---
title: "Person re-identification (Market-1501, DukeMTMC, MSMT17)"
description: "Person re-identification (Market-1501, DukeMTMC, MSMT17): compare tasks, official access, usage conditions and evaluation. Includes research-paper mention counts and trends."
url: https://scholar4ai.com/datasets/person-re-identification-market-1501-dukemtmc-msmt17
markdown_url: https://scholar4ai.com/datasets/person-re-identification-market-1501-dukemtmc-msmt17.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "Person re-identification (Market-1501, DukeMTMC, MSMT17): compare tasks, official access, usage conditions and evaluation. Includes research-paper mention counts and trends. (as of 2026-11-05)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-05T06:02:37+09:00
window: 2026-10-07 to 2026-11-05
source: OpenAlex (CC0)
---

# Person re-identification (Market-1501, DukeMTMC, MSMT17)

[Browse dataset profiles](https://scholar4ai.com/datasets/directory/page/5.md)

Faces, people, poses, facial expressions and human actions in images and video.

- data category: Face, person and video benchmarks
- 0 papers in the last 7 days
- Names searched for: Market-1501, Market1501, DukeMTMC, MSMT17

Most-used data: https://scholar4ai.com/rankings/datasets.md · All Face, person and video benchmarks datasets: https://scholar4ai.com/datasets/face-person-and-video-benchmarks.md

## Tasks, access and usage conditions

Mention counts below measure name matches in tracked papers, not benchmark quality or downloads. A family count can cover multiple datasets; it is not a separate count for each comparison row. Choose a task and version first, preserve evaluation splits, and follow the linked release terms. The site's content license does not replace the datasets' own terms.

*Dataset comparison: tasks, access and usage conditions*

| Dataset / version | Task and evaluation | Access and preparation | Usage conditions |
|---|---|---|---|
| Market-1501 | Cross-camera person retrieval; 32,668 bounding boxes of 1,501 identities. Evaluation: Report mAP and CMC/rank-1 with the official exclusions; disclose single-/multi-query and re-ranking. | [Official source / documentation](https://zheng-lab-anu.github.io/Project/project_reid.html) Use the authors’ release links and preserve train, query, gallery, junk and distractor conventions. | The source requests citation. It does not establish a blanket commercial reuse license here; confirm permission and source-image conditions. |
| DukeMTMC / DukeMTMC-reID — historical benchmark | Multi-camera tracking and a derived person-reidentification benchmark. Evaluation: Identify parent versus re-ID derivative when reading older results; choose a currently authorized dataset for a new study. | [Official source / documentation](https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/file/077e29b11be80ab57e1a2ecabb7da330-Paper-round2.pdf) The linked dataset-lifecycle study documents retraction of the parent dataset. No active authorized download is recommended here. | Retraction and continued availability of third-party copies are different things. Do not infer authorization from a mirror. |
| MSMT17 | Person re-identification across cameras and recording conditions. Evaluation: Preserve the release’s identity-disjoint split; report mAP/rank-1, camera setup and version. | [Official source / documentation](https://www.pkuvmc.com/agreement/RELEASE_AGREEMENT-MSMT17.pdf) The release agreement specifies case-by-case academic access from PKU. Confirm present availability with the owner; the agreement itself is not a download. | Academic, non-commercial scientific research; signed agreement, required citation and restrictions on redistribution and publishing images. |

Guide updated 2026-11-05.

## Key findings

- From Nov 2023 to Oct 2026, 42 archived papers mentioned Person re-identification (Market-1501, DukeMTMC, MSMT17) in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Dec 2023 (5).
- Person re-identification (Market-1501, DukeMTMC, MSMT17) was mentioned in 2 papers in the last 30 days (2026-10-07 to 2026-11-05), ranking #127 of the 246 datasets mentioned.
- By journal category: AI (2).
- Most of them appeared in Artificial Intelligence Review (1) and Pattern Recognition (1).
- From 2017 to 2026 (so far), Person re-identification (Market-1501, DukeMTMC, MSMT17) was mentioned in 82 papers in the tracked journals, most of them in AI (82).
- 12 of them were published in 2025, against 0 in 2017.
- Since 2023, the institutions with the most of these papers were Peking University (6), Chinese Academy of Sciences (5) and University of Chinese Academy of Sciences (5).
- The journals publishing most of them were IEEE Transactions on Pattern Analysis and Machine Intelligence (11), International Journal of Computer Vision (8) and Pattern Recognition (5).
- The most-cited of them is “Improving person re-identification by attribute and identity learning” (Pattern Recognition, 2019), with 864 citations.
- Papers use Person re-identification (Market-1501, DukeMTMC, MSMT17) most often with ImageNet (21), MS COCO (6) and CIFAR-10 / CIFAR-100 (3); it has 4 partners in the code and data network, in the group around ImageNet, CIFAR-10 / CIFAR-100, MNIST / Fashion-MNIST.

