{"task":"Semantic Segmentation","dataset":"CamVid","metric_names":["Mean IoU","Global Accuracy"],"rows":[{"id":35144,"task":"Semantic Segmentation","parent_task":null,"dataset":"CamVid","model_name":"SERNet-Former","metrics":{"Mean IoU":"84.62"},"paper_url":"https://arxiv.org/abs/2401.15741v7","paper_title":"SERNet-Former: Semantic Segmentation by Efficient Residual Network with Attention-Boosting Gates and Attention-Fusion Networks","paper_date":"2024-01-28","code_links":[{"title":"serdarch/sernet-former","url":"https://github.com/serdarch/sernet-former"},{"title":"serdarch/SERNet-Former","url":"https://github.com/serdarch/SERNet-Former/blob/main/README.md"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":35145,"task":"Semantic Segmentation","parent_task":null,"dataset":"CamVid","model_name":"SIW","metrics":{"Mean IoU":"83.7"},"paper_url":"https://arxiv.org/abs/2202.02002v2","paper_title":"Scaling up Multi-domain Semantic Segmentation with Sentence Embeddings","paper_date":"2022-02-04","code_links":[],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":35146,"task":"Semantic Segmentation","parent_task":null,"dataset":"CamVid","model_name":"DSNet-Base","metrics":{"Mean IoU":"83.32"},"paper_url":"https://arxiv.org/abs/2406.03702v1","paper_title":"DSNet: A Novel Way to Use Atrous Convolutions in Semantic Segmentation","paper_date":"2024-06-06","code_links":[{"title":"takaniwa/dsnet","url":"https://github.com/takaniwa/dsnet"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":35147,"task":"Semantic Segmentation","parent_task":null,"dataset":"CamVid","model_name":"RTFormer-Base","metrics":{"Mean IoU":"82.5"},"paper_url":"https://arxiv.org/abs/2210.07124v1","paper_title":"RTFormer: Efficient Design for Real-Time Semantic Segmentation with Transformer","paper_date":"2022-10-13","code_links":[{"title":"PaddlePaddle/PaddleSeg","url":"https://github.com/PaddlePaddle/PaddleSeg"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":35148,"task":"Semantic Segmentation","parent_task":null,"dataset":"CamVid","model_name":"PIDNet-Wider","metrics":{"Mean IoU":"82.0%"},"paper_url":"https://arxiv.org/abs/2206.02066v3","paper_title":"PIDNet: A Real-time Semantic Segmentation Network Inspired by PID Controllers","paper_date":"2022-06-04","code_links":[{"title":"XuJiacong/PIDNet","url":"https://github.com/XuJiacong/PIDNet"},{"title":"Darth-Kronos/PIDNet_TensorRT","url":"https://github.com/Darth-Kronos/PIDNet_TensorRT"},{"title":"hamidriasat/PIDNet","url":"https://github.com/hamidriasat/PIDNet"},{"title":"HengWeiBin/Oil-Polution-Dataset-with-PIDNet","url":"https://github.com/HengWeiBin/Oil-Polution-Dataset-with-PIDNet"},{"title":"Mahmood-Hussain/PIDNetTensorflow","url":"https://github.com/Mahmood-Hussain/PIDNetTensorflow"},{"title":"enot-autodl/lpcv-2023","url":"https://github.com/enot-autodl/lpcv-2023"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":35149,"task":"Semantic Segmentation","parent_task":null,"dataset":"CamVid","model_name":"DeepLabV3Plus + SDCNetAug","metrics":{"Mean IoU":"81.7"},"paper_url":"https://arxiv.org/abs/1812.01593v3","paper_title":"Improving Semantic Segmentation via Video Propagation and Label Relaxation","paper_date":"2018-12-04","code_links":[{"title":"NVIDIA/semantic-segmentation","url":"https://github.com/NVIDIA/semantic-segmentation"},{"title":"YeLyuUT/SSeg","url":"https://github.com/YeLyuUT/SSeg"},{"title":"ganlumomo/mtl-segmentation","url":"https://github.com/ganlumomo/mtl-segmentation"},{"title":"ganlumomo/semantic-segmentation","url":"https://github.com/ganlumomo/semantic-segmentation"},{"title":"tobiasriedlinger/uncertainty-gradients-seg","url":"https://github.com/tobiasriedlinger/uncertainty-gradients-seg"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":1,"source":"archive","tags":[]},{"id":35150,"task":"Semantic Segmentation","parent_task":null,"dataset":"CamVid","model_name":"DDRNet23","metrics":{"Mean IoU":"80.6%"},"paper_url":"https://arxiv.org/abs/2101.06085v2","paper_title":"Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes","paper_date":"2021-01-15","code_links":[{"title":"Deci-AI/super-gradients","url":"https://github.com/Deci-AI/super-gradients"},{"title":"sithu31296/semantic-segmentation","url":"https://github.com/sithu31296/semantic-segmentation"},{"title":"ydhongHIT/DDRNet","url":"https://github.com/ydhongHIT/DDRNet"},{"title":"zh320/realtime-semantic-segmentation-pytorch","url":"https://github.com/zh320/realtime-semantic-segmentation-pytorch"},{"title":"hamidriasat/DDRNets","url":"https://github.com/hamidriasat/DDRNets"},{"title":"MindSpore-paper-code-3/code2","url":"https://github.com/MindSpore-paper-code-3/code2/tree/main/DDRNet"},{"title":"2023-MindSpore-4/Code2","url":"https://github.com/2023-MindSpore-4/Code2/tree/main/DecoMR"},{"title":"MindSpore-paper-code-3/code8","url":"https://github.com/MindSpore-paper-code-3/code8/tree/main/DDRNet"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":35151,"task":"Semantic Segmentation","parent_task":null,"dataset":"CamVid","model_name":"ETC-Mobile","metrics":{"Mean IoU":"76.3"},"paper_url":"https://arxiv.org/abs/2002.11433v2","paper_title":"Efficient Semantic Video Segmentation with Per-frame Inference","paper_date":"2020-02-26","code_links":[{"title":"irfanICMLL/ETC-Real-time-Per-frame-Semantic-video-segmentation","url":"https://github.com/irfanICMLL/ETC-Real-time-Per-frame-Semantic-video-segmentation"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":35152,"task":"Semantic Segmentation","parent_task":null,"dataset":"CamVid","model_name":"VideoGCRF","metrics":{"Mean IoU":"75.2"},"paper_url":"http://arxiv.org/abs/1807.03148v1","paper_title":"Deep Spatio-Temporal Random Fields for Efficient Video Segmentation","paper_date":"2018-07-03","code_links":[],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":35153,"task":"Semantic Segmentation","parent_task":null,"dataset":"CamVid","model_name":"DenseDecoder","metrics":{"Mean IoU":"70.9"},"paper_url":"http://openaccess.thecvf.com/content_cvpr_2018/html/Bilinski_Dense_Decoder_Shortcut_CVPR_2018_paper.html","paper_title":"Dense Decoder Shortcut Connections for Single-Pass Semantic Segmentation","paper_date":"2018-06-01","code_links":[],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":35154,"task":"Semantic Segmentation","parent_task":null,"dataset":"CamVid","model_name":"BiSeNet","metrics":{"Mean