Papers with Code 아카이브
Dense Object Detection
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/ChristianMarzahl/ObjectDetection
https://github.com/CycloneBoy/PPDetectionPytorch
https://github.com/DInesh1234-wq/tyredataset
https://github.com/DaloroAT/first_break_picking
https://github.com/DetectionTeamUCAS/RetinaNet_Tensorflow_Rotation
https://github.com/DonCorle0ne/damage_detection
https://github.com/DrMMZ/RetinaNet
https://github.com/EMsnap/RobotSorting
https://github.com/ENSTA-U2IS-AI/torch-uncertainty
https://github.com/Edwardwaw/gfocalv2
https://github.com/FL77N/RetinaNet-Based-on-PPdet
https://github.com/GXYM/Focal-loss
https://github.com/GangmingZhao/GraphFPN-Graph-Feature-Pyramid-Network-for-Object-Detection
https://github.com/Gaurav14cs17/YOLOE
https://github.com/Guillem96/efficient-net-tf
https://github.com/Guillem96/efficientdet-tf
https://github.com/HongSic/DarknetAI
https://github.com/IPLI/IPLI_Server
https://github.com/IlyaOvodov/AngelinaReader
https://github.com/JaryHuang/awesome_SSD_FPN_GIoU
https://github.com/Jo-dsa/SemanticSeg
https://github.com/KingBoyBIT/yolov3test
https://github.com/LIU1514/Yolov3-
https://github.com/Lmath11/darknet
https://github.com/MIC-DKFZ/DetectionAndRegression
https://github.com/MIC-DKFZ/RegRCNN
https://github.com/MariefW/6.-trainingYOLO
https://github.com/Maskify/darknet
https://github.com/Media-Smart/SKU110K-DenseDet
https://github.com/MegEngine/Models/tree/master/official/vision/detection
https://github.com/Mind23-2/MindCode-130
https://github.com/Mind23-2/MindCode-176
https://github.com/MindSpore-paper-code-3/code5/tree/main/retinanet_resnet101
https://github.com/MindSpore-paper-code-3/code5/tree/main/retinanet_resnet152
https://github.com/NVIDIA/retinanet-examples
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.