## Mentions over 36 months

*Papers mentioning it by publication month, Nov 2023 to Oct 2026 (titles, abstracts and keywords; the full texts of earlier months are still being searched)*

| Trend | Nov 23–Oct 24 | Nov 24–Oct 25 | Nov 25–Oct 26 | 36 months |
|---|---:|---:|---:|---:|
|  | 21 | 14 | 7 | 42 |

## Papers per year

*Papers per publication year and category*

| Category | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | 2026 (so far) |
|---|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|
| [AI](https://scholar4ai.com/categories/ai.md) | 0 | 2 | 6 | 5 | 15 | 6 | 13 | 17 | 12 | 6 |
| All categories | 0 | 2 | 6 | 5 | 15 | 6 | 13 | 17 | 12 | 6 |

## Where the papers come from

*Journals with the most papers, since 2023*

| # | Journal | Papers |
|---:|---|---:|
| 1 | [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-pattern-analysis-and-machine-intelligence.md) | 11 |
| 2 | [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | 8 |
| 3 | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | 5 |
| 4 | [IEEE Transactions on Neural Networks and Learning Systems](https://scholar4ai.com/journals/ieee-transactions-on-neural-networks-and-learning-systems.md) | 5 |
| 5 | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | 3 |
| 6 | [Machine Learning](https://scholar4ai.com/journals/machine-learning.md) | 3 |
| 7 | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 3 |
| 8 | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 2 |
| 9 | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | 2 |
| 10 | [Information Fusion](https://scholar4ai.com/journals/information-fusion.md) | 2 |

*Institutions with the most papers, since 2023*

| # | Institution | Papers |
|---:|---|---:|
| 1 | [Peking University](https://scholar4ai.com/institutions/peking-university.md) | 6 |
| 2 | [Chinese Academy of Sciences](https://scholar4ai.com/institutions/chinese-academy-of-sciences.md) | 5 |
| 3 | [University of Chinese Academy of Sciences](https://scholar4ai.com/institutions/university-of-chinese-academy-of-sciences.md) | 5 |
| 4 | [Peng Cheng Laboratory](https://scholar4ai.com/institutions/peng-cheng-laboratory.md) | 4 |
| 5 | [University of Trento](https://scholar4ai.com/institutions/university-of-trento.md) | 3 |
| 6 | [Zhejiang University](https://scholar4ai.com/institutions/zhejiang-university.md) | 3 |
| 7 | [Beijing Jiaotong University](https://scholar4ai.com/institutions/beijing-jiaotong-university.md) | 2 |
| 8 | Changchun Normal University | 2 |
| 9 | [Chongqing University of Posts and Telecommunications](https://scholar4ai.com/institutions/chongqing-university-of-posts-and-telecommunications.md) | 2 |
| 10 | [Fudan University](https://scholar4ai.com/institutions/fudan-university.md) | 2 |

*Countries with the most papers, since 2023*

| # | Country | Papers |
|---:|---|---:|
| 1 | China | 36 |
| 2 | United States | 12 |
| 3 | United Kingdom | 4 |
| 4 | Italy | 4 |
| 5 | Australia | 3 |
| 6 | Sweden | 3 |
| 7 | Hong Kong | 2 |
| 8 | South Korea | 2 |
| 9 | Switzerland | 1 |
| 10 | Spain | 1 |

*Keywords with the most papers, since 2023*

| # | Keyword | Papers |
|---:|---|---:|
| 1 | person re-identification | 25 |
| 2 | Market-1501 | 6 |
| 3 | [knowledge distillation](https://scholar4ai.com/keywords/knowledge-distillation.md) | 5 |
| 4 | [multimodal fusion](https://scholar4ai.com/keywords/multimodal-fusion.md) | 4 |
| 5 | unsupervised domain adaptation | 4 |
| 6 | [attention mechanism](https://scholar4ai.com/keywords/attention-mechanism.md) | 3 |
| 7 | benchmark dataset | 3 |
| 8 | [data augmentation](https://scholar4ai.com/keywords/data-augmentation.md) | 3 |
| 9 | distribution shift | 3 |
| 10 | [domain generalization](https://scholar4ai.com/keywords/domain-generalization.md) | 3 |

