{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,5]],"date-time":"2026-04-05T03:58:24Z","timestamp":1775361504510,"version":"3.50.1"},"reference-count":61,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,3,29]],"date-time":"2024-03-29T00:00:00Z","timestamp":1711670400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,3,29]],"date-time":"2024-03-29T00:00:00Z","timestamp":1711670400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62206083"],"award-info":[{"award-number":["62206083"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62201200"],"award-info":[{"award-number":["62201200"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Vis Comput"],"published-print":{"date-parts":[[2025,1]]},"DOI":"10.1007\/s00371-024-03329-y","type":"journal-article","created":{"date-parts":[[2024,3,29]],"date-time":"2024-03-29T21:24:23Z","timestamp":1711747463000},"page":"345-358","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Loose\u2013tight cluster regularization for unsupervised person re-identification"],"prefix":"10.1007","volume":"41","author":[{"given":"Yixiu","family":"Liu","sequence":"first","affiliation":[]},{"given":"Long","family":"Zhan","sequence":"additional","affiliation":[]},{"given":"Yu","family":"Feng","sequence":"additional","affiliation":[]},{"given":"Pengju","family":"Si","sequence":"additional","affiliation":[]},{"given":"Shaowei","family":"Jiang","sequence":"additional","affiliation":[]},{"given":"Qiang","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Chenggang","family":"Yan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,3,29]]},"reference":[{"key":"3329_CR1","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1002\/cav.2173","volume":"34","author":"Z Miao","year":"2023","unstructured":"Miao, Z., Zhang, Y., Piao, X., Chu, Y., Yin, B.: Region feature smoothness assumption for weakly semi-supervised crowd counting. Comput. Animat. Virtual Worlds 34, 3\u20134 (2023)","journal-title":"Comput. Animat. Virtual Worlds"},{"key":"3329_CR2","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1002\/cav.2094","volume":"33","author":"J Shi","year":"2022","unstructured":"Shi, J., Xiu, Y., Tang, G.: Research on occlusion block face recognition based on feature point location. Comput. Animat. Virtual Worlds 33, 3\u20134 (2022)","journal-title":"Comput. Animat. Virtual Worlds"},{"key":"3329_CR3","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1002\/cav.2187","volume":"34","author":"L Sun","year":"2023","unstructured":"Sun, L., Tang, T., Qu, Y., Qin, W.: Bidirectional temporal feature for 3d human pose and shape estimation from a video. Comput. Animat. Virtual Worlds 34, 3\u20134 (2023)","journal-title":"Comput. Animat. Virtual Worlds"},{"key":"3329_CR4","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1002\/cav.2070","volume":"33","author":"Q Xu","year":"2022","unstructured":"Xu, Q., Liu, F., Fu, Z., Zhou, A., Qi, J.: Aes-gcn: attention-enhanced semantic-guided graph convolutional networks for skeleton-based action recognition. Comput. Animat. Virtual Worlds 33, 3\u20134 (2022)","journal-title":"Comput. Animat. Virtual Worlds"},{"key":"3329_CR5","doi-asserted-by":"publisher","first-page":"2226","DOI":"10.1109\/TMM.2022.3144890","volume":"25","author":"N Jiang","year":"2023","unstructured":"Jiang, N., Sheng, B., Li, P., Lee, T.: Photohelper: portrait photographing guidance via deep feature retrieval and fusion. IEEE Trans. Multim. 25, 2226\u20132238 (2023)","journal-title":"IEEE Trans. Multim."