The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Person Re-Identification
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Person re-identification by symmetry-driven accumulation of local features
Farenzena, M., Bazzani, L., Perina, A., Murino, V., & Cristani, M. (2010) · 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2010.5539926 · Cited by 1,499
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
(1994) · 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.1994.323798 · Cited by 1,477
A Survey of Open-World Person Re-Identification
Leng, Q., Ye, M., & Tian, Q. (2020) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2019.2898940 · Cited by 318
Occluded Person Re-Identification
Zhuo, J., Chen, Z., Lai, J., & Wang, G. (2018) · 2018 IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme.2018.8486568 · Cited by 282
A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets
Karanam, S., Gou, M., Wu, Z., Rates-Borras, A., Camps, O., & Radke, R. J. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2018.2807450 · Cited by 247
Hamdoun, O., Moutarde, F., Stanciulescu, B., & Steux, B. (2008) · 2008 Second ACM/IEEE International Conference on Distributed Smart Cameras · doi:10.1109/icdsc.2008.4635689 · Cited by 237
Re-identification with RGB-D Sensors
Barbosa, I. B., Cristani, M., Del Bue, A., Bazzani, L., & Murino, V. (2012) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-33863-2_43 · Cited by 202
Uniform and Variational Deep Learning for RGB-D Object Recognition and Person Re-Identification
Ren, L., Lu, J., Feng, J., & Zhou, J. (2019) · IEEE Transactions on Image Processing · doi:10.1109/tip.2019.2915655 · Cited by 53
SARC3D: A New 3D Body Model for People Tracking and Re-identification
Baltieri, D., Vezzani, R., & Cucchiara, R. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-24085-0_21 · Cited by 46
Person Re-Identification Using Spatial and Layer-Wise Attention
Lejbølle, A. R., Nasrollahi, K., Krogh, B., & Moeslund, T. B. (2019) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2019.2938870 · Cited by 29
Cited by
Person re-identification by Local Maximal Occurrence representation and metric learning
Liao, S., Hu, Y., Zhu, X., & Li, S. Z. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298832 · Cited by 2,091
Harmonious Attention Network for Person Re-identification
Li, W., Zhu, X., & Gong, S. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00243 · Cited by 1,449
Dual Attention Matching Network for Context-Aware Feature Sequence Based Person Re-identification
Si, J., Zhang, H., Li, C.-G., Kuen, J., Kong, X., Kot, A. C., & Wang, G. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00562 · Cited by 466
Joint Learning of Single-Image and Cross-Image Representations for Person Re-identification
Wang, F., Zuo, W., Lin, L., Zhang, D., & Zhang, L. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.144 · Cited by 389
Imbalanced Deep Learning by Minority Class Incremental Rectification
Dong, Q., Gong, S., & Zhu, X. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2018.2832629 · Cited by 369
Metadata
- Venue
- Advances in Computer Vision and Pattern Recognition
- Publisher
- Springer London
- Published
- 2014
- ISSN
- 2191-6586 (ISSN-L)
- 2191-6594
- OpenAlex
- W4317524344
- Cited by
- 365
- References
- 10
- FWCI
- 32.60
- Type
- book
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Person Re-Identification. https://app.cochat.ai/papers/10.1007/978-1-4471-6296-4
- The paper
- Person Re-Identification. (2014). Advances in Computer Vision and Pattern Recognition. https://doi.org/10.1007/978-1-4471-6296-4
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