IoU":"68.7%"},"paper_url":"http://arxiv.org/abs/1808.00897v1","paper_title":"BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation","paper_date":"2018-08-02","code_links":[{"title":"PaddlePaddle/PaddleSeg","url":"https://github.com/PaddlePaddle/PaddleSeg"},{"title":"osmr/imgclsmob","url":"https://github.com/osmr/imgclsmob"},{"title":"CoinCheung/BiSeNet","url":"https://github.com/CoinCheung/BiSeNet"},{"title":"kritiksoman/GIMP-ML","url":"https://github.com/kritiksoman/GIMP-ML"},{"title":"ycszen/TorchSeg","url":"https://github.com/ycszen/TorchSeg"},{"title":"ooooverflow/BiSeNet","url":"https://github.com/ooooverflow/BiSeNet"},{"title":"zh320/realtime-semantic-segmentation-pytorch","url":"https://github.com/zh320/realtime-semantic-segmentation-pytorch"},{"title":"AmrElsersy/PointPainting","url":"https://github.com/AmrElsersy/PointPainting"},{"title":"yakhyo/face-parsing","url":"https://github.com/yakhyo/face-parsing"},{"title":"kirilcvetkov92/Semantic-Segmentation","url":"https://github.com/kirilcvetkov92/Semantic-Segmentation"},{"title":"Blaizzy/BiSeNet-Implementation","url":"https://github.com/Blaizzy/BiSeNet-Implementation"},{"title":"pdoublerainbow/bisenet-tensorflow","url":"https://github.com/pdoublerainbow/bisenet-tensorflow"},{"title":"renhaa/semantic-diffusion","url":"https://github.com/renhaa/semantic-diffusion"},{"title":"GuangyanZhang/SCNN-Deeplabv3-bisenet-icnet","url":"https://github.com/GuangyanZhang/SCNN-Deeplabv3-bisenet-icnet"},{"title":"Shuai-Xie/BiSeNet-CCP","url":"https://github.com/Shuai-Xie/BiSeNet-CCP"},{"title":"SharifElfouly/easy-model-zoo","url":"https://github.com/SharifElfouly/easy-model-zoo"},{"title":"justld/BisNetV1_paddle","url":"https://github.com/justld/BisNetV1_paddle"},{"title":"hm7455/Anti-collision_Semantic-segmentation_","url":"https://github.com/hm7455/Anti-collision_Semantic-segmentation_"},{"title":"Asthestarsfalll/BiSeNet-MegEngine","url":"https://github.com/Asthestarsfalll/BiSeNet-MegEngine"},{"title":"CodePlay2016/BiSENet-TF","url":"https://github.com/CodePlay2016/BiSENet-TF"},{"title":"akinoriosamura/TorchSeg-mirror","url":"https://github.com/akinoriosamura/TorchSeg-mirror"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":35155,"task":"Semantic Segmentation","parent_task":null,"dataset":"CamVid","model_name":"FC-DenseNet103","metrics":{"Global Accuracy":"91.5%","Mean IoU":"66.9%"},"paper_url":"http://arxiv.org/abs/1611.09326v3","paper_title":"The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation","paper_date":"2016-11-28","code_links":[{"title":"SimJeg/FC-DenseNet","url":"https://github.com/SimJeg/FC-DenseNet"},{"title":"bfortuner/pytorch_tiramisu","url":"https://github.com/bfortuner/pytorch_tiramisu"},{"title":"mrkolarik/3d-brain-segmentation","url":"https://github.com/mrkolarik/3d-brain-segmentation"},{"title":"0bserver07/One-Hundred-Layers-Tiramisu","url":"https://github.com/0bserver07/One-Hundred-Layers-Tiramisu"},{"title":"Kaido0/Brain-Tissue-Segment-Keras","url":"https://github.com/Kaido0/Brain-Tissue-Segment-Keras"},{"title":"petko-nikolov/pysemseg","url":"https://github.com/petko-nikolov/pysemseg"},{"title":"smdYe/FC-DenseNet-Keras","url":"https://github.com/smdYe/FC-DenseNet-Keras"},{"title":"asprenger/keras_fc_densenet","url":"https://github.com/asprenger/keras_fc_densenet"},{"title":"demul/image_segmentation_project","url":"https://github.com/demul/image_segmentation_project"},{"title":"ankit-vaghela30/Cilia-Segmentation","url":"https://github.com/ankit-vaghela30/Cilia-Segmentation"},{"title":"pattyhendrix/CamVid-95-accuracy","url":"https://github.com/pattyhendrix/CamVid-95-accuracy"},{"title":"SANKHA1/Vehicle-Detection","url":"https://github.com/SANKHA1/Vehicle-Detection"},{"title":"kannyjyk/Nested-UNet","url":"https://github.com/kannyjyk/Nested-UNet"},{"title":"kskim-phd/mfcn","url":"https://github.com/kskim-phd/mfcn"},{"title":"koryako/AI-application","url":"https://github.com/koryako/AI-application"},{"title":"noornk/U-Net","url":"https://github.com/noornk/U-Net"},{"title":"Septembit/Image-segmentation","url":"https://github.com/Septembit/Image-segmentation"},{"title":"IllIIIllll/where-is-wally","url":"https://github.com/IllIIIllll/where-is-wally"},{"title":"boris127/vehicle-detection","url":"https://github.com/boris127/vehicle-detection"},{"title":"datoboat/Vehicle-Detection","url":"https://github.com/datoboat/Vehicle-Detection"},{"title":"Osdel/ssnets","url":"https://github.com/Osdel/ssnets"},{"title":"Vamshi399/CarND-Vehicle-Detection","url":"https://github.com/Vamshi399/CarND-Vehicle-Detection"},{"title":"vivaan-park/where-is-wally","url":"https://github.com/vivaan-park/where-is-wally"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":35156,"task":"Semantic Segmentation","parent_task":null,"dataset":"CamVid","model_name":"EDANet","metrics":{"Global Accuracy":"90.8","Mean IoU":"66.4"},"paper_url":"https://arxiv.org/abs/1809.06323v3","paper_title":"Efficient Dense Modules of Asymmetric Convolution for Real-Time Semantic Segmentation","paper_date":"2018-09-17","code_links":[{"title":"osmr/imgclsmob","url":"https://github.com/osmr/imgclsmob"},{"title":"zh320/realtime-semantic-segmentation-pytorch","url":"https://github.com/zh320/realtime-semantic-segmentation-pytorch"},{"title":"shaoyuanlo/EDANet","url":"https://github.com/shaoyuanlo/EDANet"},{"title":"wpf535236337/pytorch_EDANet","url":"https://github.com/wpf535236337/pytorch_EDANet"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":35157,"task":"Semantic Segmentation","parent_task":null,"dataset":"CamVid","model_name":"Dilated Convolutions","metrics":{"Mean IoU":"65.3%"},"paper_url":"http://arxiv.org/abs/1511.07122v3","paper_title":"Multi-Scale Context Aggregation by Dilated Convolutions","paper_date":"2015-11-23","code_links":[{"title":"fyu/dilation","url":"https://github.com/fyu/dilation"},{"title":"vlievin/Unet","url":"https://github.com/vlievin/Unet"},{"title":"Wanger-SJTU/FCN-in-the-wild","url":"https://github.com/Wanger-SJTU/FCN-in-the-wild"},{"title":"keillernogueira/FDSI","url":"https://github.com/keillernogueira/FDSI"},{"title":"Entodi/meshnet-pytorch","url":"https://github.com/Entodi/meshnet-pytorch"},{"title":"harshmaru7/DilatedConv","url":"https://github.com/harshmaru7/DilatedConv"},{"title":"Rakeshpavan333/oct_dil","url":"https://github.com/Rakeshpavan333/oct_dil"},{"title":"srihari-humbarwadi/Multi-Scale-Context-Aggregation-by-Dilated-Convolutions","url":"https://github.com/srihari-humbarwadi/Multi-Scale-Context-Aggregation-by-Dilated-Convolutions"},{"title":"ajaystar8/PDRUNet-PyTorch","url":"https://github.com/ajaystar8/PDRUNet-PyTorch"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":35158,"task":"Semantic