Papers with Code 아카이브
Pedestrian Attribute Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 8
- 보존된 평가 기록
- 30
Pedestrian attribution recognition is the task of recognizing pedestrian features - such as whether they are talking on a phone, whether they have a backpack, and so on.
<span style="color:grey; opacity: 0.6">( Image credit: HydraPlus-Net: Attentive Deep Features for Pedestrian Analysis )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yakhyo/EfficientNet-PyTorch
https://github.com/yakhyo/gaze-estimation
https://github.com/yakhyo/head-pose-estimation
https://github.com/yakhyo/retinaface-pytorch
https://github.com/yangboz/TransferLearning4Dentist
https://github.com/yangorwell/NGPlus
https://github.com/yangyucheng000/densenet/blob/main/densenet.py
https://github.com/yangyucheng000/resnet_Ascend
https://github.com/yashclone999/ResNet_MODEL
https://github.com/ycao5602/SAL
https://github.com/yibeiou/Advanced_Business_Intelligence
https://github.com/yichigo/Chest-X-Ray
https://github.com/yoshitomo-matsubara/torchdistill
https://github.com/yudhisteer/Face-Recognition-with-Masks
https://github.com/yusufsugiono/klasifikasi-gambar-bunga
https://github.com/yw0nam/DenseNet
https://github.com/yxgeee/MMT
https://github.com/zjZSTU/ResNet
https://gitlab.com/birder/birder
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.