},{"issue":"7","key":"3329_CR6","doi-asserted-by":"publisher","first-page":"6662","DOI":"10.1109\/TCYB.2021.3079311","volume":"52","author":"B Sheng","year":"2022","unstructured":"Sheng, B., Li, P., Ali, R., Chen, C.L.P.: Improving video temporal consistency via broad learning system. IEEE Trans. Cybern. 52(7), 6662\u20136675 (2022)","journal-title":"IEEE Trans. Cybern."},{"key":"3329_CR7","doi-asserted-by":"crossref","unstructured":"Ma, A.J., Yuen, P.C., Li, J.: Domain transfer support vector ranking for person re-identification without target camera label information. In: 2013 IEEE International Conference on Computer Vision, pp. 3567\u20133574 (2013)","DOI":"10.1109\/ICCV.2013.443"},{"key":"3329_CR8","doi-asserted-by":"crossref","unstructured":"Deng, W., Zheng, L., Kang, G., Yang, Y., Ye, Q., Jiao, J.: Image-image domain adaptation with preserved self-similarity and domain-dissimilarity for person re-identification. In: 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 994\u20131003 (2017)","DOI":"10.1109\/CVPR.2018.00110"},{"key":"3329_CR9","doi-asserted-by":"crossref","unstructured":"Yu, H.-X., Zheng, W., Wu, A., Guo, X., Gong, S., Lai, J.: Unsupervised person re-identification by soft multilabel learning. In: 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2143\u20132152 (2019)","DOI":"10.1109\/CVPR.2019.00225"},{"key":"3329_CR10","doi-asserted-by":"crossref","unstructured":"Zhong, Z., Zheng, L., Luo, Z., Li, S., Yang, Y.: Invariance matters: exemplar memory for domain adaptive person re-identification. In: 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 598\u2013607 (2019)","DOI":"10.1109\/CVPR.2019.00069"},{"key":"3329_CR11","doi-asserted-by":"crossref","unstructured":"Lin, Y., Dong, X., Zheng, L., Yan, Y., Yang, Y.: A bottom-up clustering approach to unsupervised person re-identification. In: AAAI Conference on Artificial Intelligence (2019)","DOI":"10.1609\/aaai.v33i01.33018738"},{"key":"3329_CR12","doi-asserted-by":"crossref","unstructured":"Zhang, X., Ge, Y., Qiao, Y., Li, H.: Refining pseudo labels with clustering consensus over generations for unsupervised object re-identification. In: 2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3435\u20133444 (2021)","DOI":"10.1109\/CVPR46437.2021.00344"},{"key":"3329_CR13","unstructured":"Fan, H., Zheng, L., Yang, Y.: Unsupervised person re-identification: clustering and fine-tuning. arXiv:1705.10444 (2017)"},{"key":"3329_CR14","doi-asserted-by":"crossref","unstructured":"Schroff, F., Kalenichenko, D., Philbin, J.: Facenet: a unified embedding for face recognition and clustering. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 815\u2013823 (2015)","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"3329_CR15","unstructured":"Hermans, A., Beyer, L., Leibe, B.: In defense of the triplet loss for person re-identification. arXiv:1703.07737 (2017)"},{"key":"3329_CR16","unstructured":"van den Oord, A., Li, Y., Vinyals, O.: Representation learning with contrastive predictive coding. arXiv:1807.03748 (2018)"},{"key":"3329_CR17","doi-asserted-by":"crossref","unstructured":"Wang, D., Zhang, S.: Unsupervised person re-identification via multi-label classification. In: 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 10978\u201310987 (2020)","DOI":"10.1109\/CVPR42600.2020.01099"},{"key":"3329_CR18","unstructured":"Ge, Y., Chen, D., Zhu, F., Zhao, R., Li, H.: Self-paced contrastive learning with hybrid memory for domain adaptive object re-id. arXiv:2006.02713 (2020)"},{"issue":"10","key":"3329_CR19","doi-asserted-by":"publisher","first-page":"5121","DOI":"10.1007\/s00371-022-02649-1","volume":"39","author":"T Si","year":"2023","unstructured":"Si, T., He, F., Li, P.: Hybrid feature constraint with clustering for unsupervised person re-identification. Vis. Comput. 