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
- 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/Rahmanzia3/darknet_original
https://github.com/Rahmanzia3/yolo
https://github.com/RashadGarayev/PersonDetection
https://github.com/Raychou0830/Carplate
https://github.com/RentadroneCL/Photovoltaic_Fault_Detector
https://github.com/RentadroneCL/model-definition
https://github.com/Ricardozzf/sdsrcnn
Illuminating Pedestrians via Simultaneous Detection & Segmentation
https://github.com/RichardMathewsII/YOLBO
https://github.com/Ritik-Sharma38/YoloV3_training_Hands
https://github.com/RituYadav92/Radar-RGB-Attentive-Multimodal-Object-Detection
https://github.com/RobotMobile/cv-deep-learning-paper-review
https://github.com/RuoyuChen10/objectdetection-saliency-maps
https://github.com/SAIGANESH-Collab/DARKNET
https://github.com/SAIGANESH-Collab/YOLO-AQUA
https://github.com/SGPHD/E-Scooter_Rider_Detection
https://github.com/SGPHD/E-Scooter_Rider_Detection_Dataset
https://github.com/SJTU-Thinklab-Det/r3det-on-mmdetection
https://github.com/SanketAgrawal/Catagorical-Focal-Loss
https://github.com/Scienceseb/Input-Dropout-for-Spatially-Aligned-Modalities
https://github.com/Seioch/darknet_v4_deploy
https://github.com/ShaharrHorn/Detection-Game-logic
https://github.com/ShaojieJiang/tldr
https://github.com/Sharpiless/paddlex-driver-state-recognition
https://github.com/Sharpiless/paddlex-vehicle-detection-with-YOLOv3
https://github.com/ShawnHXH/GNN-CCA
https://github.com/Shellllllly/plateDetection
https://github.com/ShihuaHuang95/FaPN-full
https://github.com/Shraddha2013/customyolo
https://github.com/Shraddha2013/darknett
https://github.com/Shraddha2013/darknetyol
https://github.com/Shraddha2013/darknetyolo
https://github.com/Shraddha2013/darknetyolo3
https://github.com/Shraddha2013/mydarknetyolo
https://github.com/Shraddha2013/myfileyolo
https://github.com/SilvioGiancola/maskrcnn-benchmark
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.