Papers with Code 아카이브
Segmentation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/2023-MindSpore-1/ms-code-213/tree/main/fastscnn
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/HMR
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/IRN
IRNet: Instance Relation Network for Overlapping Cervical Cell Segmentation
https://github.com/2023-MindSpore-1/ms-code-215/tree/main/OSVOS
https://github.com/2023-MindSpore-1/ms-code-215/tree/main/pointtransformer
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/REDNet30
RedNet: Residual Encoder-Decoder Network for indoor RGB-D Semantic Segmentation
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/res2net_deeplabv3
Rethinking Atrous Convolution for Semantic Image Segmentation
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/UNet3%2B
UNet++: A Nested U-Net Architecture for Medical Image Segmentation
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/Yolact%2B%2B
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/tinydarknet
https://github.com/2023-MindSpore-1/ms-code-221/tree/main/3D-LWNet
The Little W-Net That Could: State-of-the-Art Retinal Vessel Segmentation with Minimalistic Models
https://github.com/2023-MindSpore-1/ms-code-222/tree/main/pointrend
https://github.com/2023-MindSpore-1/ms-code-223/tree/main/OCRNet
https://github.com/2023-MindSpore-1/ms-code-224/tree/main/adelaide_ea
Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells
https://github.com/2023-MindSpore-1/ms-code-42
https://github.com/2023-MindSpore-1/ms-code-43
Real-time Scene Text Detection with Differentiable Binarization
https://github.com/2023-MindSpore-1/ms-code-48
https://github.com/2023-MindSpore-1/ms-code-53
3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation
https://github.com/2023-MindSpore-1/ms-code-6/tree/main/cct
https://github.com/2023-MindSpore-1/ms-code-66
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/2023-MindSpore-1/ms-code-67
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/2023-MindSpore-1/ms-code-7/tree/main/UNet3%2B
UNet++: A Nested U-Net Architecture for Medical Image Segmentation
https://github.com/2023-MindSpore-1/ms-code-7/tree/main/Unet3d
3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation
https://github.com/2023-MindSpore-1/ms-code-7/tree/main/WGAN_GP
https://github.com/2023-MindSpore-1/ms-code-7/tree/main/Yolact%2B%2B
https://github.com/2023-MindSpore-1/ms-code-7/tree/main/tinydarknet
https://github.com/2023-MindSpore-1/ms-code-7/tree/main/u2net
A new eye segmentation method based on improved U2Net in TCM eye diagnosis
https://github.com/2023-MindSpore-4/Code-5/tree/main/meta-baseline
https://github.com/2023-MindSpore-4/Code-5/tree/main/mobilenetV3_small_x1_0
https://github.com/2023-MindSpore-4/Code-5/tree/main/mobilenetv3_large
https://github.com/2023-MindSpore-4/Code1/tree/main/DeepLabv3
Rethinking Atrous Convolution for Semantic Image Segmentation
https://github.com/2023-MindSpore-4/Code10/tree/main/DeepLabv3
Rethinking Atrous Convolution for Semantic Image Segmentation
https://github.com/2023-MindSpore-4/Code10/tree/main/FCN8s
https://github.com/2023-MindSpore-4/Code10/tree/main/MaskRCNN
https://github.com/2023-MindSpore-4/Code10/tree/main/OCRNet
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.