39(10), 5121\u20135133 (2023)","journal-title":"Vis. Comput."},{"key":"3329_CR20","unstructured":"Ester, M., Kriegel, H.-P., Sander, J., Xu, X.: A density-based algorithm for discovering clusters in large spatial databases with noise. In: Knowledge Discovery and Data Mining (1996)"},{"key":"3329_CR21","doi-asserted-by":"publisher","first-page":"881","DOI":"10.1109\/TPAMI.2002.1017616","volume":"24","author":"T Kanungo","year":"2002","unstructured":"Kanungo, T., Mount, D.M., Netanyahu, N.S., Piatko, C.D., Silverman, R., Wu, A.Y.: An efficient k-means clustering algorithm: analysis and implementation. IEEE Trans. Pattern Anal. Mach. Intell. 24, 881\u2013892 (2002)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"3329_CR22","doi-asserted-by":"crossref","unstructured":"Zheng, K., Lan, C., Zeng, W., Zhang, Z., Zha, Z.: Exploiting sample uncertainty for domain adaptive person re-identification. In: AAAI Conference on Artificial Intelligence (2020)","DOI":"10.1609\/aaai.v35i4.16468"},{"key":"3329_CR23","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/0377-0427(87)90125-7","volume":"20","author":"PJ Rousseeuw","year":"1987","unstructured":"Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. J. Comput. Appl. Math. 20, 53\u201365 (1987). https:\/\/doi.org\/10.1016\/0377-0427(87)90125-7","journal-title":"J. Comput. Appl. Math."},{"key":"3329_CR24","doi-asserted-by":"crossref","unstructured":"Lin, Y., Xie, L., Wu, Y., Yan, C.C., Tian, Q.: Unsupervised person re-identification via softened similarity learning. In: 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3387\u20133396 (2020)","DOI":"10.1109\/CVPR42600.2020.00345"},{"key":"3329_CR25","doi-asserted-by":"crossref","unstructured":"Cho, Y.H., Kim, W.J., Hong, S., Eui Yoon, S.: Part-based pseudo label refinement for unsupervised person re-identification. In: 2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 7298\u20137308 (2022)","DOI":"10.1109\/CVPR52688.2022.00716"},{"issue":"3","key":"3329_CR26","doi-asserted-by":"publisher","first-page":"3395","DOI":"10.1109\/TITS.2022.3224233","volume":"24","author":"M Xu","year":"2023","unstructured":"Xu, M., Guo, H., Jia, Y., Dai, Z., Wang, J.: Pseudo label rectification with joint camera shift adaptation and outlier progressive recycling for unsupervised person re-identification. IEEE Trans. Intell. Transp. Syst. 24(3), 3395\u20133406 (2023)","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"issue":"8","key":"3329_CR27","doi-asserted-by":"publisher","first-page":"4499","DOI":"10.1109\/TNNLS.2021.3116209","volume":"34","author":"Z Xie","year":"2023","unstructured":"Xie, Z., Zhang, W., Sheng, B., Li, P., Chen, C.L.P.: Bagfn: broad attentive graph fusion network for high-order feature interactions. IEEE Trans. Neural Netw. Learn. Syst. 34(8), 4499\u20134513 (2023)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"3329_CR28","doi-asserted-by":"crossref","unstructured":"Sun, Y., Zheng, L., Yang, Y., Tian, Q., Wang, S.: Beyond part models: person retrieval with refined part pooling. In: European Conference on Computer Vision (2017)","DOI":"10.1007\/978-3-030-01225-0_30"},{"issue":"11","key":"3329_CR29","doi-asserted-by":"crossref","first-page":"13 489","DOI":"10.1109\/TPAMI.2023.3289667","volume":"45","author":"Z Chen","year":"2023","unstructured":"Chen, Z., Qiu, G., Li, P., Zhu, L., Yang, X., Sheng, B.: MNGNAS: distilling adaptive combination of multiple searched networks for one-shot neural architecture search. IEEE Trans. Pattern Anal. Mach. Intell. 