Segmentation","parent_task":null,"dataset":"CamVid","model_name":"DFANet A","metrics":{"Mean IoU":"64.7%"},"paper_url":"http://arxiv.org/abs/1904.02216v1","paper_title":"DFANet: Deep Feature Aggregation for Real-Time Semantic Segmentation","paper_date":"2019-04-03","code_links":[{"title":"huaifeng1993/DFANet","url":"https://github.com/huaifeng1993/DFANet"},{"title":"j-a-lin/DFANet_PyTorch","url":"https://github.com/j-a-lin/DFANet_PyTorch"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":35159,"task":"Semantic Segmentation","parent_task":null,"dataset":"CamVid","model_name":"Template-Based NAS-arch0 (480x360 inputs)","metrics":{"Mean IoU":"63.9%"},"paper_url":"https://arxiv.org/abs/1904.02365v2","paper_title":"Template-Based Automatic Search of Compact Semantic Segmentation Architectures","paper_date":"2019-04-04","code_links":[{"title":"drsleep/nas-segm-pytorch","url":"https://github.com/drsleep/nas-segm-pytorch"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":35160,"task":"Semantic Segmentation","parent_task":null,"dataset":"CamVid","model_name":"LMDNet","metrics":{"Mean IoU":"63.5"},"paper_url":"http://arxiv.org/abs/1809.03994v1","paper_title":"Efficient Road Lane Marking Detection with Deep Learning","paper_date":"2018-09-11","code_links":[],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":35161,"task":"Semantic Segmentation","parent_task":null,"dataset":"CamVid","model_name":"Template-Based NAS-arch1 (480x360 inputs)","metrics":{"Mean IoU":"63.2%"},"paper_url":"https://arxiv.org/abs/1904.02365v2","paper_title":"Template-Based Automatic Search of Compact Semantic Segmentation Architectures","paper_date":"2019-04-04","code_links":[{"title":"drsleep/nas-segm-pytorch","url":"https://github.com/drsleep/nas-segm-pytorch"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":35162,"task":"Semantic Segmentation","parent_task":null,"dataset":"CamVid","model_name":"DeepLab-MSc-CRF-LargeFOV","metrics":{"Mean IoU":"61.6%"},"paper_url":"http://arxiv.org/abs/1412.7062v4","paper_title":"Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs","paper_date":"2014-12-22","code_links":[{"title":"tensorflow/models","url":"https://github.com/tensorflow/models"},{"title":"tensorflow/models","url":"https://github.com/tensorflow/models/tree/master/research/deeplab"},{"title":"open-mmlab/mmsegmentation","url":"https://github.com/open-mmlab/mmsegmentation"},{"title":"DeepMotionAIResearch/DenseASPP","url":"https://github.com/DeepMotionAIResearch/DenseASPP"},{"title":"nightrome/cocostuff10k","url":"https://github.com/nightrome/cocostuff10k"},{"title":"arahusky/Tensorflow-Segmentation","url":"https://github.com/arahusky/Tensorflow-Segmentation"},{"title":"TheLegendAli/DeepLab-Context","url":"https://github.com/TheLegendAli/DeepLab-Context"},{"title":"wangleihitcs/DeepLab-V1-PyTorch","url":"https://github.com/wangleihitcs/DeepLab-V1-PyTorch"},{"title":"pathak22/ccnn","url":"https://github.com/pathak22/ccnn"},{"title":"johnnylu305/Simple-does-it-weakly-supervised-instance-and-semantic-segmentation","url":"https://github.com/johnnylu305/Simple-does-it-weakly-supervised-instance-and-semantic-segmentation"},{"title":"BardOfCodes/pytorch_deeplab_large_fov","url":"https://github.com/BardOfCodes/pytorch_deeplab_large_fov"},{"title":"Jasonlee1995/DeepLab_v1","url":"https://github.com/Jasonlee1995/DeepLab_v1"},{"title":"code-implementation1/Code9","url":"https://github.com/code-implementation1/Code9/tree/main/DeepLabV3P"},{"title":"2024-MindSpore-1/Code4","url":"https://github.com/2024-MindSpore-1/Code4/tree/main/DeepLabV3P"},{"title":"NASA-NeMO-Net/NeMO-Net","url":"https://github.com/NASA-NeMO-Net/NeMO-Net"},{"title":"open-cv/deeplab-v1","url":"https://github.com/open-cv/deeplab-v1"},{"title":"Daeijavad/Deeplab-CRF","url":"https://github.com/Daeijavad/Deeplab-CRF"},{"title":"deeplab/deeplab-public","url":"https://bitbucket.org/deeplab/deeplab-public"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":35163,"task":"Semantic Segmentation","parent_task":null,"dataset":"CamVid","model_name":"ReSeg","metrics":{"Global Accuracy":"88.7%","Mean IoU":"58.8%"},"paper_url":"http://arxiv.org/abs/1511.07053v3","paper_title":"ReSeg: A Recurrent Neural Network-based Model for Semantic Segmentation","paper_date":"2015-11-22","code_links":[{"title":"fvisin/reseg","url":"https://github.com/fvisin/reseg"},{"title":"mindspore-ai/contrib","url":"https://github.com/mindspore-ai/contrib/tree/master/application/ReSeg"},{"title":"SConsul/ReSeg","url":"https://github.com/SConsul/ReSeg"},{"title":"MindCode-4/code-8","url":"https://github.com/MindCode-4/code-8/tree/main/ReSeg"},{"title":"MindCode-4/code-13","url":"https://github.com/MindCode-4/code-13/tree/main/ReSeg"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":35164,"task":"Semantic Segmentation","parent_task":null,"dataset":"CamVid","model_name":"SegNet","metrics":{"Mean IoU":"46.4%"},"paper_url":"http://arxiv.org/abs/1511.00561v3","paper_title":"SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation","paper_date":"2015-11-02","code_links":[{"title":"PaddlePaddle/PaddleSeg","url":"https://github.com/PaddlePaddle/PaddleSeg"},{"title":"osmr/imgclsmob","url":"https://github.com/osmr/imgclsmob"},{"title":"divamgupta/image-segmentation-keras","url":"https://github.com/divamgupta/image-segmentation-keras"},{"title":"y-ouali/pytorch_segmentation","url":"https://github.com/y-ouali/pytorch_segmentation"},{"title":"alexgkendall/caffe-segnet","url":"https://github.com/alexgkendall/caffe-segnet"},{"title":"alexgkendall/SegNet-Tutorial","url":"https://github.com/alexgkendall/SegNet-Tutorial"},{"title":"vqdang/hover_net","url":"https://github.com/vqdang/hover_net"},{"title":"vqdang/xy_net","url":"https://github.com/vqdang/xy_net"},{"title":"tkuanlun350/Tensorflow-SegNet","url":"https://github.com/tkuanlun350/Tensorflow-SegNet"},{"title":"PRBonn/bonnet","url":"https://github.com/PRBonn/bonnet"},{"title":"Yijunmaverick/GenerativeFaceCompletion","url":"https://github.com/Yijunmaverick/GenerativeFaceCompletion"},{