fyu/drn#semantic-image-segmentataion" rel="nofollow" data-token="581136bd96ce0cf018d0857612d8e10e">https://github.com/fyu/drn#semantic-image-segmentataion</a> [PyTorch]</li> <li><a href="https://github.com/hangzhaomit/semantic-segmentation-pytorch" rel="nofollow" data-token="bdada0c5c86cc77536a198a1a2f9bfbb">https://github.com/hangzhaomit/semantic-segmentation-pytorch</a> [PyTorch]</li> </ul></li> <li>PixelNet [<a href="https://arxiv.org/pdf/1609.06694.pdf" rel="nofollow" data-token="7339d009ffc4690eddf5b2ec56eeee7f">https://arxiv.org/pdf/1609.06694.pdf</a>] [2016] <ul><li><a href="https://github.com/aayushbansal/PixelNet" rel="nofollow" data-token="accf61aa28802289cfcf413c20f87dea">https://github.com/aayushbansal/PixelNet</a> [Caffe]</li> </ul></li> <li>ICNet [<a href="https://arxiv.org/pdf/1704.08545.pdf" rel="nofollow" data-token="04e58b46a18b02fca688af4b698d2547">https://arxiv.org/pdf/1704.08545.pdf</a>] [2017] <ul><li><a href="https://github.com/hszhao/ICNet" rel="nofollow" data-token="6156d17a3273cf005c70dca8e176d553">https://github.com/hszhao/ICNet</a> [Caffe]</li> <li><a href="https://github.com/ai-tor/Keras-ICNet" rel="nofollow" data-token="163d76f26f7f7ed016248e5325c911d2">https://github.com/ai-tor/Keras-ICNet</a> [Keras]</li> <li><a href="https://github.com/hellochick/ICNet-tensorflow" rel="nofollow" data-token="882ce11219cf6e27a0571854bf2c7034">https://github.com/hellochick/ICNet-tensorflow</a> [Tensorflow]</li> </ul></li> <li>ERFNet [<a href="http://www.robesafe.uah.es/personal/eduardo.romera/pdfs/Romera17iv.pdf" rel="nofollow" data-token="56dbf89714f6ceded57f931a251409f9">http://www.robesafe.uah.es/personal/eduardo.romera/pdfs/Romera17iv.pdf</a>] [?] <ul><li><a href="https://github.com/Eromera/erfnet" rel="nofollow" data-token="f220474ced24c7e1dcd7ce4400721732">https://github.com/Eromera/erfnet</a> [Torch]</li> <li><a href="https://github.com/Eromera/erfnet_pytorch" rel="nofollow" data-token="f5166af1e2219c008ffe274da9ef9b53">https://github.com/Eromera/erfnet_pytorch</a> [PyTorch]</li> </ul></li> <li>RefineNet [<a href="https://arxiv.org/pdf/1611.06612.pdf" rel="nofollow" data-token="6442278ed9363b442f88cf0ac80268e5">https://arxiv.org/pdf/1611.06612.pdf</a>] [2016] <ul><li><a href="https://github.com/guosheng/refinenet" rel="nofollow" data-token="9c332c9355efc5d363db4250451edc1d">https://github.com/guosheng/refinenet</a> [MatConvNet]</li> </ul></li> <li>PSPNet [<a href="https://arxiv.org/pdf/1612.01105.pdf,https://hszhao.github.io/projects/pspnet/" rel="nofollow" data-token="51ded330538ec85307de5cc3d22b112c">https://arxiv.org/pdf/1612.01105.pdf,https://hszhao.github.io/projects/pspnet/</a>] [2017] <ul><li><a href="https://github.com/hszhao/PSPNet" rel="nofollow" data-token="60090925a0707df1a9cc6923237ad098">https://github.com/hszhao/PSPNet</a> [Caffe]</li> <li><a href="https://github.com/ZijunDeng/pytorch-semantic-segmentation" rel="nofollow" data-token="a5f77ad954fb2347615e3e079ed0ed03">https://github.com/ZijunDeng/pytorch-semantic-segmentation</a> [PyTorch]</li> <li><a href="https://github.com/mitmul/chainer-pspnet" rel="nofollow" data-token="3bb28c343b0fa62bbb959ca5ac2e4203">https://github.com/mitmul/chainer-pspnet</a> [Chainer]</li> <li><a