## Most-cited papers

*Most-cited papers since 2017*

| # | Citations | Per month | Title | Journal | Published | Authors |
|---:|---:|---:|---|---|---|---|
| 1 | 864 | 9.7 | [Improving person re-identification by attribute and identity learning](https://doi.org/10.1016/j.patcog.2019.06.006) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | 2019-06-06 | Yutian Lin, Liang Zheng, Zhedong Zheng et al. |
| 2 | 248 | 2.4 | [A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets](https://doi.org/10.1109/tpami.2018.2807450) | [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-pattern-analysis-and-machine-intelligence.md) | 2018-02-19 | Srikrishna Karanam, Mengran Gou, Ziyan Wu et al. |
| 3 | 227 | 2.5 | [AlignedReID++: Dynamically matching local information for person re-identification](https://doi.org/10.1016/j.patcog.2019.05.028) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | 2019-05-15 | Hao Luo, Wei Jiang, Xuan Zhang et al. |
| 4 | 147 | 2.2 | [Identifying Visible Parts via Pose Estimation for Occluded Person Re-Identification](https://doi.org/10.1109/tnnls.2021.3059515) | [IEEE Transactions on Neural Networks and Learning Systems](https://scholar4ai.com/journals/ieee-transactions-on-neural-networks-and-learning-systems.md) | 2021-03-02 | Jiaxu Miao, Yu Wu, Yi Yang |
| 5 | 142 | 3.9 | [Occluded person re-identification with deep learning: A survey and perspectives](https://doi.org/10.1016/j.eswa.2023.122419) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 2023-11-02 | Enhao Ning, Changshuo Wang, Huang Zhang et al. |

## Used together with

Papers use Person re-identification (Market-1501, DukeMTMC, MSMT17) most often with ImageNet (21), MS COCO (6) and CIFAR-10 / CIFAR-100 (3); it has 4 partners in the code and data network, in the group around ImageNet, CIFAR-10 / CIFAR-100, MNIST / Fashion-MNIST.

*What papers use Person re-identification (Market-1501, DukeMTMC, MSMT17) together with (at least 3 papers; lift 1 = chance)*

| Used with | Type | Papers using both | Lift |
|---|---|---:|---:|
| [ImageNet](https://scholar4ai.com/datasets/imagenet.md) | Dataset | 21 | 5.2 |
| [MS COCO](https://scholar4ai.com/datasets/ms-coco.md) | Dataset | 6 | 3.8 |
| [CIFAR-10 / CIFAR-100](https://scholar4ai.com/datasets/cifar-10-cifar-100.md) | Dataset | 3 | 1.3 |
| [Face recognition (LFW, CelebA, VGGFace2)](https://scholar4ai.com/datasets/face-recognition-lfw-celeba-vggface2.md) | Dataset | 3 | 5.9 |

The whole network: https://scholar4ai.com/code/network.md

## Papers

*Papers mentioning Person re-identification (Market-1501, DukeMTMC, MSMT17) in the last 30 days, newest first.*

| Date | Title | Journal | Authors | Affiliations |
|---|---|---|---|---|
| 2026-10-22 | [Beyond the survey: a systematic empirical study of detection and association in visual MOT](https://doi.org/10.1007/s10462-026-11713-4) | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | Linh Van Ma, Juhua Hu, Wei Cheng et al. | Gwangju Institute of Science and Technology; University of Washington Tacoma |
| 2026-10-07 | [Koopman Re-ID: Modeling invariant and variant features for person re-identification](https://doi.org/10.1016/j.patcog.2026.115052) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | Jinlong Zhu, Wendong Sun, Qingliang Li et al. | Changchun Normal University |

## Cite this page

Scholar4AI. (2026). Person re-identification (Market-1501, DukeMTMC, MSMT17). Journal and Conference Research Rankings. Retrieved November 5, 2026, from https://scholar4ai.com/datasets/person-re-identification-market-1501-dukemtmc-msmt17

```bibtex
@misc{scholar4ai-datasets-person-re-identification-market-1501-dukemtmc-msmt17,
  author = {{Scholar4AI}},
  title = {Person re-identification (Market-1501, DukeMTMC, MSMT17)},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/datasets/person-re-identification-market-1501-dukemtmc-msmt17}},
  urldate = {2026-11-05},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).