45(11), 13 489-13 508 (2023)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"3329_CR30","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1109\/TMM.2021.3120873","volume":"25","author":"X Lin","year":"2023","unstructured":"Lin, X., Sun, S., Huang, W., Sheng, B., Li, P., Feng, D.D.: EAPT: efficient attention pyramid transformer for image processing. IEEE Trans. Multim. 25, 50\u201361 (2023)","journal-title":"IEEE Trans. Multim."},{"issue":"1","key":"3329_CR31","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1109\/TII.2021.3085669","volume":"18","author":"J Li","year":"2022","unstructured":"Li, J., Chen, J., Sheng, B., Li, P., Yang, P., Feng, D.D., Qi, J.: Automatic detection and classification system of domestic waste via multimodel cascaded convolutional neural network. IEEE Trans. Ind. Inf. 18(1), 163\u2013173 (2022)","journal-title":"IEEE Trans. Ind. Inf."},{"key":"3329_CR32","unstructured":"Cheng, H., Zhu, Z., Li, X., Gong, Y., Sun, X., Liu, Y.: Learning with instance-dependent label noise: a sample sieve approach. arXiv:2010.02347 (2020)"},{"key":"3329_CR33","doi-asserted-by":"publisher","first-page":"3180","DOI":"10.1109\/TMM.2020.2972125","volume":"22","author":"C Zhao","year":"2020","unstructured":"Zhao, C., Lv, X., Zhang, Z., Zuo, W., Wu, J., Miao, D.: Deep fusion feature representation learning with hard mining center-triplet loss for person re-identification. IEEE Trans. Multimedia 22, 3180\u20133195 (2020)","journal-title":"IEEE Trans. Multimedia"},{"key":"3329_CR34","unstructured":"Ge, Y., Chen, D., Li, H.: Mutual mean-teaching: pseudo label refinery for unsupervised domain adaptation on person re-identification. arXiv:2001.01526 (2020)"},{"key":"3329_CR35","unstructured":"Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., Uszkoreit, J., Houlsby, N.: An image is worth 16x16 words: transformers for image recognition at scale. arXiv:2010.11929 (2020)"},{"key":"3329_CR36","doi-asserted-by":"crossref","unstructured":"He, S., Luo, H., Wang, P., Wang, F., Li, H., Jiang, W.: Transreid: transformer-based object re-identification. In: 2021 IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 14993\u201315002 (2021)","DOI":"10.1109\/ICCV48922.2021.01474"},{"key":"3329_CR37","doi-asserted-by":"crossref","unstructured":"Fu, D., Chen, D., Bao, J., Yang, H., Yuan, L., Zhang, L., Li, H., Chen, D.: Unsupervised pre-training for person re-identification. In: 2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 14745\u201314754 (2020)","DOI":"10.1109\/CVPR46437.2021.01451"},{"key":"3329_CR38","doi-asserted-by":"publisher","first-page":"236","DOI":"10.1080\/01621459.1963.10500845","volume":"58","author":"JH Ward","year":"1963","unstructured":"Ward, J.H.: Hierarchical grouping to optimize an objective function. J. Am. Stat. Assoc. 58, 236\u2013244 (1963)","journal-title":"J. Am. Stat. Assoc."},{"key":"3329_CR39","doi-asserted-by":"crossref","unstructured":"Feng, Y., Zhao, S., Zhang, Y., Liu, Y., Zhu, S., Coleman, S. A.: Noise-tolerant learning with silhouette coefficient for unsupervised person re-identification. In: 2022 IEEE International Conference on Multimedia and Expo (ICME), pp. 1\u20136 (2022)","DOI":"10.1109\/ICME52920.2022.9859824"},{"key":"3329_CR40","doi-asserted-by":"crossref","unstructured":"He, K., Fan, H., Wu, Y., Xie, S., Girshick, R.B.: Momentum contrast for unsupervised visual representation learning. In: 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 9726\u20139735 (2019)","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"3329_CR41","doi-asserted-by":"crossref","unstructured":"Zhong, Z., Zheng, L., Cao, D., Li, S.: Re-ranking person re-identification with k-reciprocal encoding. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3652\u20133661 (2017)","DOI":"10.1109\/CVPR.2017.389"},{"key":"3329_CR42","doi-asserted-by":"publisher","first-page":"395","DOI":"10.1007\/s11222-007-9033-z","volume":"17","author":"U von Luxburg","year":"2007","unstructured":"von Luxburg, U.: A tutorial on spectral clustering. Stat. Comput. 17, 395\u2013416 (2007)","journal-title":"Stat. Comput."},{"key":"3329_CR43","doi-asserted-by":"crossref","unstructured":"Zhai, Y., Ye, Q., Lu, S., Jia, M., Ji, R., Tian, Y.: Multiple expert brainstorming for domain adaptive person re-identification. arXiv:2007.01546 (2020)","DOI":"10.1007\/978-3-030-58571-6_35"},{"key":"3329_CR44","doi-asserted-by":"crossref","unstructured":"Zheng, K., Liu, W., He, L., Mei, T., Luo, J., Zha, Z.: Group-aware label transfer for domain adaptive person re-identification. In: 2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5306\u20135315 (2021)","DOI":"10.1109\/CVPR46437.2021.00527"},{"key":"3329_CR45","doi-asserted-by":"publisher","first-page":"3825","DOI":"10.1109\/TCSVT.2021.3118060","volume":"32","author":"S Li","year":"2022","unstructured":"Li, S., Yuan, M., Chen, J., Hu, Z.: Adadc: adaptive deep clustering for unsupervised domain adaptation in person re-identification. IEEE Trans. Circuits Syst. Video Technol. 32, 3825\u20133838 (2022)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"3329_CR46","doi-asserted-by":"publisher","first-page":"5802","DOI":"10.1109\/TCSVT.2023.3258917","volume":"33","author":"J Peng","year":"2023","unstructured":"Peng, J., Jiang, G., Wang, H.: Adaptive memorization with group labels for unsupervised person re-identification. IEEE Trans. Circuits Syst. Video Technol. 33, 5802\u20135813 (2023)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"3329_CR47","doi-asserted-by":"crossref","unstructured":"Zeng, K., Ning, M., Wang, Y., Guo, Y.: Hierarchical clustering with hard-batch triplet loss for person re-identification. In: 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 13654\u201313662 (2019)","DOI":"10.1109\/CVPR42600.2020.01367"},{"key":"3329_CR48","doi-asserted-by":"crossref","unstructured":"Wang, Z., Zhang, J., Zheng, L., Liu, Y., Sun, Y., Li, Y., Wang, S.: Cycas: self-supervised cycle association for learning re-identifiable descriptions. In: European Conference on Computer Vision (2020)","DOI":"10.1007\/978-3-030-58621-8_5"},{"key":"3329_CR49","unstructured":"Dai, Z., Wang, G., Zhu, S., Yuan, W., Tan, P.: Cluster contrast for unsupervised person re-identification. In: Asian Conference on Computer Vision (2021)"},{"key":"3329_CR50","doi-asserted-by":"crossref","unstructured":"Zhang, X., Li, D., Wang, Z., Wang, J., Ding, E., Shi, J. Q., Zhang, Z., Wang, J.: Implicit sample extension for unsupervised person re-identification. In: 2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 7359\u20137368 (2022)","DOI":"10.1109\/CVPR52688.2022.00722"},{"key":"3329_CR51","doi-asserted-by":"crossref","unstructured":"He, Q., Wang, Z., Zheng, Z., Hu, H.: Spatial and temporal dual-attention for unsupervised person re-identification. In: IEEE Transactions on Intelligent Transportation Systems (2023)","DOI":"10.1109\/TITS.2023.3314453"},{"key":"3329_CR52","doi-asserted-by":"publisher","first-page":"3338","DOI":"10.1109\/TIP.2023.3278860","volume":"32","author":"L Lan","year":"2022","unstructured":"Lan, L., Teng, X., Zhang, J., Zhang, X., Tao, D.: Learning to purification for unsupervised person re-identification. IEEE Trans. Image Process. 32, 3338\u20133353 (2022)","journal-title":"IEEE Trans. Image Process."