A. Bochkovskiy, C. Y. Wang, and H. Y. M. Liao. YOLOv4: Optimal speed and accuracy of object detection. arXiv, 2020. arXiv:2004.10934. https://doi.org/10.48550/arXiv.2004.10934.

S. Bąk and P. Carr. One-shot metric learning for person re-identification. In Proc. 2017 IEEE Conf. Computer Vision and Pattern Recognition (CVPR 2017), pages 1571-1580, Honolulu, HI, USA, 21-26 Jul 2017. https://doi.org/10.1109/CVPR.2017.171. (Crossref)

Y. Dai, J. Liu, Y. Sun, et al. IDM: An intermediate domain module for domain adaptive person re-ID. In Proc. 2021 IEEE/CVF Conf. Computer Vision (ICCV 2021), pages 11844-11854, Montreal, QC, Canada, 10-17 Oct. https://doi.org/10.1109/ICCV48922.2021.01165. (Crossref)

Y. Dai, Y. Sun, J. Liu, et al. Bridging the source-to-target gap for cross-domain person re-identification with intermediate domains. ArXiv, 2022. arXiv:2203.01682v1. https://doi.org/10.48550/arXiv.2203.01682.

Z. Ding, C. Ding, Z. Shao, and D. Tao. Semantically self-aligned network for text-to-image part-aware person re-identification. arXiv, 2021. arXiv:2107.12666v2. https://doi.org/10.48550/arXiv.2107.12666.

D. Fu, D. Chen, J. Bao, et al. Unsupervised pre-training for person re-identification. In Proc. 2021 IEEE/CVF Conf. Computer Vision and Pattern Recognition (CVPR 2021), pages 14745-14754, Nashville, TN, USA, 20-25 Jun 2021. https://doi.org/10.1109/CVPR46437.2021.01451. (Crossref)

S. Gong and T. Xiang. Person re-identification. In Visual Analysis of Behaviour: From Pixels to Semantics, pages 301-313, London, 2011. Springer. https://doi.org/10.1007/978-0-85729-670-2_14. (Crossref)

D. Gray, S. Brennan, and H. Tao. Evaluating appearance models for recognition, reacquisition, and tracking. In Proc. 10th IEEE Int. Workshop on Performance Evaluation of Tracking and Surveillance (PETS 2007), Sep 2007. https://www.researchgate.net/publication/228345677_Evaluating_appearance_models_for_recognition_reacquisition_and_tracking.

K. He, X. Zhang, Sh. Ren, and J. Sun. Deep residual learning for image recognition. 2016 IEEE Conf. Computer Vision and Pattern Recognition (CVPR), pages 770-778, 2015. https://doi.org/10.1109/cvpr.2016.90. (Crossref)

M. Hirzer, C. Beleznai, P. M. Roth, and H. Bischof. Person re-identification by descriptive and discriminative classification. In Proc. Scandinavian Conf. Image Analysis (SCIA 2011), volume 6688 of Lecture Notes in Computer Science, pages 91-102, Ystad, Sweden, 23-25 May 2011. https://doi.org/10.1007/978-3-642-21227-7_9. (Crossref)

G. Huang, Zh. Liu, and K. Q. Weinberger. Densely connected convolutional networks. 2017 IEEE Conf. Computer Vision and Pattern Recognition (CVPR), pages 2261-2269, 2017. https://doi.org/10.1109/CVPR.2017.243. (Crossref)

S. Ihnatsyeva, R. Bohush, and Ablameyko. Joint dataset for CNN-based person re-identification. In Proc. 15th Int. Conf. Pattern Recognition and Information Processing (PRIP 2021), pages 33-37, Minsk, Belarus, 21-24 Sep 2021. United Institute of Informatics Problems, NAS Belarus, Minsk. https://elib.psu.by/handle/123456789/28586.

SvetlanaIgn (S. Ihnatsyeva). PolReID. GitHub, Sep 2022. https://github.com/SvetlanaIgn/PolReID. [Accessed 1 Dec 2022].

X. Jin, C. Lan, W. Zeng, et al. Style normalization and restitution for generalizable person re-identification. In Proc. 2020 IEEE/CVF Conf. Computer Vision and Pattern Recognition (CVPR 2020), pages 3140-3149, Seattle, WA, USA, 13-19 Jun 2020. https://doi.org/10.1109/cvpr42600.2020.00321. (Crossref)

X. Jing, X. Zhu, F. Wu, et al. Super-resolution person re-identification with semi-coupled low-rank discriminant dictionary learning. IEEE Transactions on Image Processing, 26(3):1363-1378, 2015. https://doi.org/10.1109/TIP.2017.2651364. (Crossref)

R. Layne, T. M. Hospedales, and S. Gong. Investigating open-world person re-identification using a drone. In Agapito L. et al., editors, Computer Vision - Proc. European Conf. Computer Vision Workshops (ECCVW 2014), volume 8927, Part III of Lecture Notes in Computer Science, pages 225–240, Zurich, Switzerland, 6-7 Sep 2014. https://doi.org/10.1007/978-3-319-16199-0_16. (Crossref)