href="https://github.com/Vladkryvoruchko/PSPNet-Keras-tensorflow" rel="nofollow" data-token="c14e7f499b1cc65449ebc984a781e7fc">https://github.com/Vladkryvoruchko/PSPNet-Keras-tensorflow</a> [Keras/Tensorflow]</li> <li><a href="https://github.com/pudae/tensorflow-pspnet" rel="nofollow" data-token="d1443160c832726ac5f51aedbc1b34ce">https://github.com/pudae/tensorflow-pspnet</a> [Tensorflow]</li> <li><a href="https://github.com/hellochick/PSPNet-tensorflow" rel="nofollow" data-token="c1a7caf5f3c671279d91826fe96a014c">https://github.com/hellochick/PSPNet-tensorflow</a> [Tensorflow]</li> <li><a href="https://github.com/hellochick/semantic-segmentation-tensorflow" rel="nofollow" data-token="ac2d46961dd04a76c662c4a9414c58d9">https://github.com/hellochick/semantic-segmentation-tensorflow</a> [Tensorflow]</li> </ul></li> <li>DeconvNet [<a href="https://arxiv.org/pdf/1505.04366.pdf" rel="nofollow" data-token="8e35f606d0217380674d212189870f6d">https://arxiv.org/pdf/1505.04366.pdf</a>] [2015] <ul><li><a href="http://cvlab.postech.ac.kr/research/deconvnet/" rel="nofollow" data-token="2558f73e61dcc8ccce11c78d5fab1261">http://cvlab.postech.ac.kr/research/deconvnet/</a> [Caffe]</li> <li><a href="https://github.com/HyeonwooNoh/DeconvNet" rel="nofollow" data-token="66a35cf3a38814b94d534667dcc3583b">https://github.com/HyeonwooNoh/DeconvNet</a> [Caffe]</li> <li><a href="https://github.com/f*bormann/Tensorflow-DeconvNet-Segmentation" rel="nofollow" data-token="4a7a9f91926ba2b3e65696fcbe2efc34">https://github.com/f*bormann/Tensorflow-DeconvNet-Segmentation</a> [Tensorflow]</li> </ul></li> <li>FRRN [<a href="https://arxiv.org/pdf/1611.08323.pdf" rel="nofollow" data-token="9d4ac4730200cecadec4ca46fb7399c0">https://arxiv.org/pdf/1611.08323.pdf</a>] [2016] <ul><li><a href="https://github.com/TobyPDE/FRRN" rel="nofollow" data-token="eb4f5a928357782c9d56da095a63eaaf">https://github.com/TobyPDE/FRRN</a> [Lasagne]</li> </ul></li> <li>GCN [<a href="https://arxiv.org/pdf/1703.02719.pdf" rel="nofollow" data-token="037f12bd4239505b5ff999ca394959c7">https://arxiv.org/pdf/1703.02719.pdf</a>] [2017] <ul><li><a href="https://github.com/ZijunDeng/pytorch-semantic-segmentation" rel="nofollow" data-token="a5f77ad954fb2347615e3e079ed0ed03">https://github.com/ZijunDeng/pytorch-semantic-segmentation</a> [PyTorch]</li> <li><a href="https://github.com/ycszen/pytorch-seg" rel="nofollow" data-token="01fc983c7d719e729103260422840c54">https://github.com/ycszen/pytorch-seg</a> [PyTorch]</li> </ul></li> <li>LRR [<a href="https://arxiv.org/pdf/1605.02264.pdf" rel="nofollow" data-token="76f67b064e051587853fbd435e7b6c46">https://arxiv.org/pdf/1605.02264.pdf</a>] [2016] <ul><li><a href="https://github.com/golnazghiasi/LRR" rel="nofollow" data-token="62182f01fd8fa4859e6c1acc715ae624">https://github.com/golnazghiasi/LRR</a> [Matconvnet]</li> </ul></li> <li>DUC, HDC [<a href="https://arxiv.org/pdf/1702.08502.pdf" rel="nofollow" data-token="bec92ddcab665c11aee6c21a6df7de6a">https://arxiv.org/pdf/1702.08502.pdf</a>] [2017] <ul><li><a href="https://github.com/ZijunDeng/pytorch-semantic-segmentation" rel="nofollow" data-token="a5f77ad954fb2347615e3e079ed0ed03">https://github.com/ZijunDeng/pytorch-semantic-segmentation</a> [PyTorch]</li> <li><a