Papers with Code 아카이브
RGB Salient Object Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
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- 보존된 평가 기록
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RGB Salient object detection is a task-based on a visual attention mechanism, in which algorithms aim to explore objects or regions more attentive than the surrounding areas on the scene or RGB images.
<span style="color:grey; opacity: 0.6">( Image credit: Attentive Feedback Network for Boundary-Aware Salient Object Detection )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/daxiaHuang/brainstorm
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/dbailey00/Semantic-Segmentation-With-Seismic-Images
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/decentNick/Signals_big_lab_SPBSTU
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/dengpingfan/fsgan
U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection
https://github.com/devanshpratapsingh/U-net_for_Multiclass_Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/diasirish/mobilenetv3
https://github.com/divamgupta/image-segmentation-keras
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/dmlc/gluon-cv
https://github.com/dry01/segmentation-
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/dsandeep0138/UNet-Colorization
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/e9190712/vessel_segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/ekzhang/fastseg
https://github.com/emilianavt/OpenSeeFace
https://github.com/ensta-u2is/deeplabv3plus-muad-pytorch
Rethinking Atrous Convolution for Semantic Image Segmentation
https://github.com/eshaanagarwal/hr-net-implementation
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/ethanhou99/ml_learn
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/fenglian425/Agriculture_AI
https://github.com/fepegar/unet
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/filippogiruzzi/semantic_segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/fregu856/deeplabv3
Rethinking Atrous Convolution for Semantic Image Segmentation
https://github.com/frgfm/Holocron
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/fupiao1998/res2net-keras
https://github.com/galprz/brain-tumor-segemntation
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/galprz/brain-tumor-segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/ganeshpawar95/removebg1
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/gasvn/Res2Net
https://github.com/geekswaroop/Human-Parsing
https://github.com/georgeyiasemis/U-Net-PyTorch
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/gerardrbentley/Pytorch-U-Net-AutoEncoder
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/giannifranchi/deeplabv3-superpixelmix
Rethinking Atrous Convolution for Semantic Image Segmentation
https://github.com/giovanniguidi/deeplabV3-PyTorch
Rethinking Atrous Convolution for Semantic Image Segmentation
https://github.com/giovanniguidi/deeplabV3_Pytorch
Rethinking Atrous Convolution for Semantic Image Segmentation
https://github.com/gmatasci/SemanticSegmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/gomezzz/distmsmatch
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/gorjida/ap-unet
U-Net: Convolutional Networks for Biomedical Image Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.