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/2023-MindSpore-1/ms-code-215/tree/main/PAMTRI
https://github.com/2023-MindSpore-1/ms-code-215/tree/main/osnet
https://github.com/2023-MindSpore-1/ms-code-215/tree/main/pcb
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)
https://github.com/2023-MindSpore-1/ms-code-215/tree/main/pcb_rpp
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/resnet50_adv_pruning
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/simclr
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/ssd_mobilenetV2
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/ssd_mobilenetV2_FPNlite
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/ssd_resnet34
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/ssd_resnet_34
https://github.com/2023-MindSpore-1/ms-code-22
https://github.com/2023-MindSpore-1/ms-code-223/tree/main/PointNet
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/2023-MindSpore-1/ms-code-223/tree/main/PointNet2
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/2023-MindSpore-1/ms-code-223/tree/main/ShuffleNet
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
https://github.com/2023-MindSpore-1/ms-code-224/tree/main/AlignedReID
https://github.com/2023-MindSpore-1/ms-code-224/tree/main/AlignedReID%2B%2B
AlignedReID: Surpassing Human-Level Performance in Person Re-Identification
https://github.com/2023-MindSpore-1/ms-code-38
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
https://github.com/2023-MindSpore-1/ms-code-64
Deep Learning for Person Re-identification: A Survey and Outlook
https://github.com/2023-MindSpore-1/ms-code-71
Deep Attention Aware Feature Learning for Person Re-Identification
https://github.com/2023-MindSpore-1/ms-code-8/tree/main/PointNet2
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/2023-MindSpore-4/Code-5/tree/main/lresnet100e_ir
https://github.com/2023-MindSpore-4/Code-5/tree/main/metric_learn
Beyond triplet loss: a deep quadruplet network for person re-identification
https://github.com/2023-MindSpore-4/Code10/tree/main/PointNet
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/2023-MindSpore-4/Code10/tree/main/PointNet2
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/2023-MindSpore-4/Code10/tree/main/ResNet
https://github.com/2023-MindSpore-4/Code10/tree/main/SSD
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
https://github.com/2023-MindSpore-4/Code10/tree/main/ShuffleNet
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
https://github.com/2023-MindSpore-4/Code11/tree/main/resnet50_adv_pruning
https://github.com/2023-MindSpore-4/Code11/tree/main/simclr
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/2023-MindSpore-4/Code11/tree/main/ssc_resnet50
https://github.com/2023-MindSpore-4/Code11/tree/main/ssd_resnet_34
https://github.com/2023-MindSpore-4/Code16/tree/main/yanyichao/mindspore_CGPS-master
Exploring Visual Context for Weakly Supervised Person Search
https://github.com/2023-MindSpore-4/Code6/tree/main/FPL_MS-main
Rotation Invariant Transformer for Recognizing Object in UAVs
https://github.com/2023-MindSpore-4/Code6/tree/main/Rottrans_mindspore-main
Rotation Invariant Transformer for Recognizing Object in UAVs
https://github.com/2023-MindSpore-4/Code7/tree/main/ssd_mobilenetV2
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.