href="https://github.com/ycszen/pytorch-seg" rel="nofollow" data-token="01fc983c7d719e729103260422840c54">https://github.com/ycszen/pytorch-seg</a> [PyTorch]</li> </ul></li> <li>MultiNet [<a href="https://arxiv.org/pdf/1612.07695.pdf" rel="nofollow" data-token="3c0f616dc226bca5b8ac4eab3d21e37f">https://arxiv.org/pdf/1612.07695.pdf</a>] [2016] <ul><li><a href="https://github.com/MarvinTeichmann/MultiNet" rel="nofollow" data-token="afd77a50a73e8d1eeaaf337ae8071e08">https://github.com/MarvinTeichmann/MultiNet</a></li> <li><a href="https://github.com/MarvinTeichmann/KittiSeg" rel="nofollow" data-token="d3608d7466a7781d69fca1aff93cb367">https://github.com/MarvinTeichmann/KittiSeg</a></li> </ul></li> <li>Segaware [<a href="https://arxiv.org/pdf/1708.04607.pdf" rel="nofollow" data-token="fea30d528fe929faa6c3eca67c2a8d71">https://arxiv.org/pdf/1708.04607.pdf</a>] [2017] <ul><li><a href="https://github.com/aharley/segaware" rel="nofollow" data-token="efa83370979071cdf4a9f01623138065">https://github.com/aharley/segaware</a> [Caffe]</li> </ul></li> <li>Semantic Segmentation using Adversarial Networks [<a href="https://arxiv.org/pdf/1611.08408.pdf" rel="nofollow" data-token="1d641c150acd20f1c72080ff71a4c225">https://arxiv.org/pdf/1611.08408.pdf</a>] [2016] <ul><li><a href="https://github.com/oyam/Semantic-Segmentation-using-Adversarial-Networks" rel="nofollow" data-token="12d1d400ba88893f1c85726422b58592">https://github.com/oyam/Semantic-Segmentation-using-Adversarial-Networks</a> [Chainer]</li> </ul></li> <li>PixelDCN [<a href="https://arxiv.org/pdf/1705.06820.pdf" rel="nofollow" data-token="7650c1d61f20205618129d788a0d6e94">https://arxiv.org/pdf/1705.06820.pdf</a>] [2017] <ul><li><a href="https://github.com/HongyangGao/PixelDCN" rel="nofollow" data-token="5b5ddddc527cac69d9f359c1f3385742">https://github.com/HongyangGao/PixelDCN</a> [Tensorflow]</li> </ul></li> <li>ShuffleSeg [<a href="https://arxiv.org/pdf/1803.03816.pdf" rel="nofollow" data-token="2171d75f50745004ddddc02fa5ca797c">https://arxiv.org/pdf/1803.03816.pdf</a>] [2018] <ul><li><a href="https://github.com/MSiam/TFSegmentation" rel="nofollow" data-token="e4785179d24a1d3e34b2166f70d3c099">https://github.com/MSiam/TFSegmentation</a> [TensorFlow]</li> </ul></li> <li>AdaptSegNet [<a href="https://arxiv.org/pdf/1802.10349.pdf" rel="nofollow" data-token="1e0b1973be9f555b94e0205071d66731">https://arxiv.org/pdf/1802.10349.pdf</a>] [2018] <ul><li><a href="https://github.com/wasidennis/AdaptSegNet" rel="nofollow" data-token="7eed188bc1aa4d48d21fc0fbd859586f">https://github.com/wasidennis/AdaptSegNet</a> [PyTorch]</li> </ul></li> <li>TuSimple-DUC [<a href="https://arxiv.org/pdf/1702.08502.pdf" rel="nofollow" data-token="bec92ddcab665c11aee6c21a6df7de6a">https://arxiv.org/pdf/1702.08502.pdf</a>] [2018] <ul><li><a href="https://github.com/TuSimple/TuSimple-DUC" rel="nofollow" data-token="ffa4853aaae9add735802a7fd674ac1c">https://github.com/TuSimple/TuSimple-DUC</a> [MxNet]</li> </ul></li>
Instance aware segmentation
- FCIS [https://arxiv.org/pdf/1611.07709.pdf]
