{"task":"Semantic Segmentation","dataset":"ACDC Scribbles","metric_names":["Dice (Average)"],"rows":[{"id":36147,"task":"Semantic Segmentation","parent_task":null,"dataset":"ACDC Scribbles","model_name":"ScribFormer","metrics":{"Dice (Average)":"88.8%"},"paper_url":"https://arxiv.org/abs/2402.02029v1","paper_title":"ScribFormer: Transformer Makes CNN Work Better for Scribble-based Medical Image Segmentation","paper_date":"2024-02-03","code_links":[{"title":"HUANGLIZI/ScribFormer","url":"https://github.com/HUANGLIZI/ScribFormer"}],"metrics_order":"[\"Dice (Average)\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":36148,"task":"Semantic Segmentation","parent_task":null,"dataset":"ACDC Scribbles","model_name":"ScribbleVC","metrics":{"Dice (Average)":"88.4%"},"paper_url":"https://arxiv.org/abs/2307.16226v1","paper_title":"ScribbleVC: Scribble-supervised Medical Image Segmentation with Vision-Class Embedding","paper_date":"2023-07-30","code_links":[{"title":"huanglizi/scribblevc","url":"https://github.com/huanglizi/scribblevc"}],"metrics_order":"[\"Dice (Average)\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":36149,"task":"Semantic Segmentation","parent_task":null,"dataset":"ACDC Scribbles","model_name":"CycleMix","metrics":{"Dice (Average)":"84.8%"},"paper_url":"https://arxiv.org/abs/2203.01475v2","paper_title":"CycleMix: A Holistic Strategy for Medical Image Segmentation from Scribble Supervision","paper_date":"2022-03-03","code_links":[{"title":"bwgzk/cyclemix","url":"https://github.com/bwgzk/cyclemix"}],"metrics_order":"[\"Dice (Average)\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":36150,"task":"Semantic Segmentation","parent_task":null,"dataset":"ACDC Scribbles","model_name":"CutMix","metrics":{"Dice (Average)":"70.5%"},"paper_url":"https://arxiv.org/abs/1905.04899v2","paper_title":"CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features","paper_date":"2019-05-13","code_links":[{"title":"rwightman/pytorch-image-models","url":"https://github.com/rwightman/pytorch-image-models"},{"title":"pytorch/vision","url":"https://github.com/pytorch/vision"},{"title":"kornia/kornia","url":"https://github.com/kornia/kornia"},{"title":"PaddlePaddle/PaddleClas","url":"https://github.com/PaddlePaddle/PaddleClas"},{"title":"open-mmlab/mmclassification","url":"https://github.com/open-mmlab/mmclassification"},{"title":"clovaai/CutMix-PyTorch","url":"https://github.com/clovaai/CutMix-PyTorch"},{"title":"Westlake-AI/openmixup","url":"https://github.com/Westlake-AI/openmixup"},{"title":"ildoonet/cutmix","url":"https://github.com/ildoonet/cutmix"},{"title":"hysts/pytorch_cutmix","url":"https://github.com/hysts/pytorch_cutmix"},{"title":"IlyaDobrynin/GridMixup","url":"https://github.com/IlyaDobrynin/GridMixup"},{"title":"DevBruce/CutMixImageDataGenerator_For_Keras","url":"https://github.com/DevBruce/CutMixImageDataGenerator_For_Keras"},{"title":"wangermeng2021/FastClassification","url":"https://github.com/wangermeng2021/FastClassification"},{"title":"jis478/Tensorflow","url":"https://github.com/jis478/Tensorflow/tree/master/TF2.0/Cutmix"},{"title":"kboseong/RotNet","url":"https://github.com/kboseong/RotNet"},{"title":"TianshuXie/Cut-Thumbnail","url":"https://github.com/TianshuXie/Cut-Thumbnail"},{"title":"xden2331/attentive_cutmix","url":"https://github.com/xden2331/attentive_cutmix"},{"title":"hh-xiaohu/Image-augementation-pytorch","url":"https://github.com/hh-xiaohu/Image-augementation-pytorch"},{"title":"Bennie-Han/Image-augementation-pytorch","url":"https://github.com/Bennie-Han/Image-augementation-pytorch"},{"title":"sangHa0411/VIT","url":"https://github.com/sangHa0411/VIT"},{"title":"airplane2230/keras_cutmix","url":"https://github.com/airplane2230/keras_cutmix"},{"title":"js-aguiar/wheat-object-detection","url":"https://github.com/js-aguiar/wheat-object-detection"},{"title":"juergenlandauer/Maya-Challenge","url":"https://github.com/juergenlandauer/Maya-Challenge"},{"title":"jis478/cutmix_tensorflow2","url":"https://github.com/jis478/cutmix_tensorflow2"},{"title":"toshi-k/kaggle-bengaliai-handwritten-grapheme-classification","url":"https://github.com/toshi-k/kaggle-bengaliai-handwritten-grapheme-classification"},{"title":"PsorTheDoctor/microarray-data","url":"https://github.com/PsorTheDoctor/microarray-data"},{"title":"Kaushal28/CutMix-Regularization-using-PyTorch","url":"https://github.com/Kaushal28/CutMix-Regularization-using-PyTorch"},{"title":"SyogoShibuya/Chainer-Cutmix","url":"https://github.com/SyogoShibuya/Chainer-Cutmix"},{"title":"liuch37/image-processing","url":"https://github.com/liuch37/image-processing"},{"title":"dongdong69/MixAugmentation","url":"https://github.com/dongdong69/MixAugmentation"},{"title":"sangHa0411/ImageNet","url":"https://github.com/sangHa0411/ImageNet"}],"metrics_order":"[\"Dice (Average)\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":36151,"task":"Semantic Segmentation","parent_task":null,"dataset":"ACDC Scribbles","model_name":"TFCNs","metrics":{"Dice (Average)":"64.5%"},"paper_url":"https://arxiv.org/abs/2207.03450v1","paper_title":"TFCNs: A CNN-Transformer Hybrid Network for Medical Image Segmentation","paper_date":"2022-07-07","code_links":[{"title":"huanglizi/tfcns","url":"https://github.com/huanglizi/tfcns"}],"metrics_order":"[\"Dice (Average)\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":36152,"task":"Semantic Segmentation","parent_task":null,"dataset":"ACDC Scribbles","model_name":"Puzzle Mix","metrics":{"Dice (Average)":"62.4%"},"paper_url":"https://arxiv.org/abs/2009.06962v2","paper_title":"Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup","paper_date":"2020-09-15","code_links":[{"title":"snu-mllab/PuzzleMix","url":"https://github.com/snu-mllab/PuzzleMix"}],"metrics_order":"[\"Dice (Average)\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":137892,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"ACDC Scribbles","model_name":"ScribFormer","metrics":{"Dice (Average)":"88.8%"},"paper_url":"https://arxiv.org/abs/2402.02029v1","paper_title":"ScribFormer: Transformer Makes CNN Work Better for Scribble-based Medical Image Segmentation","paper_date":"2024-02-03","code_links":[{"title":"HUANGLIZI/ScribFormer","url":"https://github.com/HUANGLIZI/ScribFormer"}],"metrics_order":"[\"Dice (Average)\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":137893,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"ACDC Scribbles","model_name":"ScribbleVC","metrics":{"Dice (Average)":"88.4%"},"paper_url":"https://arxiv.org/abs/2307.16226v1","paper_title":"ScribbleVC: Scribble-supervised Medical Image Segmentation with Vision-Class Embedding","paper_date":"2023-07-30","code_links":[{"title":"huanglizi/scribblevc","url":"https://github.com/huanglizi/scribblevc"}],"metrics_order":"[\"Dice (Average)\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":137894,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"ACDC Scribbles","model_name":"CycleMix","metrics":{"Dice (Average)":"84.8%"},"paper_url":"https://arxiv.org/abs/2203.01475v2","paper_title":"CycleMix: A Holistic Strategy for Medical Image Segmentation from Scribble Supervision","paper_date":"2022-03-03","code_links":[{"title":"bwgzk/cyclemix","url":"https://github.com/bwgzk/cyclemix"}],"metrics_order":"[\"Dice (Average)\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":137895,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"ACDC Scribbles","model_name":"CutMix","metrics":{"Dice (Average)":"70.5%"},"paper_url":"https://arxiv.org/abs/1905.04899v2","paper_title":"CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features","paper_date":"2019-05-13","code_links":[{"title":"rwightman/pytorch-image-models","url":"https://github.com/rwightman/pytorch-image-models"},{"title":"pytorch/vision","url":"https://github.com/pytorch/vision"},{"title":"kornia/kornia","url":"https://github.com/kornia/kornia"},{"title":"PaddlePaddle/PaddleClas","url":"https://github.com/PaddlePaddle/PaddleClas"},{"title":"open-mmlab/mmclassification","url":"https://github.com/open-mmlab/mmclassification"},{"title":"clovaai/CutMix-PyTorch","url":"https://github.com/clovaai/CutMix-PyTorch"},{"title":"Westlake-AI/openmixup","url":"https://github.com/Westlake-AI/openmixup"},{"title":"ildoonet/cutmix","url":"https://github.com/ildoonet/cutmix"},{"title":"hysts/pytorch_cutmix","url":"https://github.com/hysts/pytorch_cutmix"},{"title":"IlyaDobrynin/GridMixup","url":"https://github.com/IlyaDobrynin/GridMixup"},{"title":"DevBruce/CutMixImageDataGenerator_For_Keras","url":"https://github.com/DevBruce/CutMixImageDataGenerator_For_Keras"},{"title":"wangermeng2021/FastClassification","url":"https://github.com/wangermeng2021/FastClassification"},{"title":"jis478/Tensorflow","url":"https://github.com/jis478/Tensorflow/tree/master/TF2.0/Cutmix"},{"title":"kboseong/RotNet","url":"https://github.com/kboseong/RotNet"},{"title":"TianshuXie/Cut-Thumbnail","url":"https://github.com/TianshuXie/Cut-Thumbnail"},{"title":"xden2331/attentive_cutmix","url":"https://github.com/xden2331/attentive_cutmix"},{"title":"hh-xiaohu/Image-augementation-pytorch","url":"https://github.com/hh-xiaohu/Image-augementation-pytorch"},{"title":"Bennie-Han/Image-augementation-pytorch","url":"https://github.com/Bennie-Han/Image-augementation-pytorch"},{"title":"sangHa0411/VIT","url":"https://github.com/sangHa0411/VIT"},{"title":"airplane2230/keras_cutmix","url":"https://github.com/airplane2230/keras_cutmix"},{"title":"js-aguiar/wheat-object-detection","url":"https://github.com/js-aguiar/wheat-object-detection"},{"title":"juergenlandauer/Maya-Challenge","url":"https://github.com/juergenlandauer/Maya-Challenge"},{"title":"jis478/cutmix_tensorflow2","url":"https://github.com/jis478/cutmix_tensorflow2"},{"title":"toshi-k/kaggle-bengaliai-handwritten-grapheme-classification","url":"https://github.com/toshi-k/kaggle-bengaliai-handwritten-grapheme-classification"},{"title":"PsorTheDoctor/microarray-data","url":"https://github.com/PsorTheDoctor/microarray-data"},{"title":"Kaushal28/CutMix-Regularization-using-PyTorch","url":"https://github.com/Kaushal28/CutMix-Regularization-using-PyTorch"},{"title":"SyogoShibuya/Chainer-Cutmix","url":"https://github.com/SyogoShibuya/Chainer-Cutmix"},{"title":"liuch37/image-processing","url":"https://github.com/liuch37/image-processing"},{"title":"dongdong69/MixAugmentation","url":"https://github.com/dongdong69/MixAugmentation"},{"title":"sangHa0411/ImageNet","url":"https://github.com/sangHa0411/ImageNet"}],"metrics_order":"[\"Dice (Average)\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":137896,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"ACDC Scribbles","model_name":"TFCNs","metrics":{"Dice (Average)":"64.5%"},"paper_url":"https://arxiv.org/abs/2207.03450v1","paper_title":"TFCNs: A CNN-Transformer Hybrid Network for Medical Image Segmentation","paper_date":"2022-07-07","code_links":[{"title":"huanglizi/tfcns","url":"https://github.com/huanglizi/tfcns"}],"metrics_order":"[\"Dice (Average)\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]},{"id":137897,"task":"Semantic Segmentation","parent_task":"10-shot image generation","dataset":"ACDC Scribbles","model_name":"Puzzle Mix","metrics":{"Dice (Average)":"62.4%"},"paper_url":"https://arxiv.org/abs/2009.06962v2","paper_title":"Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup","paper_date":"2020-09-15","code_links":[{"title":"snu-mllab/PuzzleMix","url":"https://github.com/snu-mllab/PuzzleMix"}],"metrics_order":"[\"Dice (Average)\"]","area":"Medical","uses_additional_data":0,"source":"archive","tags":[]}]}