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/LinZhuoChen/pointnet2_multi_gpu
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/LinhanDai/yolov4-deepsort
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/Liut2016/ecg-supcontrast
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/Liuyixuan95/DORN
Devil in the Details: Towards Accurate Single and Multiple Human Parsing
https://github.com/Lonepic/SPIB
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/Lornatang/ResNet-PyTorch
https://github.com/LuigiRussoDev/Covid19Detection
https://github.com/LuigiRussoDev/ResNets
https://github.com/Lw510107/PointNet
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/MARMOTatZJU/ZSLPR-TIANCHI
In Defense of the Classification Loss for Person Re-Identification
https://github.com/MEME-Phoenix/Autonomous-Driving-Cart-MEME
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/MEME-Phoenix/MEME
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/MS-Mind/MS-Code-02/tree/main/configs/mobilenetv2
https://github.com/MS-Mind/MS-Code-02/tree/main/configs/resnet
https://github.com/MS-Mind/MS-Code-02/tree/main/configs/shufflenet_v1
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
https://github.com/MS-Mind/MS-Code-06/tree/main/PAMTRI
https://github.com/MS-Mind/MS-Code-06/tree/main/osnet
Learning Generalisable Omni-Scale Representations for Person Re-Identification
https://github.com/MS-Mind/MS-Code-06/tree/main/pcb_rpp
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)
https://github.com/MTMC-DeeCamp2018/deep_sort
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/MacherLabs/deep_sort
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/Marior87/Telegram_Bot
https://github.com/MarkHershey/arxiv-dl
https://github.com/MarvinMartin24/MADA-PL
https://github.com/Masao-Taketani/FOTS_OCR
https://github.com/MatthewAbugeja/osnet
https://github.com/MaxwellHeller/coffee_fraud_detection
https://github.com/Mayurji/Image-Classification-PyTorch
https://github.com/Mayurji/SimCLR
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/MegEngine/Models/tree/master/official/vision/classification/resnet
https://github.com/MiX-S/resnet_cifar10
https://github.com/MichaelWangfc/distributed-tensorflow-resnet
https://github.com/MikelBros/Yolov3_DeepSort_Pytorch
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/Mind23-2/MindCode-101
https://github.com/Mind23-2/MindCode-101/tree/main/MGN
Learning Discriminative Features with Multiple Granularities for Person Re-Identification
https://github.com/Mind23-2/MindCode-101/tree/main/lresnet100e_ir
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.