<ul><li><a href="https://github.com/msracver/FCIS" rel="nofollow" data-token="c0a7d8ee52ce32f4ab265741fb7b0ae6">https://github.com/msracver/FCIS</a> [MxNet]</li> </ul></li> <li>MNC [<a href="https://arxiv.org/pdf/1512.04412.pdf" rel="nofollow" data-token="c18b8ca79f87cf581159cb3ee5c4c9d5">https://arxiv.org/pdf/1512.04412.pdf</a>] <ul><li><a href="https://github.com/daijifeng001/MNC" rel="nofollow" data-token="01885ea12696b8fe7187e569e1a36282">https://github.com/daijifeng001/MNC</a> [Caffe]</li> </ul></li> <li>DeepMask [<a href="https://arxiv.org/pdf/1506.06204.pdf" rel="nofollow" data-token="8cb7b03edc4e40bd8c936c2950844b5b">https://arxiv.org/pdf/1506.06204.pdf</a>] <ul><li><a href="https://github.com/facebookresearch/deepmask" rel="nofollow" data-token="5f6d14d53ea37e5393d0ebf1f3e9700e">https://github.com/facebookresearch/deepmask</a> [Torch]</li> </ul></li> <li>SharpMask [<a href="https://arxiv.org/pdf/1603.08695.pdf" rel="nofollow" data-token="f543a5aea72df9c6a90f93aaf762cd10">https://arxiv.org/pdf/1603.08695.pdf</a>] <ul><li><a href="https://github.com/facebookresearch/deepmask" rel="nofollow" data-token="5f6d14d53ea37e5393d0ebf1f3e9700e">https://github.com/facebookresearch/deepmask</a> [Torch]</li> </ul></li> <li>Mask-RCNN [<a href="https://arxiv.org/pdf/1703.06870.pdf" rel="nofollow" data-token="7ba3aabee1bc48993a92ce51d7b10881">https://arxiv.org/pdf/1703.06870.pdf</a>] <ul><li><a href="https://github.com/CharlesShang/FastMaskRCNN" rel="nofollow" data-token="4a5b28446049f344204afc177db1afac">https://github.com/CharlesShang/FastMaskRCNN</a> [Tensorflow]</li> <li><a href="https://github.com/jasjeetIM/Mask-RCNN" rel="nofollow" data-token="a4099162024d5652d613776435d3f2a7">https://github.com/jasjeetIM/Mask-RCNN</a> [Caffe]</li> <li><a href="https://github.com/TuSimple/mx-maskrcnn" rel="nofollow" data-token="a62d77db6748bda6299eba2e81ce169f">https://github.com/TuSimple/mx-maskrcnn</a> [MxNet]</li> <li><a href="https://github.com/matterport/Mask_RCNN" rel="nofollow" data-token="d07ca7dfad76cb1195acc193cda3b5db">https://github.com/matterport/Mask_RCNN</a> [Keras]</li> </ul></li> <li>RIS [<a href="https://arxiv.org/pdf/1511.08250.pdf" rel="nofollow" data-token="a7578a6fc91496ef1a414539f0d5b331">https://arxiv.org/pdf/1511.08250.pdf</a>] <ul><li><a href="https://github.com/bernard24/RIS" rel="nofollow" data-token="72087647cd40e0376ec6a9727792b4a7">https://github.com/bernard24/RIS</a> [Torch]</li> </ul></li> <li>FastMask [<a href="https://arxiv.org/pdf/1612.08843.pdf" rel="nofollow" data-token="a1952ceb37c577a6d8c45d0acd3abe68">https://arxiv.org/pdf/1612.08843.pdf</a>] <ul><li><a href="https://github.com/voidrank/FastMask" rel="nofollow" data-token="665951a520fad44b7ff22705444d2cb5">https://github.com/voidrank/FastMask</a> [Caffe]</li> </ul></li> <li>BlitzNet [<a href="https://arxiv.org/pdf/1708.02813.pdf" rel="nofollow" data-token="4731dba076e3d1b89e87ff67813c1311">https://arxiv.org/pdf/1708.02813.pdf</a>] <ul><li><a href="https://github.com/dvornikita/blitznet" rel="nofollow" data-token="dc3d12aa2f0dc31997984838f4f352cb">https://github.com/dvornikita/blitznet</a> [Tensorflow]</li> </ul></li>
Weakly-supervised segmentation
- SEC [https://arxiv.org/pdf/1603.06098.pdf]
<ul><li><a href="https://github.com/kolesman/SEC" rel="nofollow" data-token="bf6cdba01ad2de448f34a234283c15b0">https://github.com/kolesman/SEC</a> [Caffe]</li> </ul></li>
RNN
- ReNet [https://arxiv.org/pdf/1505.00393.pdf]