S. Li, T. Xiao, H. Li, et al. Person search with natural language description. In Proc. 2017 IEEE Conf. Computer Vision and Pattern Recognition (CVPR 2017), pages 5187-5196, Honolulu, HI, USA, 21-26 Jul 2017. https://doi.org/10.1109/CVPR.2017.551. (Crossref)

W. Li and X. Wang. Locally aligned feature transforms across views. In Proc. 2013 IEEE Conf. Computer Vision and Pattern Recognition (CVPR 2013), pages 3594-3601, Portland, OR, USA, 23-28 Jun 2013. https://doi.org/10.1109/CVPR.2013.461. (Crossref)

W. Li, R. Zhao, and X. Wang. Human reidentification with transferred metric learning. In K. M. Lee et al., editors, Computer Vision - Proc. 11th Asian Conf. Computer Vision (ACCV 2012), volume 7724 of Lecture Notes in Computer Science, pages 31-44, Daejeon, Republic of Korea, 5-9 Nov 2012. https://doi.org/10.1007/978-3-030-58555-6_14. (Crossref)

W. Li, R. Zhao, T. Xiao, and X. Wang. DeepReID: Deep filter pairing neural network for person re-identification. In Proc. 2014 IEEE Conf. Computer Vision and Pattern Recognition (CVPR 2014), pages 152-159, Columbus, OH, USA, 23-28 Jun 2014. https://doi.org/10.1109/CVPR.2014.27. (Crossref)

X. Li, W. Zheng, X. Wang, et al. Multi-scale learning for low-resolution person re-identification. In Proc. 2015 IEEE Int. Conf. Computer Vision (ICCV 2015), pages 3765-3773, Santiago, Chile, 7-13 Dec 2015. https://doi.org/10.1109/ICCV.2015.429. (Crossref)

C. Luo, C. Song, and Z. Zhang. Generalizing person re-identification by camera-aware invariance learning and cross-domain mixup. In A. Vedaldi et al., editors, Computer Vision - Proc. European Conf. Computer Vision (ECCV 2020), volume 12360 of Lecture Notes in Computer Science, pages 224-241, Glasgow, United Kingdom, 23-28 Aug 2020. https://doi.org/10.1007/978-3-030-58555-6_14. (Crossref)

T. D. Nguyen, H. G. Hong, K. W. Kim, and K. R. Park. Person recognition system based on a combination of body images from visible light and thermal cameras. Sensors, 17(3):605, 2017. https://doi.org/10.3390/s17030605. (Crossref)

L. Pang, Y. Wang, Y. Song, et al. Cross-domain adversarial feature learning for sketch re-identification. In Proc. 26th ACM Int. Conf. Multimedia (MM '18), pages 609-617, Seoul, Republic of Korea, 22-26 Oct 2018. https://doi.org/10.1145/3240508.3240606. (Crossref)

E. Ristani, F. Solera, R. S. Zou, et al. Performance measures and a data set for multi-target, multi-camera tracking. In G. Hua et al., editors, Computer Vision - Proc. European Conf. Computer Vision Workshops (ECCVW 2020), volume 9914 of Lecture Notes in Computer Science, pages 17-35, Amsterdam, The Netherlands, 8-16 Oct 2016. https://doi.org/10.1007/978-3-319-48881-3_2. (Crossref)

Y. Shiping, S. Ihnatsyeva, R. Bohush, C. Chen, and S. Ablameyko. Estimation CNN-based person re-identification accuracy in video using different datasets. In C.-H. Chen et al., editors, Applied Mathematics, Modeling and Computer Simulation, volume 30 of Advances in Transdisciplinary Engineering, pages 978-985. IOS Press, 2022. https://doi.org/10.3233/ATDE221122. (Crossref)

G. Song, B. Leng, Y. Liu, et al. Region-based quality estimation network for large-scale person re-identification. Proc. AAAI Conf. Artificial Intelligence, 32(1):7347-7354, 2018. https://doi.org/10.1609/aaai.v32i1.12305. (Crossref)

Y. Sun, L. Zheng, Y. Yang, et al. Beyond part models: Person retrieval with refined part pooling. In V. Ferrari et al., editors, Computer Vision - Proc. European Conf. Computer Vision (ECCV 2017), volume 11208, Part IV of Lecture Notes in Computer Science, pages 501-518, Munich, Germany, 8-14 Sep 2018. https://doi.org/10.1007/978-3-030-01225-0_30. (Crossref)

Tianxiaomo. Pytorch-YOLOv4. GitHub, 2020. https://github.com/Tianxiaomo/pytorch-YOLOv4. [Accessed 1 Dec 2022].