"title":"navganti/SIVO","url":"https://github.com/navganti/SIVO"},{"title":"yubaoliu/rds-slam","url":"https://github.com/yubaoliu/rds-slam"},{"title":"arahusky/Tensorflow-Segmentation","url":"https://github.com/arahusky/Tensorflow-Segmentation"},{"title":"shanglianlm0525/CvPytorch","url":"https://github.com/shanglianlm0525/CvPytorch"},{"title":"zh320/realtime-semantic-segmentation-pytorch","url":"https://github.com/zh320/realtime-semantic-segmentation-pytorch"},{"title":"preddy5/segnet","url":"https://github.com/preddy5/segnet"},{"title":"TimoSaemann/caffe-segnet-cudnn5","url":"https://github.com/TimoSaemann/caffe-segnet-cudnn5"},{"title":"hydrogo/rainnet","url":"https://github.com/hydrogo/rainnet"},{"title":"JosephPB/XNet","url":"https://github.com/JosephPB/XNet"},{"title":"0bserver07/Keras-SegNet-Basic","url":"https://github.com/0bserver07/Keras-SegNet-Basic"},{"title":"ankit-ai/GAN_breast_mammography_segmentation","url":"https://github.com/ankit-ai/GAN_breast_mammography_segmentation"},{"title":"vinceecws/SegNet_PyTorch","url":"https://github.com/vinceecws/SegNet_PyTorch"},{"title":"trypag/pytorch-unet-segnet","url":"https://github.com/trypag/pytorch-unet-segnet"},{"title":"Charmve/Semantic-Segmentation-PyTorch","url":"https://github.com/Charmve/Semantic-Segmentation-PyTorch/blob/master/models/seg_net.py"},{"title":"Lkruitwagen/remote-sensing-solar-pv","url":"https://github.com/Lkruitwagen/remote-sensing-solar-pv"},{"title":"Violet981/Breast_mass_Segmentation","url":"https://github.com/Violet981/Breast_mass_Segmentation"},{"title":"neuropoly/multiclass-segmentation","url":"https://github.com/neuropoly/multiclass-segmentation"},{"title":"kulkarnikeerti/SegNet-Semantic-Segmentation","url":"https://github.com/kulkarnikeerti/SegNet-Semantic-Segmentation"},{"title":"ArkaJU/SegNet---Chromosome","url":"https://github.com/ArkaJU/SegNet---Chromosome"},{"title":"danielenricocahall/Keras-SegNet","url":"https://github.com/danielenricocahall/Keras-SegNet"},{"title":"alejandrodebus/SegNet","url":"https://github.com/alejandrodebus/SegNet"},{"title":"jqueguiner/camembert-as-a-service","url":"https://github.com/jqueguiner/camembert-as-a-service"},{"title":"pa56/SegNetonCityscapes","url":"https://github.com/pa56/SegNetonCityscapes"},{"title":"pa56/SegNet_on_Cityscapes","url":"https://github.com/pa56/SegNet_on_Cityscapes"},{"title":"zhuotongchen/self-healing-robust-neural-networks-via-closed-loop-control","url":"https://github.com/zhuotongchen/self-healing-robust-neural-networks-via-closed-loop-control"},{"title":"jqueguiner/image-segmentation","url":"https://github.com/jqueguiner/image-segmentation"},{"title":"akhadangi/EM-net","url":"https://github.com/akhadangi/EM-net"},{"title":"yinanzhu12/SegNet-keras","url":"https://github.com/yinanzhu12/SegNet-keras"},{"title":"yinanzhu12/SegNet-keras-implementation","url":"https://github.com/yinanzhu12/SegNet-keras-implementation"},{"title":"burakalperen/Pytorch-Semantic-Segmentation","url":"https://github.com/burakalperen/Pytorch-Semantic-Segmentation"},{"title":"arsalhuda24/SS_lstm","url":"https://github.com/arsalhuda24/SS_lstm"},{"title":"XiangbingJi/Stanford-cs230-final-project","url":"https://github.com/XiangbingJi/Stanford-cs230-final-project"},{"title":"okn-yu/SegNet-A-Deep-Convolutional-Encoder-Decoder-Architecture-for-Image-Segmentation","url":"https://github.com/okn-yu/SegNet-A-Deep-Convolutional-Encoder-Decoder-Architecture-for-Image-Segmentation"},{"title":"nisharaichur/segNet_tensorflow","url":"https://github.com/nisharaichur/segNet_tensorflow"},{"title":"CellSMB/EM-net","url":"https://github.com/CellSMB/EM-net"},{"title":"nisharaichur/SegNet-Encoder-Decoder-Architecture-for-Image-Segmentation","url":"https://github.com/nisharaichur/SegNet-Encoder-Decoder-Architecture-for-Image-Segmentation"},{"title":"navganti/SegNet","url":"https://github.com/navganti/SegNet"},{"title":"yubaoliu/caffe-segnet","url":"https://github.com/yubaoliu/caffe-segnet"},{"title":"Harsharma2308/PoseRefinement","url":"https://github.com/Harsharma2308/PoseRefinement"},{"title":"ajjdan/KaI","url":"https://github.com/ajjdan/KaI"},{"title":"stuartchen1949/segnet_paddle","url":"https://github.com/stuartchen1949/segnet_paddle"},{"title":"ayushmankumar7/SegNet---Tensorflow-2","url":"https://github.com/ayushmankumar7/SegNet---Tensorflow-2"},{"title":"ajjdan/Karst-Segmentation-from-DEM","url":"https://github.com/ajjdan/Karst-Segmentation-from-DEM"},{"title":"Tez01/SegNet-Keras-Implementation","url":"https://github.com/Tez01/SegNet-Keras-Implementation"},{"title":"hosshonarvar/Image-Segmentation","url":"https://github.com/hosshonarvar/Image-Segmentation"},{"title":"gaelmoccand/RoadSegmentation_CNN","url":"https://github.com/gaelmoccand/RoadSegmentation_CNN"},{"title":"TheUser0815/segnet-pytorch","url":"https://github.com/TheUser0815/segnet-pytorch"},{"title":"s9mondal9upriti/Segnet","url":"https://github.com/s9mondal9upriti/Segnet"},{"title":"Zhanghongbin-github/SegNet-Tutorial","url":"https://github.com/Zhanghongbin-github/SegNet-Tutorial"},{"title":"NeuronDroid/GVSS-S.A.Drone","url":"https://github.com/NeuronDroid/GVSS-S.A.Drone"},{"title":"rotemgoren/segNet","url":"https://github.com/rotemgoren/segNet"},{"title":"alexandrelewin/FollowMe","url":"https://github.com/alexandrelewin/FollowMe"},{"title":"HAN-ARK/GVSS-S.A.Drone","url":"https://github.com/HAN-ARK/GVSS-S.A.Drone"},{"title":"DarkGeekMS/Semantic_Segmentation_Models_Keras","url":"https://github.com/DarkGeekMS/Semantic_Segmentation_Models_Keras"},{"title":"billlyzhaoyh/SegNetFromScratch","url":"https://github.com/billlyzhaoyh/SegNetFromScratch"},{"title":"RajkumarPreetham/Road-scene-understanding","url":"https://github.com/RajkumarPreetham/Road-scene-understanding"},{"title":"SSN15/Behavioral-Cloning--Implementaion-of-Autonomous-car-using-deep-learning","url":"https://github.com/SSN15/Behavioral-Cloning--Implementaion-of-Autonomous-car-using-deep-learning"},{"title":"ajoshi944/Segmentation-severstal-steel","url":"https://github.com/ajoshi944/Segmentation-severstal-steel"},{"title":"Paultool/segnet","url":"https://github.com/Paultool/segnet"},{"title":"TqDavid/td","url":"https://github.com/TqDavid/td"},{"title":"azy64/Deep-Learning","url":"https://github.com/azy64/Deep-Learning"},{"title":"Fangrn/caffe-segnet","url":"https://github.com/Fangrn/caffe-segnet"},{"title":"mrmtn86/python1","url":"https://github.com/mrmtn86/python1"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":136889,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"CamVid","model_name":"SERNet-Former","metrics":{"Mean