<ul><li><a href="https://github.com/fvisin/reseg" rel="nofollow" data-token="2c9de896d3c3ef2b6aaeef4b042e6683">https://github.com/fvisin/reseg</a> [Lasagne]</li> </ul></li> <li>ReSeg [<a href="https://arxiv.org/pdf/1511.07053.pdf" rel="nofollow" data-token="0dffd1ced29550f33c5291756305cc9a">https://arxiv.org/pdf/1511.07053.pdf</a>] <ul><li><a href="https://github.com/Wizaron/reseg-pytorch" rel="nofollow" data-token="21c8abc09072f0e527308ea4b32b5ca4">https://github.com/Wizaron/reseg-pytorch</a> [PyTorch]</li> <li><a href="https://github.com/fvisin/reseg" rel="nofollow" data-token="2c9de896d3c3ef2b6aaeef4b042e6683">https://github.com/fvisin/reseg</a> [Lasagne]</li> </ul></li> <li>RIS [<a href="https://arxiv.org/pdf/1511.08250.pdf" rel="nofollow" data-token="a7578a6fc91496ef1a414539f0d5b331">https://arxiv.org/pdf/1511.08250.pdf</a>] <ul><li><a href="https://github.com/bernard24/RIS" rel="nofollow" data-token="72087647cd40e0376ec6a9727792b4a7">https://github.com/bernard24/RIS</a> [Torch]</li> </ul></li> <li>CRF-RNN [<a href="http://www.robots.ox.ac.uk/~szheng/papers/CRFasRNN.pdf" rel="nofollow" data-token="1e6f8653b1e05117586f843a255bb4f9">http://www.robots.ox.ac.uk/%7Eszheng/papers/CRFasRNN.pdf</a>] <ul><li><a href="https://github.com/martinkersner/train-CRF-RNN" rel="nofollow" data-token="b89b40757b7bf09aedffaee09e8d0045">https://github.com/martinkersner/train-CRF-RNN</a> [Caffe]</li> <li><a href="https://github.com/torrvision/crfasrnn" rel="nofollow" data-token="5f0156466b8e8734ffa8cc62a4494862">https://github.com/torrvision/crfasrnn</a> [Caffe]</li> <li><a href="https://github.com/NP-coder/CLPS1520Project" rel="nofollow" data-token="232b7643e907d1fc221df093eff2e83d">https://github.com/NP-coder/CLPS1520Project</a> [Tensorflow]</li> <li><a href="https://github.com/renmengye/rec-attend-public" rel="nofollow" data-token="9db49bea09e2d9ceb2033d0930412a6a">https://github.com/renmengye/rec-attend-public</a> [Tensorflow]</li> <li><a href="https://github.com/sadeepj/crfasrnn_keras" rel="nofollow" data-token="1d0aa2c8648367c42055dde88accbff9">https://github.com/sadeepj/crfasrnn_keras</a> [Keras]</li> </ul></li>
GANS
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:
- Stanford Background Dataset
- Sift Flow Dataset
- Barcelona Dataset
- Microsoft COCO dataset
- MSRC Dataset
- LITS Liver Tumor Segmentation Dataset
- KITTI
- Pascal Context
- Data from Games dataset
- Human parsing dataset
- Mapillary Vistas Dataset
- Microsoft AirSim
- MIT Scene Parsing Benchmark
- COCO 2017 Stuff Segmentation Challenge
- ADE20K Dataset
- INRIA Annotations for Graz-02
- Daimler dataset
- ISBI Challenge: Segmentation of neuronal structures in EM stacks
- INRIA Annotations for Graz-02 (IG02)
- Pratheepan Dataset
- Clothing Co-Parsing (CCP) Dataset
- Inria Aerial Image
- ApolloScape
- UrbanMapper3D
- RoadDetector
Benchmarks
- 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]
Starter code
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
Results:
Metrics
Other lists
- https://github.com/tangzhenyu/SemanticSegmentation_DL
- https://github.com/nightrome/really-awesome-semantic-segmentation
Medical image segmentation:
-
DIGITS
