Papers with Code 아카이브
Person Re-Identification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 13
- 평가표
- 41
- 보존된 평가 기록
- 533
Person Re-Identification is a computer vision task in which the goal is to match a person's identity across different cameras or locations in a video or image sequence. It involves detecting and tracking a person and then using features such as appearance, body shape, and clothing to match their identity in different frames. The goal is to associate the same person across multiple non-overlapping camera views in a robust and efficient manner.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/oylz/DS
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/p-mc-grath/DMMFODS
https://github.com/p3i0t/simclr-cifar10
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/pacharadanait/Densnet_project
https://github.com/pacharadanait/MobileNet_V2
https://github.com/paperswithcode/paperswithcode-client
https://github.com/parachutel/deeplabv3plus_on_Mapillary_Vistas
https://github.com/parkinkon1/simclr
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/parviagrawal/IdenProf
https://github.com/patientzero/timage-icann2019
https://github.com/paulblum00/ResNet-Recreation
https://github.com/pawelbeza/ClothesDetectorModel
https://github.com/peteryuX/arcface-tf2
https://github.com/phanav/simclr-presentation
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/philippmwirth/byol
Bootstrap your own latent: A new approach to self-supervised Learning
https://github.com/phillity/BioCapsule
https://github.com/pikkaay/efficientnet_gpu
https://github.com/pilsHan/DML
https://github.com/pilsHan/DML_for-personal-study
https://github.com/pmcgrath249/DMMFODS
https://github.com/pmcgrath249/DeepCVLab
https://github.com/pmcgrath249/DeepCV_Lab
https://github.com/ppriyank/-Online-Soft-Mining-and-Class-Aware-Attention-Pytorch
Deep Metric Learning by Online Soft Mining and Class-Aware Attention
https://github.com/ppwwyyxx/moco.tensorflow
https://github.com/princeton-vl/SimpleView
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/priyankadeybhadra/CNN-on-CIFR
https://github.com/priyavrat-misra/xrays-and-gradcam
https://github.com/pszemraj/BoulderAreaDetector
https://github.com/pudae/tensorflow-densenet
https://github.com/pvtien96/D2DP
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/pvtien96/Detectron2DeepSortPlus
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/pwc-1/Paper-5/tree/main/mobilenet_v1
https://github.com/pwc-1/Paper-5/tree/main/mobilenet_v2
https://github.com/pwc-1/Paper-9/tree/main/2/mobilenet_v2
https://github.com/pwc-1/Paper-9/tree/main/3/AGW
Deep Learning for Person Re-identification: A Survey and Outlook
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.