Y. Wang, X. Liang, and S. Liao. Cloning outfits from real-world images to 3D characters for generalizable person re-identification. In Proc. 2022 IEEE/CVF Conf. Computer Vision and Pattern Recognition (CVPR 2022), pages 4890-4899, New Orleans, LA, USA, 18-24 Jun 2022. https://doi.org/10.1109/CVPR52688.2022.00485. (Crossref)

Y. Wang, S. Liao, and L. Shao. Surpassing real-world source training data: Random 3d characters for generalizable person re-identification. In Proc. 28th ACM Int. Conf. Multimedia (MM '20), Seattle, WA, USA, 12-16 Oct 2020. https://doi.org/10.1145/3394171.3413815. (Crossref)

L. Wei, S. Zhang, W. Gao, and Tian Q. Person transfer GAN to bridge domain gap for person re-identification. In Proc. 2018 IEEE/CVF Conf. Computer Vision and Pattern Recognition (CVPR 2018), pages 79-88, Salt Lake City, UT, USA, 18-23 Jun 2018. https://doi.org/10.1109/CVPR.2018.00016. (Crossref)

A. Wu, W. Zheng, H. Yu, et al. RGB-infrared cross-modality person re-identification. In Proc. 2017 IEEE Int. Conf. Computer Vision (ICCV 2017), pages 5390-5399, Venice, Italy, 22-29 Oct 2017. https://doi.org/10.1109/ICCV.2017.575. (Crossref)

D. Wu, S.-J. Zheng, X.-P. Zhang, et al. Deep learning-based methods for person re-identification: A comprehensive review. Neurocomputing, 337:354-371, 2019. https://doi.org/10.1016/j.neucom.2019.01.079. (Crossref)

T. Xiao, S. Li, B. Wang, et al. Joint detection and identification feature learning for person search. In Proc. 2017 IEEE Conf. Computer Vision and Pattern Recognition (CVPR 2017), pages 3376-3385, Honolulu, HI, USA, 21-26 Jul 2017. https://doi.org/10.1109/CVPR.2017.360. (Crossref)

T. Xiao, S. Li, B. Wang, L. Lin, and X. Wang. End-to-end deep learning for person search. Xiaogang Wang: private web page, 2016. http://www.ee.cuhk.edu.hk/ xgwang/PS/paper.pdf.

M. Ye, J. Shen, G. Lin, et al. Deep learning for person re-identification: A survey and outlook. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(6):2872-2893, 2020. https://doi.org/10.1109/TPAMI.2021.3054775. (Crossref)

T. Zhang, L. Xie, L. Wei, et al. UnrealPerson: An adaptive pipeline towards costless person re-identification. In Proc. 2021 IEEE/CVF Conf. Computer Vision and Pattern Recognition (CVPR 2021), pages 11501-11510, Nashville, TN, USA, 20-25 Jun 2021. https://doi.org/10.1109/CVPR46437.2021.01134. (Crossref)

F. Zhao, S. Liao, G. Xie, et al. Unsupervised domain adaptation with noise resistible mutual-training for person re-identification. In A. Vedaldi et al., editors, Computer Vision - Proc. European Conf. Computer Vision (ECCV 2020), volume 12356 of Lecture Notes in Computer Science, pages 526-544, Glasgow, United Kingdom, 23-28 Aug 2020. https://doi.org/10.1007/978-3-030-58621-8_31. (Crossref)

L. Zheng, Z. Bie, Y. Sun, et al. MARS: A video benchmark for large-scale person re-identification. In B. Leibe et al., editors, Computer Vision - Proc. European Conf. Computer Vision (ECCV 2016), volume 9910 of Lecture Notes in Computer Science, pages 868-884, Amsterdam, The Netherlands, 11-14 Oct 2016. https://doi.org/10.1007/978-3-319-46466-4_52. (Crossref)

L. Zheng, L. Shen, L. Tian, et al. Scalable person re-identification: A benchmark. In Proc. 2015 IEEE Int. Conf. Computer Vision (ICCV 2015), pages 1116-1124, Santiago, Chile, 7-13 Dec 2015. https://doi.org/10.1109/ICCV.2015.133. (Crossref)

L. Zheng, H. Zhang, S. Sun, et al. Person re-identification in the wild. In Proc. 2017 IEEE Conf. Computer Vision and Pattern Recognition (CVPR 2017), pages 3346-3355, Honolulu, HI, USA, 21-26 Jul 2017. https://doi.org/10.1109/CVPR.2017.357. (Crossref)

Z. Zheng, X. Yang, Z. Yu, et al. Joint discriminative and generative learning for person re-identification. In Proc. 2019 IEEE Conf. Computer Vision and Pattern Recognition (CVPR 2019), pages 2133-2142, Long Beach, CA, USA, 15-20 Jun 2019. https://doi.org/10.1109/CVPR.2019.00224. (Crossref)

layumi (Z. Zheng). Person_reID_baseline_pytorch. GitHub. https://github.com/layumi/Person_reID_baseline_pytorch. [Accessed 1 Dec 2022].

Z. Zhong, L. Zheng, D. Cao, and S. Li. Re-ranking person re-identification with k-reciprocal encoding. In Proc. 2017 IEEE Conf. Computer Vision and Pattern Recognition (CVPR 2017), pages 3652-3661, Honolulu, HI, USA, 21-26 Jul 2017. https://doi.org/10.1109/CVPR.2017.389. (Crossref)