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/abhishirk/Aligned_ReId
https://github.com/abuchin/resnet_sign
https://github.com/aby2s/sharpmask
https://github.com/ace19-dev/image-retrieval-tf
https://github.com/ace19-dev/mvcnn-tf
https://github.com/achen353/face-mask-detector
https://github.com/acholston/SimCLR
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/adambielski/siamese-triplet
https://github.com/aditya30394/Person-Re-Identification
https://github.com/adldotori/ResNet
https://github.com/ae-foster/pytorch-simclr
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/afzalahmad0203/Numpy-Shufflenet
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
https://github.com/afzalahmad0203/Tensorflow-Shufflenet
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
https://github.com/afzalahmad0203/tf_shufflenet
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
https://github.com/agassi4013/Log-DenseNet-Tensorflow
https://github.com/agongt408/vbranch
https://github.com/ahangchen/rank-reid
A Discriminatively Learned CNN Embedding for Person Re-identification
https://github.com/aheuillet/nasiam
https://github.com/aia39/DeepSORT-Multi-Object-Tracking-using-YOLOv5
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/aimbsg/EVA4_S15
https://github.com/airalcorn2/parking-lot-pointnetplusplus
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/ajaystar8/PDRUNet-PyTorch
https://github.com/ajcohen1/CoVision-Social-Distance-Violation-Detection
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/ajithvallabai/getsetgo_keras-beginner
https://github.com/akamaster/pytorch_resnet_cifar10
https://github.com/akar5h/Image-Recognition-with-CNN-and-Transfer-Learning-ResNet101
https://github.com/akhadangi/EM-net
https://github.com/akommini/Spoken-Numeric-Digit-detection
https://github.com/akrapukhin/MobileNetV3
https://github.com/alalagong/LEDNet
https://github.com/albarji/neurowriter
https://github.com/albumentations-team/albumentations
https://github.com/alcunha/iwildcam2021ufam
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/alecwangcq/KFAC-Pytorch
https://github.com/alex-f1tor/Image-Caption
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.