Papers with Code 아카이브
Pedestrian Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
- 9
- 보존된 평가 기록
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Pedestrian detection is the task of detecting pedestrians from a camera.
Further state-of-the-art results (e.g. on the KITTI dataset) can be found at 3D Object Detection.
<span style="color:grey; opacity: 0.6">( Image credit: High-level Semantic Feature Detection: A New Perspective for Pedestrian Detection )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/mindspore-ai/models/blob/master/official/cv/retinanet/
https://github.com/mindspore-ai/models/blob/master/research/cv/retinanet_resnet152
https://github.com/ming71/UCAS-AOD-benchmark
https://github.com/minhcong0891/wheat-detection
https://github.com/minhdua/PHONES
https://github.com/mkang315/rcs-yolo
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
https://github.com/mkocabas/focal-loss-keras
https://github.com/moallafatma/Breast_Cancer_Detection_Classification
https://github.com/modelhub-ai/yolo-v3
https://github.com/modelscope/modelscope
https://github.com/molyswu/knowledge-graph-embeding
https://github.com/monk-ai/maskrcnn
https://github.com/muddge/yolov3-person-only
https://github.com/munachisonwadike/YOLOV3
https://github.com/mutichung/yolov3_pt
https://github.com/muyiguangda/pytorch-yolov3
https://github.com/mvxxx/mimuw-hats
https://github.com/namdvt/Focal-loss-pytorch-implementation
https://github.com/nautilus261/tf-faster-rcnn
https://github.com/neilctwu/FCOS-pytorch_Simplified
https://github.com/neshitov/UNet
https://github.com/neung678/anti_bird
https://github.com/neuqgz/modify-faster-rcnn-tf
https://github.com/neuralmagic/sparseml
https://github.com/neuralmagic/sparsify
https://github.com/neverleave0916/darknet
https://github.com/nghgphi/fire_detection
https://github.com/nguoido/Yolo-alexeyAB
https://github.com/nilesh0109/PedestrianTracking
https://github.com/nlee-208/face_mask_detection
https://github.com/nmcasasr/darknet2
https://github.com/nmcasasr/darknet_oldVersion
https://github.com/nurulxakmar/darknet
https://github.com/ogatarina-sq/secyolov7
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
https://github.com/okboseong/darknet
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.