mlsanityData to 7 Oct 2026

Deep learning-based person re-identification methods: A survey and outlook of recent works

arXiv 2110.04764 ↗First posted 10 Oct 2021cs.CVcited by 23

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Abstract (arXiv)

In recent years, with the increasing demand for public safety and the rapid development of intelligent surveillance networks, person re-identification (Re-ID) has become one of the hot research topics in the computer vision field. The main research goal of person Re-ID is to retrieve persons with the same identity from different cameras. However, traditional person Re-ID methods require manual marking of person targets, which consumes a lot of labor cost. With the widespread application of deep neural networks, many deep learning-based person Re-ID methods have emerged. Therefore, this paper is to facilitate researchers to understand the latest research results and the future trends in the field. Firstly, we summarize the studies of several recently published person Re-ID surveys and complement the latest research methods to systematically classify deep learning-based person Re-ID methods. Secondly, we propose a multi-dimensional taxonomy that classifies current deep learning-based person Re-ID methods into four categories according to metric and representation learning, including methods for deep metric learning, local feature learning, generative adversarial learning and sequence feature learning. Furthermore, we subdivide the above four categories according to their methodologies and motivations, discussing the advantages and limitations of part subcategories. Finally, we discuss some challenges and possible research directions for person Re-ID.

Key facts. Cited by 23 papers in the map (data through 7 Oct 2026). Builds on 113 of its 205 references that are in the map. First posted on arXiv 10 Oct 2021.

Builds on

113 of 205 references.

References · 113

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38 more
  1. 2020Deep Learning for Person Re-identification: A Survey and Outlookcited by 547
  2. 2017Person Transfer GAN to Bridge Domain Gap for Person Re-Identificationcited by 479
  3. 2017Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)cited by 472
  4. 2015Deep Metric Learning via Lifted Structured Feature Embeddingcited by 449
  5. 2019Omni-Scale Feature Learning for Person Re-Identificationcited by 292
  6. 2018Learning Discriminative Features with Multiple Granularities for Person Re-Identificationcited by 290
  7. 2017Unlabeled Samples Generated by GAN Improve the Person Re-identification Baseline in vitrocited by 280
  8. 2017Re-ranking Person Re-identification with k-reciprocal Encodingcited by 260
  9. 2017Working hard to know your neighbor's margins: Local descriptor learning losscited by 212
  10. 2018Harmonious Attention Network for Person Re-Identificationcited by 211
  11. 2019Joint Discriminative and Generative Learning for Person Re-identificationcited by 211
  12. 2016Joint Detection and Identification Feature Learning for Person Searchcited by 190
  13. 2016Person Re-identification: Past, Present and Futurecited by 180
  14. 2017Beyond triplet loss: a deep quadruplet network for person re-identificationcited by 172
  15. 2017Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identificationcited by 168
  16. 2016Person Re-identification in the Wildcited by 157
  17. 2019Progressive Pose Attention Transfer for Person Image Generationcited by 138
  18. 2019Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identificationcited by 133
  19. 2019ABD-Net: Attentive but Diverse Person Re-Identificationcited by 126
  20. 2019Relation-Aware Global Attention for Person Re-identificationcited by 124
  21. 2021Diverse Part Discovery: Occluded Person Re-identification with Part-Aware Transformercited by 119
  22. 2020Dynamic Dual-Attentive Aggregation Learning for Visible-Infrared Person Re-Identificationcited by 111
  23. 2020Unsupervised Person Re-identification via Multi-label Classificationcited by 107
  24. 2018Human Semantic Parsing for Person Re-identificationcited by 100
  25. 2017Disentangled Person Image Generationcited by 98
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  36. 2018Horizontal Pyramid Matching for Person Re-identificationcited by 70
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  38. 2017Pose-Normalized Image Generation for Person Re-identificationcited by 69

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Citing papers per year: 2022: 4; 2023: 6; 2024: 6; 2025: 7.

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  1. 2023Are These the Same Apple? Comparing Images Based on Object Intrinsicscited by 19
  2. 2022Person Re-identification: A Retrospective on Domain Specific Open Challenges and Future Trendscited by 15
  3. 2023Occluded Person Re-Identification with Deep Learning: A Survey and Perspectivescited by 13
  4. 2022Deep Learning-based Occluded Person Re-identification: A Surveycited by 12
  5. 2024PersonViT: Large-scale Self-supervised Vision Transformer for Person Re-Identificationcited by 9
  6. 2022Similarity Distribution based Membership Inference Attack on Person Re-identificationcited by 8
  7. 2025VLMs have Tunnel Vision: Evaluating Nonlocal Visual Reasoning in Leading VLMscited by 7
  8. 2025Beyond Role-Based Surgical Domain Modeling: Generalizable Re-Identification in the Operating Roomcited by 6
  9. 2023Improving CNN-based Person Re-identification using score Normalizationcited by 5
  10. 2024Deep Learning-Based Robust Multi-Object Tracking via Fusion of mmWave Radar and Camera Sensorscited by 5
  11. 2024From Attributes to Natural Language: A Survey and Foresight on Text-based Person Re-identificationcited by 5
  12. 2024CLASH: Complementary Learning with Neural Architecture Search for Gait Recognitioncited by 3
11 more
  1. 2023Revealing the Underlying Patterns: Investigating Dataset Similarity, Performance, and Generalizationcited by 1
  2. 2023YOLORe-IDNet: An Efficient Multi-Camera System for Person-Trackingcited by 1
  3. 2024Adaptive Intra-Class Variation Contrastive Learning for Unsupervised Person Re-Identificationcited by 1
  4. 2025Person detection and re-identification in open-world settings of retail stores and public spacescited by 1
  5. 2022Using Auxiliary Information for Person Re-Identification -- A Tutorial Overviewcited by 0
  6. 2023AaP-ReID: Improved Attention-Aware Person Re-identificationcited by 0
  7. 2024On the Effectiveness of Heterogeneous Ensemble Methods for Re-identificationcited by 0
  8. 2025Evolution of ReID: From Early Methods to LLM Integrationcited by 0
  9. 2025Mitigating Biases in Surgical Operating Rooms with Geometrycited by 0
  10. 2025A review of Recent Techniques for Person Re-Identificationcited by 0
  11. 2025PCD-ReID: Occluded Person Re-Identification for Base Station Inspectioncited by 0