<ul><li><a href="https://github.com/NVIDIA/DIGITS/tree/master/examples/medical-imaging" rel="nofollow">https://github.com/NVIDIA/DIGITS/tree/master/examples/medical-imaging</a></li> </ul></li> <li> <p>U-Net: Convolutional Networks for Biomedical Image Segmentation</p> <ul><li><a href="http://lmb.informatik.uni-freiburg.de/people/ronneber/u-net/" rel="nofollow" data-token="da19edf78875e75ae18f347d41b27337">http://lmb.informatik.uni-freiburg.de/people/ronneber/u-net/</a></li> <li><a href="https://github.com/dmlc/mxnet/issues/1514" rel="nofollow" data-token="ba235b4460c146145114b889dbbb511c">https://github.com/dmlc/mxnet/issues/1514</a></li> <li><a href="https://github.com/orobix/retina-unet" rel="nofollow" data-token="d79d95018048974c476a618dd46fd8a7">https://github.com/orobix/retina-unet</a></li> <li><a href="https://github.com/fvisin/reseg" rel="nofollow" data-token="2c9de896d3c3ef2b6aaeef4b042e6683">https://github.com/fvisin/reseg</a></li> <li><a href="https://github.com/yulequan/melanoma-recognition" rel="nofollow" data-token="a17d7b634cc2574f27f3d3c5d78cfb8c">https://github.com/yulequan/melanoma-recognition</a></li> <li><a href="http://www.andrewjanowczyk.com/use-case-1-nuclei-segmentation/" rel="nofollow" data-token="224dfd76d2da49bfc143609aad989cdb">http://www.andrewjanowczyk.com/use-case-1-nuclei-segmentation/</a></li> <li><a href="https://github.com/junyanz/MCILBoost" rel="nofollow" data-token="f0aacb0dba25a1abe550ffbcab6ac638">https://github.com/junyanz/MCILBoost</a></li> <li><a href="https://github.com/imlab-uiip/lung-segmentation-2d" rel="nofollow" data-token="1c0945a2d44c97348a466a4080bd4db5">https://github.com/imlab-uiip/lung-segmentation-2d</a></li> <li><a href="https://github.com/scottykwok/cervix-roi-segmentation-by-unet" rel="nofollow" data-token="0df413a8c6794ff59ee29112c1dac52e">https://github.com/scottykwok/cervix-roi-segmentation-by-unet</a></li> <li><a href="https://github.com/WeidiXie/cell_counting_v2" rel="nofollow" data-token="a59c36c71ae71c4124737cb192de2433">https://github.com/WeidiXie/cell_counting_v2</a></li> <li><a href="https://github.com/yandexdataschool/YSDA_deeplearning17/blob/master/Seminar6/Seminar%206%20-%20segmentation.ipynb" rel="nofollow" data-token="c6c7d1b2359497319c0f076017cb3b3e">https://github.com/yandexdataschool/YSDA_deeplearning17/blob/master/Seminar6/Seminar%206%20-%20segmentation.ipynb</a></li> </ul></li> <li> <p>Cascaded-FCN</p> <ul><li><a href="https://github.com/IBBM/Cascaded-FCN" rel="nofollow" data-token="ac7404d33845684ab167b99c3b7c369c">https://github.com/IBBM/Cascaded-FCN</a></li> </ul></li> <li> <p>Keras</p> <ul><li><a href="https://github.com/jocicmarko/ultrasound-nerve-segmentation" rel="nofollow" data-token="8f2aa2ea7cab73b87f471ca529493d81">https://github.com/jocicmarko/ultrasound-nerve-segmentation</a></li> <li><a href="https://github.com/EdwardTyantov/ultrasound-nerve-segmentation" rel="nofollow" data-token="eb86fbef88b214c4c158f5e2a43f7121">https://github.com/EdwardTyantov/ultrasound-nerve-segmentation</a></li> <li><a href="https://github.com/intact-project/ild-cnn" rel="nofollow" data-token="1e61a8cb866d492c45e5635120568cd2">https://github.com/intact-project/ild-cnn</a></li> <li><a