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Person Re-Identification

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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://git.unl.edu/ece-unl-images-lab/group-attention-module-person-re-id

공식 코드

Unsupervised Attention Based Instance Discriminative Learning for Person Re-Identification

https://github.com/1024ailab/reid-sepg

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Spectral Enhancement and Pseudo-Anchor Guidance for Infrared-Visible Person Re-Identification

https://github.com/123ci/PBCmodel

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Progressive Bilateral-Context Driven Model for Post-Processing Person Re-Identification

https://github.com/1kk077/idkl

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Implicit Discriminative Knowledge Learning for Visible-Infrared Person Re-Identification

https://github.com/924973292/fusionreid

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Unity is Strength: Unifying Convolutional and Transformeral Features for Better Person Re-Identification

https://github.com/AI-NERC-NUPT/PLR-OSNet

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Learning Diverse Features with Part-Level Resolution for Person Re-Identification

https://github.com/AI-Zhpp/HAT

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HAT: Hierarchical Aggregation Transformers for Person Re-identification

https://github.com/AliaksandrSiarohin/pose-gan

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Appearance and Pose-Conditioned Human Image Generation using Deformable GANs

https://github.com/BJTUJia/person_reID_DualNorm

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Frustratingly Easy Person Re-Identification: Generalizing Person Re-ID in Practice

https://github.com/CASIA-IVA-Lab/ISP-reID

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Identity-Guided Human Semantic Parsing for Person Re-Identification

https://github.com/CYFFF/DAAF_re-id

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Deep Attention Aware Feature Learning for Person Re-Identification

https://github.com/Chenfeng1271/MGMRA

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Memory Regulation and Alignment toward Generalizer RGB-Infrared Person

https://github.com/ComputerVisionIUST/IUST_PersonReId

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IUST_PersonReId: A New Domain in Person Re-Identification Datasets

https://github.com/Cysu/person_reid

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Learning Deep Feature Representations with Domain Guided Dropout for Person Re-identification

https://github.com/DengpanFu/LUPerson

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Unsupervised Pre-training for Person Re-identification

https://github.com/Dingyuan-Zheng/maskPS

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Segmentation Mask Guided End-to-End Person Search

https://github.com/EasyFL-AI/EasyFL/tree/master/applications/fedreid

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Performance Optimization for Federated Person Re-identification via Benchmark Analysis

https://github.com/Ehsan-Yaghoubi/reid-strong-baseline

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Person Re-identification: Implicitly Defining the Receptive Fields of Deep Learning Classification Frameworks

https://github.com/Ethanscuter/SimPGAN

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Cross-dataset Person Re-Identification Using Similarity Preserved Generative Adversarial Networks

https://github.com/FlyHighest/Single-Camera-Training-ReID

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Single Camera Training for Person Re-identification

https://github.com/FlyHighest/UnrealPerson

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UnrealPerson: An Adaptive Pipeline towards Costless Person Re-identification

https://github.com/FlyingRoastDuck/ACT_AAAI20

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Asymmetric Co-Teaching for Unsupervised Cross Domain Person Re-Identification

https://github.com/FlyingRoastDuck/MetaCam_DSCE

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Joint Noise-Tolerant Learning and Meta Camera Shift Adaptation for Unsupervised Person Re-Identification

https://github.com/FutabaSakuraXD/Farewell-to-Mutual-Information-Variational-Distiilation-for-Cross-Modal-Person-Re-identification

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Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-Identification

https://github.com/Gabrielcb/Leveraging_ensembles_and_self_supervised_fully_ReID

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Leveraging Ensembles and Self-Supervised Learning for Fully-Unsupervised Person Re-Identification and Text Authorship Attribution

https://github.com/Gabrielcb/Unsupervised_selfAdaptative_ReID

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Unsupervised and self-adaptative techniques for cross-domain person re-identification

https://github.com/HeliosZhao/M3L

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Learning to Generalize Unseen Domains via Memory-based Multi-Source Meta-Learning for Person Re-Identification

https://github.com/Hua-XC/MSCMNet

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MSCMNet: Multi-scale Semantic Correlation Mining for Visible-Infrared Person Re-Identification

https://github.com/IIT-PAVIS/ReId_without_Id

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Person Re-Identification without Identification via Event Anonymization

https://github.com/JDAI-CV/fast-reid

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FastReID: A Pytorch Toolbox for General Instance Re-identification

https://github.com/JeremyXSC/MCN-MT

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Learning from Self-Discrepancy via Multiple Co-teaching for Cross-Domain Person Re-Identification

https://github.com/JeyesHan/P2LR

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Delving into Probabilistic Uncertainty for Unsupervised Domain Adaptive Person Re-Identification

https://github.com/KaimingHe/resnet-1k-layers

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Deep Residual Learning for Image Recognition

https://github.com/KaiyangZhou/Dassl.pytorch

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Domain Generalization: A Survey

https://github.com/KaiyangZhou/deep-person-reid

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Omni-Scale Feature Learning for Person Re-Identification

https://github.com/Kali-Hac/Locality-Awareness-SGE

공식 코드

A Self-Supervised Gait Encoding Approach with Locality-Awareness for 3D Skeleton Based Person Re-Identification

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.