Papers with Code 아카이브
Human Parsing
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
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- 보존된 평가 기록
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Human parsing is the task of segmenting a human image into different fine-grained semantic parts such as head, torso, arms and legs.
<span style="color:grey; opacity: 0.6">( Image credit: Multi-Human-Parsing (MHP) )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/DengpanFu/LUPerson
https://github.com/DivJAth/DeepLearning5922
https://github.com/EmGarr/kerod
https://github.com/Engineering-Course/LIP_JPPNet
Look into Person: Joint Body Parsing & Pose Estimation Network and A New Benchmark
https://github.com/ErikGDev/instance-segmentation
https://github.com/GAOwy123/py-faster-rcnn
https://github.com/GH3927/Mask-RCNN-applied-to-cranes
https://github.com/George-Ogden/Mask-RCNN
https://github.com/KMnP/fashionpedia-api
https://github.com/Krupal09/MaskRCNN-Demo
https://github.com/Liuyixuan95/DORN
Devil in the Details: Towards Accurate Single and Multiple Human Parsing
https://github.com/Lopezurrutia/DSB_2018
https://github.com/MIC-DKFZ/DetectionAndRegression
https://github.com/MIC-DKFZ/RegRCNN
https://github.com/MR3z4/SemanticSegmentation
https://github.com/Makunda/DeepLearningASL
https://github.com/MindSpore-MS-Code2/code0/tree/main/dlinknet
C-DLinkNet: considering multi-level semantic features for human parsing
https://github.com/MindSpore-paper-code-2/code3/tree/main/tinydarknet
https://github.com/MindSpore-paper-code-3/code3/tree/main/faster_rcnn_dcn
https://github.com/MindSpore-paper-code-3/code9/tree/main/MaskRCNN
https://github.com/Mrnoorsingh/car-parking
https://github.com/NVlabs/industreallib
https://github.com/NaturalHistoryMuseum/semantic-segmentation
Semantic Instance Segmentation with a Discriminative Loss Function
https://github.com/NiravRaiyani/Mask-R-CNN-for-water-detection
https://github.com/Okery/PyTorch-Simple-MaskRCNN
https://github.com/PaddlePaddle/PaddleDetection
https://github.com/Qinhj07/ATOMCode
https://github.com/RaiyaniNirav/Mask-R-CNN-for-water-detection
https://github.com/RajArPatra/Super-OCR
https://github.com/Rakeshvd/Instance-Segmenation-of-MRI-scan-using-Mask-RCNN
https://github.com/Rakeshvd/Semantic-Segmenation-of-MRI-scan-using-Mask-RCNN
https://github.com/RituYadav92/Radar-RGB-Attentive-Multimodal-Object-Detection
https://github.com/SUYEgit/Surgery-Robot-Detection-Segmentation
https://github.com/SfTI-Robotics/ROS-label-node
https://github.com/SonginCV/GMPHD_MAF
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.