href="https://github.com/scottykwok/cervix-roi-segmentation-by-unet" rel="nofollow" data-token="0df413a8c6794ff59ee29112c1dac52e">https://github.com/scottykwok/cervix-roi-segmentation-by-unet</a></li> <li><a href="https://github.com/lishen/end2end-all-conv" rel="nofollow" data-token="f98d6225076b3b3112dd5e4443a95625">https://github.com/lishen/end2end-all-conv</a></li> </ul></li> <li> <p>Tensorflow</p> <ul><li><a href="https://github.com/imatge-upc/liverseg-2017-nipsws" rel="nofollow" data-token="414544231f6607d4b6fb4c46d3df8480">https://github.com/imatge-upc/liverseg-2017-nipsws</a></li> </ul></li> <li> <p>Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA)</p> <ul><li><a href="https://github.com/ecobost/cnn4brca" rel="nofollow" data-token="5a2dadf26d9861d77679dadd1bb6072b">https://github.com/ecobost/cnn4brca</a></li> </ul></li> <li> <p>Papers:</p> <ul><li><a href="https://www2.warwick.ac.uk/fac/sci/dcs/people/research/csrkbb/tmi2016_ks.pdf" rel="nofollow" data-token="a762297f0aa6d0c3b14f7313e7ae18f5">https://www2.warwick.ac.uk/fac/sci/dcs/people/research/csrkbb/tmi2016_ks.pdf</a></li> <li>Sliding window approach <ul><li><a href="http://people.idsia.ch/~juergen/nips2012.pdf" rel="nofollow" data-token="6671c5281dd5fc6ac30c0a78a948c405">http://people.idsia.ch/~juergen/nips2012.pdf</a></li> </ul></li> <li><a href="https://github.com/albarqouni/Deep-Learning-for-Medical-Applications#segmentation" rel="nofollow" data-token="aa5d9f1eccf4116dc85b620c410c1ca7">https://github.com/albarqouni/Deep-Learning-for-Medical-Applications#segmentation</a></li> </ul></li> <li> <p>Data:</p> <ul><li><a href="https://luna16.grand-challenge.org/" rel="nofollow" data-token="2275b112de266fd5ffb32688a11448fb">https://luna16.grand-challenge.org/</a></li> <li><a href="https://camelyon16.grand-challenge.org/" rel="nofollow" data-token="c8fa9570833533da23557bb04f8122f6">https://camelyon16.grand-challenge.org/</a></li> <li><a href="https://github.com/beamandrew/medical-data" rel="nofollow" data-token="9dfcf608cb785b06951eba9d27b819e3">https://github.com/beamandrew/medical-data</a></li> </ul></li>
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
- Data:
Video segmentation
Autonomous driving
- https://github.com/MarvinTeichmann/MultiNet
- https://github.com/MarvinTeichmann/KittiSeg
- https://github.com/vxy10/p5_VehicleDetection_Unet [Keras]
- https://github.com/ndrplz/self-driving-car
- https://github.com/mvirgo/MLND-Capstone
- https://github.com/zhujun98/semantic_segmentation/tree/master/fcn8s_road
Other
Networks by framework (Older list)
-
Keras
<ul><li><a href="https://github.com/gakarak/FCN_MSCOCO_Food_Segmentation" rel="nofollow" data-token="7db7d781c59c9b56f33c84adfcd7ec52">https://github.com/gakarak/FCN_MSCOCO_Food_Segmentation</a></li> <li><a href="https://github.com/abbypa/NNProject_DeepMask" rel="nofollow" data-token="bd32df2ff6633a0d33fc68d4ed54e288">https://github.com/abbypa/NNProject_DeepMask</a></li> </ul></li> <li> <p>TensorFlow</p> <ul><li><a href="https://github.com/warmspringwinds/tf-image-segmentation" rel="nofollow" data-token="457fdc5622a52fa148fad6649b1b0383">https://github.com/warmspringwinds/tf-image-segmentation</a></li> </ul></li> <li> <p>Caffe</p> <ul><li><a