[ { "mIoU": 58.9, "code_links": [ { "title": "dmlc/gluon-cv", "url": "https://github.com/dmlc/gluon-cv" }, { "title": "zhanghang1989/ResNeSt", "url": "https://github.com/zhanghang1989/ResNeSt" }, { "title": "zhanghang1989/PyTorch-Encoding", "url": "https://github.com/zhanghang1989/PyTorch-Encoding" }, { "title": "zhanghang1989/detectron2-ResNeSt", "url": "https://github.com/zhanghang1989/detectron2-ResNeSt" }, { "title": "YeongHyeon/ResNeSt-TF2", "url": "https://github.com/YeongHyeon/ResNeSt-TF2" }, { "title": "shellhue/detectron2-ResNeSt", "url": "https://github.com/shellhue/detectron2-ResNeSt" }, { "title": "sailfish009/detectron2-ResNeSt", "url": "https://github.com/sailfish009/detectron2-ResNeSt" }, { "title": "ferna11i/detectron2_ResNeST", "url": "https://github.com/ferna11i/detectron2_ResNeST" } ], "date": "2020-04-19", "date2": 20200419, "model": "ResNeSt-269", "paper": { "title": "ResNeSt: Split-Attention Networks", "url": "https://cknow.io/lib/1d079584bf28fb94" }, "paper_data_uoa": "1d079584bf28fb94" }, { "mIoU": 58.4, "code_links": [ { "title": "dmlc/gluon-cv", "url": "https://github.com/dmlc/gluon-cv" }, { "title": "zhanghang1989/ResNeSt", "url": "https://github.com/zhanghang1989/ResNeSt" }, { "title": "zhanghang1989/PyTorch-Encoding", "url": "https://github.com/zhanghang1989/PyTorch-Encoding" }, { "title": "zhanghang1989/detectron2-ResNeSt", "url": "https://github.com/zhanghang1989/detectron2-ResNeSt" }, { "title": "YeongHyeon/ResNeSt-TF2", "url": "https://github.com/YeongHyeon/ResNeSt-TF2" }, { "title": "shellhue/detectron2-ResNeSt", "url": "https://github.com/shellhue/detectron2-ResNeSt" }, { "title": "sailfish009/detectron2-ResNeSt", "url": "https://github.com/sailfish009/detectron2-ResNeSt" }, { "title": "ferna11i/detectron2_ResNeST", "url": "https://github.com/ferna11i/detectron2_ResNeST" } ], "date": "2020-04-19", "date2": 20200419, "model": "ResNeSt-200", "paper": { "title": "ResNeSt: Split-Attention Networks", "url": "https://cknow.io/lib/1d079584bf28fb94" }, "paper_data_uoa": "1d079584bf28fb94" }, { "mIoU": 56.5, "code_links": [ { "title": "dmlc/gluon-cv", "url": "https://github.com/dmlc/gluon-cv" }, { "title": "zhanghang1989/ResNeSt", "url": "https://github.com/zhanghang1989/ResNeSt" }, { "title": "zhanghang1989/PyTorch-Encoding", "url": "https://github.com/zhanghang1989/PyTorch-Encoding" }, { "title": "zhanghang1989/detectron2-ResNeSt", "url": "https://github.com/zhanghang1989/detectron2-ResNeSt" }, { "title": "YeongHyeon/ResNeSt-TF2", "url": "https://github.com/YeongHyeon/ResNeSt-TF2" }, { "title": "shellhue/detectron2-ResNeSt", "url": "https://github.com/shellhue/detectron2-ResNeSt" }, { "title": "sailfish009/detectron2-ResNeSt", "url": "https://github.com/sailfish009/detectron2-ResNeSt" }, { "title": "ferna11i/detectron2_ResNeST", "url": "https://github.com/ferna11i/detectron2_ResNeST" } ], "date": "2020-04-19", "date2": 20200419, "model": "ResNeSt-101", "paper": { "title": "ResNeSt: Split-Attention Networks", "url": "https://cknow.io/lib/1d079584bf28fb94" }, "paper_data_uoa": "1d079584bf28fb94" }, { "mIoU": 56.2, "code_links": [ { "title": "HRNet/HRNet-Semantic-Segmentation", "url": "https://github.com/HRNet/HRNet-Semantic-Segmentation" }, { "title": "openseg-group/OCNet.pytorch", "url": "https://github.com/openseg-group/OCNet.pytorch" }, { "title": "PkuRainBow/OCNet", "url": "https://github.com/PkuRainBow/OCNet" }, { "title": "PkuRainBow/OCNet.pytorch", "url": "https://github.com/PkuRainBow/OCNet.pytorch" }, { "title": "openseg-group/openseg.pytorch", "url": "https://github.com/openseg-group/openseg.pytorch" }, { "title": "rosinality/ocr-pytorch", "url": "https://github.com/rosinality/ocr-pytorch" } ], "date": "2019-09-24", "date2": 20190924, "model": "OCR (HRNetV2-W48)", "paper": { "title": "Object-Contextual Representations for Semantic Segmentation", "url": "https://cknow.io/lib/2425114c988834de" }, "paper_data_uoa": "2425114c988834de" }, { "mIoU": 55.4, "code_links": [ { "title": "junfu1115/DRAN", "url": "https://github.com/junfu1115/DRAN" } ], "date": "2020-08-05", "date2": 20200805, "model": "DRAN(ResNet-101)", "paper": { "title": "Scene Segmentation with Dual Relation-aware Attention Network", "url": "https://cknow.io/lib/853b6588fd4e8983" }, "paper_data_uoa": "853b6588fd4e8983" }, { "mIoU": 54.8, "code_links": [ { "title": "HRNet/HRNet-Semantic-Segmentation", "url": "https://github.com/HRNet/HRNet-Semantic-Segmentation" }, { "title": "openseg-group/OCNet.pytorch", "url": "https://github.com/openseg-group/OCNet.pytorch" }, { "title": "PkuRainBow/OCNet", "url": "https://github.com/PkuRainBow/OCNet" }, { "title": "PkuRainBow/OCNet.pytorch", "url": "https://github.com/PkuRainBow/OCNet.pytorch" }, { "title": "openseg-group/openseg.pytorch", "url": "https://github.com/openseg-group/openseg.pytorch" }, { "title": "rosinality/ocr-pytorch", "url": "https://github.com/rosinality/ocr-pytorch" } ], "date": "2019-09-24", "date2": 20190924, "model": "OCR (ResNet-101)", "paper": { "title": "Object-Contextual Representations for Semantic Segmentation", "url": "https://cknow.io/lib/2425114c988834de" }, "paper_data_uoa": "2425114c988834de" }, { "mIoU": 54, "code_links": [ { "title": "CSAILVision/semantic-segmentation-pytorch", "url": "https://github.com/CSAILVision/semantic-segmentation-pytorch" }, { "title": "leoxiaobin/deep-high-resolution-net.pytorch", "url": "https://github.com/leoxiaobin/deep-high-resolution-net.pytorch" }, { "title": "HRNet/HRNet-Semantic-Segmentation", "url": "https://github.com/HRNet/HRNet-Semantic-Segmentation" }, { "title": "HRNet/HRNet-Image-Classification", "url": "https://github.com/HRNet/HRNet-Image-Classification" }, { "title": "HRNet/HRNet-Facial-Landmark-Detection", "url": "https://github.com/HRNet/HRNet-Facial-Landmark-Detection" }, { "title": "HRNet/HRNet-Object-Detection", "url": "https://github.com/HRNet/HRNet-Object-Detection" }, { "title": "HRNet/HRNet-MaskRCNN-Benchmark", "url": "https://github.com/HRNet/HRNet-MaskRCNN-Benchmark" }, { "title": "yuanyuanli85/tf-hrnet", "url": "https://github.com/yuanyuanli85/tf-hrnet" }, { "title": "shijianjian/HRNet_Keras", "url": "https://github.com/shijianjian/HRNet_Keras" } ], "date": "2019-08-20", "date2": 20190820, "model": "HRNetV2 (HRNetV2-W48)", "paper": { "title": "Deep High-Resolution Representation Learning for Visual Recognition", "url": "https://cknow.io/lib/a907f44d2b3b200a" }, "paper_data_uoa": "a907f44d2b3b200a" }, { "mIoU": 54, "code_links": [ { "title": "leoxiaobin/deep-high-resolution-net.pytorch", "url": "https://github.com/leoxiaobin/deep-high-resolution-net.pytorch" }, { "title": "HRNet/HRNet-Semantic-Segmentation", "url": "https://github.com/HRNet/HRNet-Semantic-Segmentation" }, { "title": "HRNet/HRNet-Image-Classification", "url": "https://github.com/HRNet/HRNet-Image-Classification" }, { "title": "HRNet/HRNet-Facial-Landmark-Detection", "url": "https://github.com/HRNet/HRNet-Facial-Landmark-Detection" }, { "title": "HRNet/HRNet-Object-Detection", "url": "https://github.com/HRNet/HRNet-Object-Detection" }, { "title": "HRNet/HRNet-MaskRCNN-Benchmark", "url": "https://github.com/HRNet/HRNet-MaskRCNN-Benchmark" }, { "title": "shuuchen/HRNet", "url": "https://github.com/shuuchen/HRNet" } ], "date": "2019-08-20", "date2": 20190820, "model": "CFNet (ResNet-101)", "paper": { "title": "Deep High-Resolution Representation Learning for Visual Recognition", "url": "https://cknow.io/lib/a907f44d2b3b200a" }, "paper_data_uoa": "a907f44d2b3b200a" }, { "mIoU": 53.7, "code_links": [ { "title": "lxtGH/GALD-Net", "url": "https://github.com/lxtGH/GALD-Net" } ], "date": "2019-09-13", "date2": 20190913, "model": "DGCNet (MS, ResNet-101)", "paper": { "title": "Dual Graph Convolutional Network for Semantic Segmentation", "url": "https://cknow.io/lib/2cc05696f9eb49af" }, "paper_data_uoa": "2cc05696f9eb49af" }, { "mIoU": 53.1, "code_links": [ { "title": "wuhuikai/FastFCN", "url": "https://github.com/wuhuikai/FastFCN" }, { "title": "srihari-humbarwadi/FastFCN_TF2.0", "url": "https://github.com/srihari-humbarwadi/FastFCN_TF2.0" }, { "title": "2anchao/VovJpu", "url": "https://github.com/2anchao/VovJpu" }, { "title": "yougoforward/GSNet", "url": "https://github.com/yougoforward/GSNet" }, { "title": "DongjuSin/computer-vision-proj", "url": "https://github.com/DongjuSin/computer-vision-proj" }, { "title": "yougoforward/can", "url": "https://github.com/yougoforward/can" }, { "title": "yougoforward/Fast_psaa", "url": "https://github.com/yougoforward/Fast_psaa" }, { "title": "yougoforward/localUp", "url": "https://github.com/yougoforward/localUp" } ], "date": "2019-03-28", "date2": 20190328, "model": "Joint Pyramid Upsampling + EncNet", "paper": { "title": "FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation", "url": "https://cknow.io/lib/0a914f63be8b6dcd" }, "paper_data_uoa": "0a914f63be8b6dcd" }, { "mIoU": 51.7, "code_links": [ { "title": "zhanghang1989/PyTorch-Encoding", "url": "https://github.com/zhanghang1989/PyTorch-Encoding" }, { "title": "zhusiling/EncNet", "url": "https://github.com/zhusiling/EncNet" }, { "title": "RyanHTR/PyTorch-Encoding", "url": "https://github.com/RyanHTR/PyTorch-Encoding" }, { "title": "kmaninis/pytorch-encoding", "url": "https://github.com/kmaninis/pytorch-encoding" }, { "title": "CWanli/myencoding", "url": "https://github.com/CWanli/myencoding" }, { "title": "Praveen94/pytorch-encoding", "url": "https://github.com/Praveen94/pytorch-encoding" } ], "date": "2018-03-23", "date2": 20180323, "model": "EncNet (ResNet-101)", "paper": { "title": "Context Encoding for Semantic Segmentation", "url": "https://cknow.io/lib/ee6cc4c538dd0cad" }, "paper_data_uoa": "ee6cc4c538dd0cad" }, { "mIoU": 47.8, "code_links": [ { "title": "tensorflow/models", "url": "https://github.com/tensorflow/models/tree/master/research/deeplab" }, { "title": "tensorflow/models", "url": "https://github.com/tensorflow/models" }, { "title": "CSAILVision/semantic-segmentation-pytorch", "url": "https://github.com/CSAILVision/semantic-segmentation-pytorch" }, { "title": "qubvel/segmentation_models", "url": "https://github.com/qubvel/segmentation_models" }, { "title": "divamgupta/image-segmentation-keras", "url": "https://github.com/divamgupta/image-segmentation-keras" }, { "title": "osmr/imgclsmob", "url": "https://github.com/osmr/imgclsmob" }, { "title": "hszhao/PSPNet", "url": "https://github.com/hszhao/PSPNet" }, { "title": "warmspringwinds/pytorch-segmentation-detection", "url": "https://github.com/warmspringwinds/pytorch-segmentation-detection" }, { "title": "y-ouali/pytorch_segmentation", "url": "https://github.com/y-ouali/pytorch_segmentation" }, { "title": "irfanICMLL/structure_knowledge_distillation", "url": "https://github.com/irfanICMLL/structure_knowledge_distillation" }, { "title": "Media-Smart/vedaseg", "url": "https://github.com/Media-Smart/vedaseg" }, { "title": "PRBonn/bonnet", "url": "https://github.com/PRBonn/bonnet" }, { "title": "oandrienko/fast-semantic-segmentation", "url": "https://github.com/oandrienko/fast-semantic-segmentation" }, { "title": "manideep2510/eye-in-the-sky", "url": "https://github.com/manideep2510/eye-in-the-sky" }, { "title": "switchablenorms/SwitchNorm_Segmentation", "url": "https://github.com/switchablenorms/SwitchNorm_Segmentation" }, { "title": "kazuto1011/pspnet-pytorch", "url": "https://github.com/kazuto1011/pspnet-pytorch" }, { "title": "UBC-CIC/COVID19-L3-Net", "url": "https://github.com/UBC-CIC/COVID19-L3-Net" }, { "title": "Britefury/cutmix-semisup-seg", "url": "https://github.com/Britefury/cutmix-semisup-seg" }, { "title": "BOBrown/deeparsing-master", "url": "https://github.com/BOBrown/deeparsing-master" }, { "title": "jqueguiner/camembert-as-a-service", "url": "https://github.com/jqueguiner/camembert-as-a-service" }, { "title": "jqueguiner/image-segmentation", "url": "https://github.com/jqueguiner/image-segmentation" }, { "title": "kukby/Mish-semantic-segmentation-pytorch", "url": "https://github.com/kukby/Mish-semantic-segmentation-pytorch" }, { "title": "leemathew1998/RG", "url": "https://github.com/leemathew1998/RG" }, { "title": "udacity/MLND-CN-Capstone-TGSImage", "url": "https://github.com/udacity/MLND-CN-Capstone-TGSImage" }, { "title": "RituYadav92/Image-segmentation", "url": "https://github.com/RituYadav92/Image-segmentation" }, { "title": "Lxrd-AJ/Advanced_ML", "url": "https://github.com/Lxrd-AJ/Advanced_ML" }, { "title": "leemathew1998/GradientWeight", "url": "https://github.com/leemathew1998/GradientWeight" }, { "title": "RRoundTable/U_net", "url": "https://github.com/RRoundTable/U_net" }, { "title": "monsieurmona/LinkCollectionAutonomousDriving", "url": "https://github.com/monsieurmona/LinkCollectionAutonomousDriving" } ], "date": "2016-12-04", "date2": 20161204, "model": "PSPNet (ResNet-101)", "paper": { "title": "Pyramid Scene Parsing Network", "url": "https://cknow.io/lib/59c987cd01bc78f7" }, "paper_data_uoa": "59c987cd01bc78f7" }, { "mIoU": 45.7, "code_links": [ { "title": "tensorflow/models", "url": "https://github.com/tensorflow/models/tree/master/research/deeplab" }, { "title": "tensorflow/models", "url": "https://github.com/tensorflow/models" }, { "title": "kazuto1011/deeplab-pytorch", "url": "https://github.com/kazuto1011/deeplab-pytorch" }, { "title": "warmspringwinds/pytorch-segmentation-detection", "url": "https://github.com/warmspringwinds/pytorch-segmentation-detection" }, { "title": "isht7/pytorch-deeplab-resnet", "url": "https://github.com/isht7/pytorch-deeplab-resnet" }, { "title": "DeepMotionAIResearch/DenseASPP", "url": "https://github.com/DeepMotionAIResearch/DenseASPP" }, { "title": "yaq007/Autofocus-Layer", "url": "https://github.com/yaq007/Autofocus-Layer" }, { "title": "switchablenorms/SwitchNorm_Segmentation", "url": "https://github.com/switchablenorms/SwitchNorm_Segmentation" }, { "title": "leimao/DeepLab_v3", "url": "https://github.com/leimao/DeepLab_v3" }, { "title": "ShichengChen/WaveUNet", "url": "https://github.com/ShichengChen/WaveUNet" }, { "title": "wangleihitcs/DeepLab-V1-PyTorch", "url": "https://github.com/wangleihitcs/DeepLab-V1-PyTorch" }, { "title": "Qengineering/TensorFlow-Lite-RPi-64-bit-Segmentation", "url": "https://github.com/Qengineering/TensorFlow-Lite-RPi-64-bit-Segmentation" }, { "title": "Qengineering/TensorFlow_Lite_Segmentation_RPi_64-bit", "url": "https://github.com/Qengineering/TensorFlow_Lite_Segmentation_RPi_64-bit" }, { "title": "liarba/caffe_dev", "url": "https://github.com/liarba/caffe_dev" }, { "title": "kdethoor/panoptictorch", "url": "https://github.com/kdethoor/panoptictorch" }, { "title": "OIdiotLin/DeepLab-pytorch", "url": "https://github.com/OIdiotLin/DeepLab-pytorch" }, { "title": "RituYadav92/Image-segmentation", "url": "https://github.com/RituYadav92/Image-segmentation" }, { "title": "cgsaxner/UB_Segmentation", "url": "https://github.com/cgsaxner/UB_Segmentation" }, { "title": "cdmh/deeplab-public-ver2", "url": "https://github.com/cdmh/deeplab-public-ver2" }, { "title": "keb123keb/deeplabv2", "url": "https://github.com/keb123keb/deeplabv2" }, { "title": "Qengineering/TensorFlow-Lite-RPi-32-bit-Segmentation", "url": "https://github.com/Qengineering/TensorFlow-Lite-RPi-32-bit-Segmentation" }, { "title": "violin0847/crowdcounting", "url": "https://github.com/violin0847/crowdcounting" }, { "title": "Lxrd-AJ/Advanced_ML", "url": "https://github.com/Lxrd-AJ/Advanced_ML" }, { "title": "purushothamgowthu/deep-photo-styletransfer", "url": "https://github.com/purushothamgowthu/deep-photo-styletransfer" }, { "title": "z01nl1o02/deeplab-v2", "url": "https://github.com/z01nl1o02/deeplab-v2" }, { "title": "divisionai/deep-photo-styletransfer", "url": "https://github.com/divisionai/deep-photo-styletransfer" }, { "title": "zej-luffy/deeplab-public-ver2", "url": "https://github.com/zej-luffy/deeplab-public-ver2" }, { "title": "open-cv/deeplab-v2", "url": "https://github.com/open-cv/deeplab-v2" } ], "date": "2016-06-02", "date2": 20160602, "model": "DeepLabV2", "paper": { "title": "DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs", "url": "https://cknow.io/lib/441ed44fe9598407" }, "paper_data_uoa": "441ed44fe9598407" }, { "mIoU": 40.4, "code_links": [ { "title": "tensorflow/models", "url": "https://github.com/tensorflow/models/tree/master/research/deeplab" }, { "title": "tensorflow/models", "url": "https://github.com/tensorflow/models" }, { "title": "xiamenwcy/extended-caffe", "url": "https://github.com/xiamenwcy/extended-caffe" } ], "date": "2015-06-15", "date2": 20150615, "model": "ParseNet ", "paper": { "title": "ParseNet: Looking Wider to See Better", "url": "https://cknow.io/lib/1abf3fc44c90be7d" }, "paper_data_uoa": "1abf3fc44c90be7d" } ]