},{"key":"3329_CR53","doi-asserted-by":"publisher","first-page":"5908","DOI":"10.1109\/TCSVT.2023.3261898","volume":"33","author":"Z Chen","year":"2022","unstructured":"Chen, Z., Cui, Z., Zhang, C., Zhou, J., Liu, Y.: Dual clustering co-teaching with consistent sample mining for unsupervised person re-identification. IEEE Trans. Circuits Syst. Video Technol. 33, 5908\u20135920 (2022)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"3329_CR54","doi-asserted-by":"crossref","unstructured":"Zhu, K., Guo, H., Yan, T., Zhu, Y., Wang, J., Tang, M.: Part-aware self-supervised pre-training for person re-identification. In: European Conference on Computer Vision (2022)","DOI":"10.1007\/978-3-031-19781-9_12"},{"key":"3329_CR55","unstructured":"Luo, H., Wang, P., Xu, Y., Ding, F., Zhou, Y., Wang, F., Li, H., Jin, R.: Self-supervised pre-training for transformer-based person re-identification. arXiv:2111.12084 (2021)"},{"key":"3329_CR56","doi-asserted-by":"crossref","unstructured":"Yang, E., Li, C., Liu, S., Liu, Y., Zhao, S., Huang, N.: Self-supervised pre-training with learnable tokenizers for person re-identification in railway stations. In: 2022 16th IEEE International Conference on Signal Processing (ICSP), vol. 1, pp. 325\u2013330 (2022)","DOI":"10.1109\/ICSP56322.2022.9965305"},{"key":"3329_CR57","doi-asserted-by":"crossref","unstructured":"Tao, Y., Zhang, J., Chen, T., Wang, Y., Zhu, Y.: Transformer-based contrastive learning for unsupervised person re-identification. In: 2022 International Joint Conference on Neural Networks (IJCNN), pp. 1\u20139 (2022)","DOI":"10.1109\/IJCNN55064.2022.9892516"},{"key":"3329_CR58","doi-asserted-by":"crossref","unstructured":"Ristani, E., Solera, F., Zou, R. S., Cucchiara, R., Tomasi, C.: Performance measures and a data set for multi-target, multi-camera tracking. In: ECCV Workshops (2016)","DOI":"10.1007\/978-3-319-48881-3_2"},{"key":"3329_CR59","doi-asserted-by":"crossref","unstructured":"Zheng, L., Shen, L., Tian, L., Wang, S., Wang, J., Tian, Q.: Scalable person re-identification: a benchmark. In: 2015 IEEE International Conference on Computer Vision (ICCV), pp. 1116\u20131124 (2015)","DOI":"10.1109\/ICCV.2015.133"},{"key":"3329_CR60","doi-asserted-by":"crossref","unstructured":"Wei, L., Zhang, S., Gao, W., Tian, Q.: Person transfer gan to bridge domain gap for person re-identification. In: 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 79\u201388 (2017)","DOI":"10.1109\/CVPR.2018.00016"},{"key":"3329_CR61","unstructured":"Xing, E.P., Ng, A., Jordan, M.I., Russell, S.J.: Distance metric learning with application to clustering with side-information. In: NIPS (2002)"}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-024-03329-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00371-024-03329-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-024-03329-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,24]],"date-time":"2025-01-24T12:59:50Z","timestamp":1737723590000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00371-024-03329-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,29]]},"references-count":61,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,1]]}},"alternative-id":["3329"],"URL":"https:\/\/doi.org\/10.1007\/s00371-024-03329-y","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"value":"0178-2789","type":"print"},{"value":"1432-2315","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,3,29]]},"assertion":[{"value":"23 February 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 March 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}