Papers with Code 아카이브
Pedestrian Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
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- 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/clasikman/darknet
https://github.com/cloudnine148/PHC_2nd_SPC
https://github.com/code-implementation1/Code2
https://github.com/code-implementation1/Code9/tree/main/RetinaFace_ResNet50
https://github.com/cshizhe/maskrcnn_benchmark
https://github.com/csm-kr/Retinanet_pytorch
https://github.com/csmiler/tf-faster-rcnn-cpu
https://github.com/cuonga1cvp/yolov3_cuong
https://github.com/cyctrung/DPnet
https://github.com/dangWV/yolov3_darknet53
https://github.com/dansthemanwhosakid/image-classification-cancer
https://github.com/danxuhk/CMT-CNN
Learning Cross-Modal Deep Representations for Robust Pedestrian Detection
https://github.com/darkAlert/yolov3-rt
https://github.com/darshans0200/YOLOTest
https://github.com/daveboat/pytorch_focal_loss
https://github.com/daxiapazi/faster-rcnn
https://github.com/dayfixer/darknet-comment
https://github.com/dc17540/darknet
https://github.com/deeplearnproject/darknet
https://github.com/delmalih/MIAS-mammography-obj-detection
https://github.com/detectionteamucas/retinanet_tensorflow
https://github.com/dianzl/sodformer
https://github.com/dipuchak95/dip_net
https://github.com/dishen12/py03
https://github.com/dnozza/profanity-obfuscation
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
https://github.com/dorbodwolf/darknet
https://github.com/dtthi/darknetAlexeyAB
https://github.com/dvl-tum/motsynth-baselines
MOTSynth: How Can Synthetic Data Help Pedestrian Detection and Tracking?
https://github.com/dwaithe/darknet3AB
https://github.com/e0015274/darknet
https://github.com/easyadin/Object-Detection-YOLOv4
https://github.com/eavise-kul/lightnet
https://github.com/edgarrt/custom_darknet
https://github.com/edwardclem/deepscribe
https://github.com/endernewton/tf-faster-rcnn
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.