IoU":"84.62"},"paper_url":"https://arxiv.org/abs/2401.15741v7","paper_title":"SERNet-Former: Semantic Segmentation by Efficient Residual Network with Attention-Boosting Gates and Attention-Fusion Networks","paper_date":"2024-01-28","code_links":[{"title":"serdarch/sernet-former","url":"https://github.com/serdarch/sernet-former"},{"title":"serdarch/SERNet-Former","url":"https://github.com/serdarch/SERNet-Former/blob/main/README.md"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":136890,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"CamVid","model_name":"SIW","metrics":{"Mean IoU":"83.7"},"paper_url":"https://arxiv.org/abs/2202.02002v2","paper_title":"Scaling up Multi-domain Semantic Segmentation with Sentence Embeddings","paper_date":"2022-02-04","code_links":[],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":136891,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"CamVid","model_name":"DSNet-Base","metrics":{"Mean IoU":"83.32"},"paper_url":"https://arxiv.org/abs/2406.03702v1","paper_title":"DSNet: A Novel Way to Use Atrous Convolutions in Semantic Segmentation","paper_date":"2024-06-06","code_links":[{"title":"takaniwa/dsnet","url":"https://github.com/takaniwa/dsnet"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":136892,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"CamVid","model_name":"RTFormer-Base","metrics":{"Mean IoU":"82.5"},"paper_url":"https://arxiv.org/abs/2210.07124v1","paper_title":"RTFormer: Efficient Design for Real-Time Semantic Segmentation with Transformer","paper_date":"2022-10-13","code_links":[{"title":"PaddlePaddle/PaddleSeg","url":"https://github.com/PaddlePaddle/PaddleSeg"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":136893,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"CamVid","model_name":"PIDNet-Wider","metrics":{"Mean IoU":"82.0%"},"paper_url":"https://arxiv.org/abs/2206.02066v3","paper_title":"PIDNet: A Real-time Semantic Segmentation Network Inspired by PID Controllers","paper_date":"2022-06-04","code_links":[{"title":"XuJiacong/PIDNet","url":"https://github.com/XuJiacong/PIDNet"},{"title":"Darth-Kronos/PIDNet_TensorRT","url":"https://github.com/Darth-Kronos/PIDNet_TensorRT"},{"title":"hamidriasat/PIDNet","url":"https://github.com/hamidriasat/PIDNet"},{"title":"HengWeiBin/Oil-Polution-Dataset-with-PIDNet","url":"https://github.com/HengWeiBin/Oil-Polution-Dataset-with-PIDNet"},{"title":"Mahmood-Hussain/PIDNetTensorflow","url":"https://github.com/Mahmood-Hussain/PIDNetTensorflow"},{"title":"enot-autodl/lpcv-2023","url":"https://github.com/enot-autodl/lpcv-2023"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":136894,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"CamVid","model_name":"DeepLabV3Plus + SDCNetAug","metrics":{"Mean IoU":"81.7"},"paper_url":"https://arxiv.org/abs/1812.01593v3","paper_title":"Improving Semantic Segmentation via Video Propagation and Label Relaxation","paper_date":"2018-12-04","code_links":[{"title":"NVIDIA/semantic-segmentation","url":"https://github.com/NVIDIA/semantic-segmentation"},{"title":"YeLyuUT/SSeg","url":"https://github.com/YeLyuUT/SSeg"},{"title":"ganlumomo/mtl-segmentation","url":"https://github.com/ganlumomo/mtl-segmentation"},{"title":"ganlumomo/semantic-segmentation","url":"https://github.com/ganlumomo/semantic-segmentation"},{"title":"tobiasriedlinger/uncertainty-gradients-seg","url":"https://github.com/tobiasriedlinger/uncertainty-gradients-seg"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":1,"source":"archive","tags":[]},{"id":136895,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"CamVid","model_name":"DDRNet23","metrics":{"Mean IoU":"80.6%"},"paper_url":"https://arxiv.org/abs/2101.06085v2","paper_title":"Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes","paper_date":"2021-01-15","code_links":[{"title":"Deci-AI/super-gradients","url":"https://github.com/Deci-AI/super-gradients"},{"title":"sithu31296/semantic-segmentation","url":"https://github.com/sithu31296/semantic-segmentation"},{"title":"ydhongHIT/DDRNet","url":"https://github.com/ydhongHIT/DDRNet"},{"title":"zh320/realtime-semantic-segmentation-pytorch","url":"https://github.com/zh320/realtime-semantic-segmentation-pytorch"},{"title":"hamidriasat/DDRNets","url":"https://github.com/hamidriasat/DDRNets"},{"title":"MindSpore-paper-code-3/code2","url":"https://github.com/MindSpore-paper-code-3/code2/tree/main/DDRNet"},{"title":"2023-MindSpore-4/Code2","url":"https://github.com/2023-MindSpore-4/Code2/tree/main/DecoMR"},{"title":"MindSpore-paper-code-3/code8","url":"https://github.com/MindSpore-paper-code-3/code8/tree/main/DDRNet"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":136896,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"CamVid","model_name":"ETC-Mobile","metrics":{"Mean IoU":"76.3"},"paper_url":"https://arxiv.org/abs/2002.11433v2","paper_title":"Efficient Semantic Video Segmentation with Per-frame Inference","paper_date":"2020-02-26","code_links":[{"title":"irfanICMLL/ETC-Real-time-Per-frame-Semantic-video-segmentation","url":"https://github.com/irfanICMLL/ETC-Real-time-Per-frame-Semantic-video-segmentation"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":136897,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"CamVid","model_name":"VideoGCRF","metrics":{"Mean IoU":"75.2"},"paper_url":"http://arxiv.org/abs/1807.03148v1","paper_title":"Deep Spatio-Temporal Random Fields for Efficient Video Segmentation","paper_date":"2018-07-03","code_links":[],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":136898,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"CamVid","model_name":"DenseDecoder","metrics":{"Mean IoU":"70.9"},"paper_url":"http://openaccess.thecvf.com/content_cvpr_2018/html/Bilinski_Dense_Decoder_Shortcut_CVPR_2018_paper.html","paper_title":"Dense Decoder Shortcut Connections for Single-Pass Semantic Segmentation","paper_date":"2018-06-01","code_links":[],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":136899,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"CamVid","model_name":"BiSeNet","metrics":{"Mean