Papers with Code 아카이브
Pedestrian Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 9
- 보존된 평가 기록
- 92
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/rickyHong/FPN-repl
https://github.com/rickyHong/faster-rcnn-tensorflow-repl
https://github.com/rickyHong/pytorch-faster-rcnn-repl
https://github.com/rishikc137/social-distancing-detector
https://github.com/rnirdhar/yoloMultiClass
https://github.com/rnirdhar/yoloTestOneClass
https://github.com/rosinality/fcos-pytorch
https://github.com/rt55u-rgb/yolov3
https://github.com/ruinmessi/RFBNet
https://github.com/ruotianluo/pytorch-faster-rcnn
https://github.com/ryota2425/maskrcnn-benchmark
https://github.com/ryubidragonfire/mydarknet
https://github.com/s0ntr4n97/datasets
https://github.com/saber2011/darknet
https://github.com/sadicLiu/darknet-yolov4
https://github.com/sadicLiu/yolov3
https://github.com/saednasir/Helmet_Yolo
https://github.com/saimj7/Social-Distancing-Detection-in-Real-Time
https://github.com/samson6460/tf2_YOLO
https://github.com/samsonadmin/modified-alexeyab-darknet
https://github.com/saransh317/YOLOv3-Easy-Implementation
https://github.com/sarrrrry/maskrcnn-benchmark
https://github.com/sdu2011/darknet_alexyab
https://github.com/securade/hub
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
https://github.com/sejong-rcv/INSANet
https://github.com/sepuhopar/ReportDD-darknet
https://github.com/sergiosonline/transfercv
https://github.com/shanky1947/YOLOv3-Darknet-Custom-Object-Detection
https://github.com/shaojiawei07/tocom-tem
https://github.com/shashigharti/secure-privateai-scholarship-challenge
https://github.com/shikorab/tf-faster-rcnn
https://github.com/shun601/4th-tellus-satellite-challenge
https://github.com/sidSingla/RegNetx-YOLOv3
https://github.com/sidify/resnet_focal_loss
https://github.com/simonlevine/11785-project
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.