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/PaddlePaddle/PaddleClas
https://github.com/PaddlePaddle/PaddleDetection
https://github.com/PaddlePaddle/PaddleOCR
https://github.com/PaddlePaddle/PaddleSeg
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/PanoAsh/ASOD60K
F3Net: Fusion, Feedback and Focus for Salient Object Detection
https://github.com/PanoAsh/SHD360
F3Net: Fusion, Feedback and Focus for Salient Object Detection
https://github.com/Param-Raval/ipro
https://github.com/Param-Raval/shadow-sight
https://github.com/PatriciaRodrigues1994/Satellite-Image-Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/Pchank/caffe-sal
Amulet: Aggregating Multi-level Convolutional Features for Salient Object Detection
https://github.com/PhanTom2003/PSPnet
https://github.com/PlumedSerpent/tmp_perspective_map
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/PolinaDruzhinina/mobilenet
https://github.com/PolinaDruzhinina/modelnet
https://github.com/Popcorn-sugar/Deep_v2
Rethinking Atrous Convolution for Semantic Image Segmentation
https://github.com/PurabPatel555/Pytorch-UNet-Brain-MRI
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/RamposhPidrov/waifu2face
https://github.com/Randl/MobileNetV3-pytorch
https://github.com/Res2Net/Res2Net-PoolNet
https://github.com/Res2Net/Res2Net-Pose-Estimation
https://github.com/Res2Net/Res2Net-PretrainedModels
https://github.com/Res2Net/Res2Net-maskrcnn
https://github.com/Res2Net/mmdetection
https://github.com/Rintarooo/PSPNet
https://github.com/RituYadav92/Image-segmentation
https://github.com/RoadoneP/aloha
U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection
https://github.com/Robinatp/Deeplab_Tensorflow
Rethinking Atrous Convolution for Semantic Image Segmentation
https://github.com/Rosie-Brigham/sesmeg
https://github.com/SK124/Semantic-Segmentaion-Using-UNets
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/SahinTiryaki/Brain-tumor-segmentation-Vgg19UNet
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/Sakib1263/MobileNet-1D-2D-Tensorflow-Keras
https://github.com/SarthakGarg13/Severstal-Steel-Defect-Detection
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/SeonbeomKim/TensorFlow-pix2pix
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/ShahedSabab/imagePrep
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/ShaileshKumar97/Speech-Enhancement
U-Net: Convolutional Networks for Biomedical Image Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.