IoU":"68.7%"},"paper_url":"http://arxiv.org/abs/1808.00897v1","paper_title":"BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation","paper_date":"2018-08-02","code_links":[{"title":"PaddlePaddle/PaddleSeg","url":"https://github.com/PaddlePaddle/PaddleSeg"},{"title":"osmr/imgclsmob","url":"https://github.com/osmr/imgclsmob"},{"title":"CoinCheung/BiSeNet","url":"https://github.com/CoinCheung/BiSeNet"},{"title":"kritiksoman/GIMP-ML","url":"https://github.com/kritiksoman/GIMP-ML"},{"title":"ycszen/TorchSeg","url":"https://github.com/ycszen/TorchSeg"},{"title":"ooooverflow/BiSeNet","url":"https://github.com/ooooverflow/BiSeNet"},{"title":"zh320/realtime-semantic-segmentation-pytorch","url":"https://github.com/zh320/realtime-semantic-segmentation-pytorch"},{"title":"AmrElsersy/PointPainting","url":"https://github.com/AmrElsersy/PointPainting"},{"title":"yakhyo/face-parsing","url":"https://github.com/yakhyo/face-parsing"},{"title":"kirilcvetkov92/Semantic-Segmentation","url":"https://github.com/kirilcvetkov92/Semantic-Segmentation"},{"title":"Blaizzy/BiSeNet-Implementation","url":"https://github.com/Blaizzy/BiSeNet-Implementation"},{"title":"pdoublerainbow/bisenet-tensorflow","url":"https://github.com/pdoublerainbow/bisenet-tensorflow"},{"title":"renhaa/semantic-diffusion","url":"https://github.com/renhaa/semantic-diffusion"},{"title":"GuangyanZhang/SCNN-Deeplabv3-bisenet-icnet","url":"https://github.com/GuangyanZhang/SCNN-Deeplabv3-bisenet-icnet"},{"title":"Shuai-Xie/BiSeNet-CCP","url":"https://github.com/Shuai-Xie/BiSeNet-CCP"},{"title":"SharifElfouly/easy-model-zoo","url":"https://github.com/SharifElfouly/easy-model-zoo"},{"title":"justld/BisNetV1_paddle","url":"https://github.com/justld/BisNetV1_paddle"},{"title":"hm7455/Anti-collision_Semantic-segmentation_","url":"https://github.com/hm7455/Anti-collision_Semantic-segmentation_"},{"title":"Asthestarsfalll/BiSeNet-MegEngine","url":"https://github.com/Asthestarsfalll/BiSeNet-MegEngine"},{"title":"CodePlay2016/BiSENet-TF","url":"https://github.com/CodePlay2016/BiSENet-TF"},{"title":"akinoriosamura/TorchSeg-mirror","url":"https://github.com/akinoriosamura/TorchSeg-mirror"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":136900,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"CamVid","model_name":"FC-DenseNet103","metrics":{"Global Accuracy":"91.5%","Mean IoU":"66.9%"},"paper_url":"http://arxiv.org/abs/1611.09326v3","paper_title":"The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation","paper_date":"2016-11-28","code_links":[{"title":"SimJeg/FC-DenseNet","url":"https://github.com/SimJeg/FC-DenseNet"},{"title":"bfortuner/pytorch_tiramisu","url":"https://github.com/bfortuner/pytorch_tiramisu"},{"title":"mrkolarik/3d-brain-segmentation","url":"https://github.com/mrkolarik/3d-brain-segmentation"},{"title":"0bserver07/One-Hundred-Layers-Tiramisu","url":"https://github.com/0bserver07/One-Hundred-Layers-Tiramisu"},{"title":"Kaido0/Brain-Tissue-Segment-Keras","url":"https://github.com/Kaido0/Brain-Tissue-Segment-Keras"},{"title":"petko-nikolov/pysemseg","url":"https://github.com/petko-nikolov/pysemseg"},{"title":"smdYe/FC-DenseNet-Keras","url":"https://github.com/smdYe/FC-DenseNet-Keras"},{"title":"asprenger/keras_fc_densenet","url":"https://github.com/asprenger/keras_fc_densenet"},{"title":"demul/image_segmentation_project","url":"https://github.com/demul/image_segmentation_project"},{"title":"ankit-vaghela30/Cilia-Segmentation","url":"https://github.com/ankit-vaghela30/Cilia-Segmentation"},{"title":"pattyhendrix/CamVid-95-accuracy","url":"https://github.com/pattyhendrix/CamVid-95-accuracy"},{"title":"SANKHA1/Vehicle-Detection","url":"https://github.com/SANKHA1/Vehicle-Detection"},{"title":"kannyjyk/Nested-UNet","url":"https://github.com/kannyjyk/Nested-UNet"},{"title":"kskim-phd/mfcn","url":"https://github.com/kskim-phd/mfcn"},{"title":"koryako/AI-application","url":"https://github.com/koryako/AI-application"},{"title":"noornk/U-Net","url":"https://github.com/noornk/U-Net"},{"title":"Septembit/Image-segmentation","url":"https://github.com/Septembit/Image-segmentation"},{"title":"IllIIIllll/where-is-wally","url":"https://github.com/IllIIIllll/where-is-wally"},{"title":"boris127/vehicle-detection","url":"https://github.com/boris127/vehicle-detection"},{"title":"datoboat/Vehicle-Detection","url":"https://github.com/datoboat/Vehicle-Detection"},{"title":"Osdel/ssnets","url":"https://github.com/Osdel/ssnets"},{"title":"Vamshi399/CarND-Vehicle-Detection","url":"https://github.com/Vamshi399/CarND-Vehicle-Detection"},{"title":"vivaan-park/where-is-wally","url":"https://github.com/vivaan-park/where-is-wally"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":136901,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"CamVid","model_name":"EDANet","metrics":{"Global Accuracy":"90.8","Mean IoU":"66.4"},"paper_url":"https://arxiv.org/abs/1809.06323v3","paper_title":"Efficient Dense Modules of Asymmetric Convolution for Real-Time Semantic Segmentation","paper_date":"2018-09-17","code_links":[{"title":"osmr/imgclsmob","url":"https://github.com/osmr/imgclsmob"},{"title":"zh320/realtime-semantic-segmentation-pytorch","url":"https://github.com/zh320/realtime-semantic-segmentation-pytorch"},{"title":"shaoyuanlo/EDANet","url":"https://github.com/shaoyuanlo/EDANet"},{"title":"wpf535236337/pytorch_EDANet","url":"https://github.com/wpf535236337/pytorch_EDANet"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":136902,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"CamVid","model_name":"Dilated Convolutions","metrics":{"Mean IoU":"65.3%"},"paper_url":"http://arxiv.org/abs/1511.07122v3","paper_title":"Multi-Scale Context Aggregation by Dilated Convolutions","paper_date":"2015-11-23","code_links":[{"title":"fyu/dilation","url":"https://github.com/fyu/dilation"},{"title":"vlievin/Unet","url":"https://github.com/vlievin/Unet"},{"title":"Wanger-SJTU/FCN-in-the-wild","url":"https://github.com/Wanger-SJTU/FCN-in-the-wild"},{"title":"keillernogueira/FDSI","url":"https://github.com/keillernogueira/FDSI"},{"title":"Entodi/meshnet-pytorch","url":"https://github.com/Entodi/meshnet-pytorch"},{"title":"harshmaru7/DilatedConv","url":"https://github.com/harshmaru7/DilatedConv"},{"title":"Rakeshpavan333/oct_dil","url":"https://github.com/Rakeshpavan333/oct_dil"},{"title":"srihari-humbarwadi/Multi-Scale-Context-Aggregation-by-Dilated-Convolutions","url":"https://github.com/srihari-humbarwadi/Multi-Scale-Context-Aggregation-by-Dilated-Convolutions"},{"title":"ajaystar8/PDRUNet-PyTorch","url":"https://github.com/ajaystar8/PDRUNet-PyTorch"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":136903,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"CamVid","model_name":"DFANet