href="https://github.com/xiaolonw/nips14_loc_seg_testonly" rel="nofollow" data-token="3a5455be020516d80207f113d136670c">https://github.com/xiaolonw/nips14_loc_seg_testonly</a></li> <li><a href="https://github.com/naibaf7/caffe_neural_tool" rel="nofollow" data-token="3131e2e73af41d612c0a7519b79a5bb9">https://github.com/naibaf7/caffe_neural_tool</a></li> </ul></li> <li> <p>torch</p> <ul><li><a href="https://github.com/erogol/seg-torch" rel="nofollow" data-token="d3a22497c5dc621ba4faf685c49a3623">https://github.com/erogol/seg-torch</a></li> <li><a href="https://github.com/phillipi/pix2pix" rel="nofollow" data-token="9f86e046c5deec18bddde7a4b02193b4">https://github.com/phillipi/pix2pix</a></li> </ul></li> <li> <p>MXNet</p> <ul><li><a href="https://github.com/itijyou/ademxapp" rel="nofollow" data-token="277eb5c1486e842c5363e9557202fa20">https://github.com/itijyou/ademxapp</a></li> </ul></li>
Papers and Code (Older list)
-
Simultaneous detection and segmentation
<ul><li><a href="http://www.eecs.berkeley.edu/Research/Projects/CS/vision/shape/sds/" rel="nofollow">http://www.eecs.berkeley.edu/Research/Projects/CS/vision/shape/sds/</a></li> <li><a href="https://github.com/bharath272/sds_eccv2014" rel="nofollow" data-token="2f0c92f66010b2305411177979bad924">https://github.com/bharath272/sds_eccv2014</a></li> </ul></li> <li> <p>Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation</p> <ul><li><a href="https://github.com/HyeonwooNoh/DecoupledNet" rel="nofollow" data-token="e5bd613283846d4d8c4551326021ae90">https://github.com/HyeonwooNoh/DecoupledNet</a></li> </ul></li> <li> <p>Learning to Propose Objects</p> <ul><li><a href="http://vladlen.info/publications/learning-to-propose-objects/" rel="nofollow" data-token="a16e6b2f3242ac5843fcb12331aa83ea">http://vladlen.info/publications/learning-to-propose-objects/</a></li> <li><a href="https://github.com/philkr/lpo" rel="nofollow" data-token="d98dab2d0b0d440ef2292d8974dd9b47">https://github.com/philkr/lpo</a></li> </ul></li> <li> <p>Nonparametric Scene Parsing via Label Transfer</p> <ul><li><a href="http://people.csail.mit.edu/celiu/LabelTransfer/code.html" rel="nofollow" data-token="b2b1fdd8f40e234a37c6b3e8f53f3c74">http://people.csail.mit.edu/celiu/LabelTransfer/code.html</a></li> </ul></li> <li> <p>Other</p> <ul><li><a href="https://github.com/cvjena/cn24" rel="nofollow" data-token="e11f75e1efc38ed7c4fcffc5a77efeb3">https://github.com/cvjena/cn24</a></li> <li><a href="http://lmb.informatik.uni-freiburg.de/resources/software.php" rel="nofollow" data-token="b64039e4bd91f2c0ff76553ae455700b">http://lmb.informatik.uni-freiburg.de/resources/software.php</a></li> <li><a href="https://github.com/NVIDIA/DIGITS/tree/master/examples/semantic-segmentation" rel="nofollow" data-token="7110d5d05bca0f44402da8fc706a6851">https://github.com/NVIDIA/DIGITS/tree/master/examples/semantic-segmentation</a></li> <li><a href="http://jamie.shotton.org/work/code.html" rel="nofollow" data-token="d94232c1d1d924e64be0658a33c1bf66">http://jamie.shotton.org/work/code.html</a></li> <li><a href="https://github.com/amueller/textonboost" rel="nofollow" data-token="a05cb0b99576103ee161cd11cec88027">https://github.com/amueller/textonboost</a></li> </ul></li>
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
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