A","metrics":{"Mean IoU":"64.7%"},"paper_url":"http://arxiv.org/abs/1904.02216v1","paper_title":"DFANet: Deep Feature Aggregation for Real-Time Semantic Segmentation","paper_date":"2019-04-03","code_links":[{"title":"huaifeng1993/DFANet","url":"https://github.com/huaifeng1993/DFANet"},{"title":"j-a-lin/DFANet_PyTorch","url":"https://github.com/j-a-lin/DFANet_PyTorch"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":136904,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"CamVid","model_name":"Template-Based NAS-arch0 (480x360 inputs)","metrics":{"Mean IoU":"63.9%"},"paper_url":"https://arxiv.org/abs/1904.02365v2","paper_title":"Template-Based Automatic Search of Compact Semantic Segmentation Architectures","paper_date":"2019-04-04","code_links":[{"title":"drsleep/nas-segm-pytorch","url":"https://github.com/drsleep/nas-segm-pytorch"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":136905,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"CamVid","model_name":"LMDNet","metrics":{"Mean IoU":"63.5"},"paper_url":"http://arxiv.org/abs/1809.03994v1","paper_title":"Efficient Road Lane Marking Detection with Deep Learning","paper_date":"2018-09-11","code_links":[],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":136906,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"CamVid","model_name":"Template-Based NAS-arch1 (480x360 inputs)","metrics":{"Mean IoU":"63.2%"},"paper_url":"https://arxiv.org/abs/1904.02365v2","paper_title":"Template-Based Automatic Search of Compact Semantic Segmentation Architectures","paper_date":"2019-04-04","code_links":[{"title":"drsleep/nas-segm-pytorch","url":"https://github.com/drsleep/nas-segm-pytorch"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":136907,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"CamVid","model_name":"DeepLab-MSc-CRF-LargeFOV","metrics":{"Mean IoU":"61.6%"},"paper_url":"http://arxiv.org/abs/1412.7062v4","paper_title":"Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs","paper_date":"2014-12-22","code_links":[{"title":"tensorflow/models","url":"https://github.com/tensorflow/models"},{"title":"tensorflow/models","url":"https://github.com/tensorflow/models/tree/master/research/deeplab"},{"title":"open-mmlab/mmsegmentation","url":"https://github.com/open-mmlab/mmsegmentation"},{"title":"DeepMotionAIResearch/DenseASPP","url":"https://github.com/DeepMotionAIResearch/DenseASPP"},{"title":"nightrome/cocostuff10k","url":"https://github.com/nightrome/cocostuff10k"},{"title":"arahusky/Tensorflow-Segmentation","url":"https://github.com/arahusky/Tensorflow-Segmentation"},{"title":"TheLegendAli/DeepLab-Context","url":"https://github.com/TheLegendAli/DeepLab-Context"},{"title":"wangleihitcs/DeepLab-V1-PyTorch","url":"https://github.com/wangleihitcs/DeepLab-V1-PyTorch"},{"title":"pathak22/ccnn","url":"https://github.com/pathak22/ccnn"},{"title":"johnnylu305/Simple-does-it-weakly-supervised-instance-and-semantic-segmentation","url":"https://github.com/johnnylu305/Simple-does-it-weakly-supervised-instance-and-semantic-segmentation"},{"title":"BardOfCodes/pytorch_deeplab_large_fov","url":"https://github.com/BardOfCodes/pytorch_deeplab_large_fov"},{"title":"Jasonlee1995/DeepLab_v1","url":"https://github.com/Jasonlee1995/DeepLab_v1"},{"title":"code-implementation1/Code9","url":"https://github.com/code-implementation1/Code9/tree/main/DeepLabV3P"},{"title":"2024-MindSpore-1/Code4","url":"https://github.com/2024-MindSpore-1/Code4/tree/main/DeepLabV3P"},{"title":"NASA-NeMO-Net/NeMO-Net","url":"https://github.com/NASA-NeMO-Net/NeMO-Net"},{"title":"open-cv/deeplab-v1","url":"https://github.com/open-cv/deeplab-v1"},{"title":"Daeijavad/Deeplab-CRF","url":"https://github.com/Daeijavad/Deeplab-CRF"},{"title":"deeplab/deeplab-public","url":"https://bitbucket.org/deeplab/deeplab-public"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":136908,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"CamVid","model_name":"ReSeg","metrics":{"Global Accuracy":"88.7%","Mean IoU":"58.8%"},"paper_url":"http://arxiv.org/abs/1511.07053v3","paper_title":"ReSeg: A Recurrent Neural Network-based Model for Semantic Segmentation","paper_date":"2015-11-22","code_links":[{"title":"fvisin/reseg","url":"https://github.com/fvisin/reseg"},{"title":"mindspore-ai/contrib","url":"https://github.com/mindspore-ai/contrib/tree/master/application/ReSeg"},{"title":"SConsul/ReSeg","url":"https://github.com/SConsul/ReSeg"},{"title":"MindCode-4/code-8","url":"https://github.com/MindCode-4/code-8/tree/main/ReSeg"},{"title":"MindCode-4/code-13","url":"https://github.com/MindCode-4/code-13/tree/main/ReSeg"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":136909,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"CamVid","model_name":"SegNet","metrics":{"Mean IoU":"46.4%"},"paper_url":"http://arxiv.org/abs/1511.00561v3","paper_title":"SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation","paper_date":"2015-11-02","code_links":[{"title":"PaddlePaddle/PaddleSeg","url":"https://github.com/PaddlePaddle/PaddleSeg"},{"title":"osmr/imgclsmob","url":"https://github.com/osmr/imgclsmob"},{"title":"divamgupta/image-segmentation-keras","url":"https://github.com/divamgupta/image-segmentation-keras"},{"title":"y-ouali/pytorch_segmentation","url":"https://github.com/y-ouali/pytorch_segmentation"},{"title":"alexgkendall/caffe-segnet","url":"https://github.com/alexgkendall/caffe-segnet"},{"title":"alexgkendall/SegNet-Tutorial","url":"https://github.com/alexgkendall/SegNet-Tutorial"},{"title":"vqdang/hover_net","url":"https://github.com/vqdang/hover_net"},{"title":"vqdang/xy_net","url":"https://github.com/vqdang/xy_net"},{"title":"tkuanlun350/Tensorflow-SegNet","url":"https://github.com/tkuanlun350/Tensorflow-SegNet"},{"title":"PRBonn/bonnet","url":"https://github.com/PRBonn/bonnet"},{"title":"Yijunmaverick/GenerativeFaceCompletion","url":"https://github.com/Yijunmaverick/GenerativeFaceCompletion"},{"title":"navganti/SIVO","url":"https://github.com/navganti/SIVO"},{"title":"yubaoliu/rds-slam","url":"https://github.com/yubaoliu/rds-slam"},{"title":"arahusky/Tensorflow-Segmentation","url":"https://github.com/arahusky/Tensorflow-Segmentation"},{"title":"shanglianlm0525/CvPytorch","url":"https://github.com/shanglianlm0525/CvPytorch"},{"title":"zh320/realtime-semantic-segmentation-pytorch","url":"https://github.com/zh320/realtime-semantic-segmentation-pytorch"},{"title":"preddy5/segnet","url":"https://github.com/preddy5/segnet"},{"title":"TimoSaemann/caffe-segnet-cudnn5","url":"https://github.com/TimoSaemann/caffe-segnet-cudnn5"},{"title":"hydrogo/rainnet","url":"https://github.com/hydrogo/rainnet"},{"title":"JosephPB/XNet","url":"https://github.com/JosephPB/XNet"},{"title":"0bserver07/Keras-SegNet-Basic","url":"https://github.com/0bserver07/Keras-SegNet-Basic"},{"title":"ankit-ai/GAN_breast_mammography_segmentation","url":"https://github.com/ankit-ai/GAN_breast_mammography_segmentation"},{"title":"vinceecws/SegNet_PyTorch","url":"https://github.com/vinceecws/SegNet_PyTorch"},{"title":"trypag/pytorch-unet-segnet","url":"https://github.com/trypag/pytorch-unet-segnet"},{"title":"Charmve/Semantic-Segmentation-PyTorch","url":"https://github.com/Charmve/Semantic-Segmentation-PyTorch/blob/master/models/seg_net.py"},{"title":"Lkruitwagen/remote-sensing-solar-pv","url":"https://github.com/Lkruitwagen/remote-sensing-solar-pv"},{"title":"Violet981/Breast_mass_Segmentation","url":"https://github.com/Violet981/Breast_mass_Segmentation"},{"title":"neuropoly/multiclass-segmentation","url":"https://github.com/neuropoly/multiclass-segmentation"},{"title":"kulkarnikeerti/SegNet-Semantic-Segmentation","url":"https://github.com/kulkarnikeerti/SegNet-Semantic-Segmentation"},{"title":"ArkaJU/SegNet---Chromosome","url":"https://github.com/ArkaJU/SegNet---Chromosome"},{"title":"danielenricocahall/Keras-SegNet","url":"https://github.com/danielenricocahall/Keras-SegNet"},{"title":"alejandrodebus/SegNet","url":"https://github.com/alejandrodebus/SegNet"},{"title":"jqueguiner/camembert-as-a-service","url":"https://github.com/jqueguiner/camembert-as-a-service"},{"title":"pa56/SegNetonCityscapes","url":"https://github.com/pa56/SegNetonCityscapes"},{"title":"pa56/SegNet_on_Cityscapes","url":"https://github.com/pa56/SegNet_on_Cityscapes"},{"title":"zhuotongchen/self-healing-robust-neural-networks-via-closed-loop-control","url":"https://github.com/zhuotongchen/self-healing-robust-neural-networks-via-closed-loop-control"},{"title":"jqueguiner/image-segmentation","url":"https://github.com/jqueguiner/image-segmentation"},{"title":"akhadangi/EM-net","url":"https://github.com/akhadangi/EM-net"},{"title":"yinanzhu12/SegNet-keras","url":"https://github.com/yinanzhu12/SegNet-keras"},{"title":"yinanzhu12/SegNet-keras-implementation","url":"https://github.com/yinanzhu12/SegNet-keras-implementation"},{"title":"burakalperen/Pytorch-Semantic-Segmentation","url":"https://github.com/burakalperen/Pytorch-Semantic-Segmentation"},{"title":"arsalhuda24/SS_lstm","url":"https://github.com/arsalhuda24/SS_lstm"},{"title":"XiangbingJi/Stanford-cs230-final-project","url":"https://github.com/XiangbingJi/Stanford-cs230-final-project"},{"title":"okn-yu/SegNet-A-Deep-Convolutional-Encoder-Decoder-Architecture-for-Image-Segmentation","url":"https://github.com/okn-yu/SegNet-A-Deep-Convolutional-Encoder-Decoder-Architecture-for-Image-Segmentation"},{"title":"nisharaichur/segNet_tensorflow","url":"https://github.com/nisharaichur/segNet_tensorflow"},{"title":"CellSMB/EM-net","url":"https://github.com/CellSMB/EM-net"},{"title":"nisharaichur/SegNet-Encoder-Decoder-Architecture-for-Image-Segmentation","url":"https://github.com/nisharaichur/SegNet-Encoder-Decoder-Architecture-for-Image-Segmentation"},{"title":"navganti/SegNet","url":"https://github.com/navganti/SegNet"},{"title":"yubaoliu/caffe-segnet","url":"https://github.com/yubaoliu/caffe-segnet"},{"title":"Harsharma2308/PoseRefinement","url":"https://github.com/Harsharma2308/PoseRefinement"},{"title":"ajjdan/KaI","url":"https://github.com/ajjdan/KaI"},{"title":"stuartchen1949/segnet_paddle","url":"https://github.com/stuartchen1949/segnet_paddle"},{"title":"ayushmankumar7/SegNet---Tensorflow-2","url":"https://github.com/ayushmankumar7/SegNet---Tensorflow-2"},{"title":"ajjdan/Karst-Segmentation-from-DEM","url":"https://github.com/ajjdan/Karst-Segmentation-from-DEM"},{"title":"Tez01/SegNet-Keras-Implementation","url":"https://github.com/Tez01/SegNet-Keras-Implementation"},{"title":"hosshonarvar/Image-Segmentation","url":"https://github.com/hosshonarvar/Image-Segmentation"},{"title":"gaelmoccand/RoadSegmentation_CNN","url":"https://github.com/gaelmoccand/RoadSegmentation_CNN"},{"title":"TheUser0815/segnet-pytorch","url":"https://github.com/TheUser0815/segnet-pytorch"},{"title":"s9mondal9upriti/Segnet","url":"https://github.com/s9mondal9upriti/Segnet"},{"title":"Zhanghongbin-github/SegNet-Tutorial","url":"https://github.com/Zhanghongbin-github/SegNet-Tutorial"},{"title":"NeuronDroid/GVSS-S.A.Drone","url":"https://github.com/NeuronDroid/GVSS-S.A.Drone"},{"title":"rotemgoren/segNet","url":"https://github.com/rotemgoren/segNet"},{"title":"alexandrelewin/FollowMe","url":"https://github.com/alexandrelewin/FollowMe"},{"title":"HAN-ARK/GVSS-S.A.Drone","url":"https://github.com/HAN-ARK/GVSS-S.A.Drone"},{"title":"DarkGeekMS/Semantic_Segmentation_Models_Keras","url":"https://github.com/DarkGeekMS/Semantic_Segmentation_Models_Keras"},{"title":"billlyzhaoyh/SegNetFromScratch","url":"https://github.com/billlyzhaoyh/SegNetFromScratch"},{"title":"RajkumarPreetham/Road-scene-understanding","url":"https://github.com/RajkumarPreetham/Road-scene-understanding"},{"title":"SSN15/Behavioral-Cloning--Implementaion-of-Autonomous-car-using-deep-learning","url":"https://github.com/SSN15/Behavioral-Cloning--Implementaion-of-Autonomous-car-using-deep-learning"},{"title":"ajoshi944/Segmentation-severstal-steel","url":"https://github.com/ajoshi944/Segmentation-severstal-steel"},{"title":"Paultool/segnet","url":"https://github.com/Paultool/segnet"},{"title":"TqDavid/td","url":"https://github.com/TqDavid/td"},{"title":"azy64/Deep-Learning","url":"https://github.com/azy64/Deep-Learning"},{"title":"Fangrn/caffe-segnet","url":"https://github.com/Fangrn/caffe-segnet"},{"title":"mrmtn86/python1","url":"https://github.com/mrmtn86/python1"}],"metrics_order":"[\"Mean IoU\", \"Global Accuracy\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]}]}