{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T11:02:27Z","timestamp":1768993347423,"version":"3.49.0"},"publisher-location":"Singapore","reference-count":45,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819556922","type":"print"},{"value":"9789819556939","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-981-95-5693-9_14","type":"book-chapter","created":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T21:22:29Z","timestamp":1768944149000},"page":"196-209","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["VAMN: View-Invariant Adaptive Multi-granularity Network for\u00a0Unsupervised Vessel Re-identification"],"prefix":"10.1007","author":[{"given":"Yize","family":"Ma","sequence":"first","affiliation":[]},{"given":"Yongguo","family":"Ling","sequence":"additional","affiliation":[]},{"given":"Gangzhu","family":"Lin","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,1,21]]},"reference":[{"issue":"8","key":"14_CR1","doi-asserted-by":"publisher","first-page":"4756","DOI":"10.1016\/j.jksuci.2021.05.001","volume":"34","author":"B Ait Skourt","year":"2022","unstructured":"Ait Skourt, B., El Hassani, A., Majda, A.: Mixed-pooling-dropout for convolutional neural network regularization. J. King Saud Univ. CIS 34(8), 4756\u20134762 (2022)","journal-title":"J. King Saud Univ. CIS"},{"key":"14_CR2","doi-asserted-by":"crossref","unstructured":"Cao, Y., Liu, J., Yu, Z., Li, X., Wei, L., Wu, Z.: Vessel re-identification by a hierarchical perceptual aggregation network with inclination-aware attention. Comput. J. (2024)","DOI":"10.1093\/comjnl\/bxae136"},{"key":"14_CR3","doi-asserted-by":"crossref","unstructured":"Chen, H., Lagadec, B., Bremond, F.: Ice: inter-instance contrastive encoding for unsupervised person re-identification. In: ICCV, pp. 14960\u201314969 (2021)","DOI":"10.1109\/ICCV48922.2021.01469"},{"key":"14_CR4","doi-asserted-by":"crossref","unstructured":"Chen, H., Wang, Y., Lagadec, B., Dantcheva, A., Bremond, F.: Joint generative and contrastive learning for unsupervised person re-identification. In: CVPR, pp. 2004\u20132013 (2021)","DOI":"10.1109\/CVPR46437.2021.00204"},{"key":"14_CR5","doi-asserted-by":"crossref","unstructured":"Cho, Y., Kim, W.J., Hong, S., Yoon, S.E.: Part-based pseudo label refinement for unsupervised person re-identification. In: CVPR, pp. 7308\u20137318 (2022)","DOI":"10.1109\/CVPR52688.2022.00716"},{"key":"14_CR6","doi-asserted-by":"crossref","unstructured":"Dai, W., Lu, L., Li, Z.: Diffusion-based synthetic data generation for visible-infrared person re-identification. In: AAAI, vol.\u00a039, pp. 11185\u201311193 (2025)","DOI":"10.1609\/aaai.v39i11.33216"},{"key":"14_CR7","unstructured":"Dai, Z., Wang, G., Yuan, W., Zhu, S., Tan, P.: Cluster contrast for unsupervised person re-identification. In: ACCV, pp. 1142\u20131160 (2022)"},{"key":"14_CR8","doi-asserted-by":"crossref","unstructured":"Fu, Y., Wei, Y., Wang, G., Zhou, Y., Shi, H., Huang, T.S.: Self-similarity grouping: a simple unsupervised cross domain adaptation approach for person re-identification. In: ICCV, pp. 6112\u20136121 (2019)","DOI":"10.1109\/ICCV.2019.00621"},{"key":"14_CR9","unstructured":"Ge, Y., Chen, D., Li, H.: Mutual mean-teaching: pseudo label refinery for unsupervised domain adaptation on person re-identification. arXiv preprint arXiv:2001.01526 (2020)"},{"key":"14_CR10","first-page":"11309","volume":"33","author":"Y Ge","year":"2020","unstructured":"Ge, Y., Zhu, F., Chen, D., Zhao, R., et al.: Self-paced contrastive learning with hybrid memory for domain adaptive object re-id. NeurIPS 33, 11309\u201311321 (2020)","journal-title":"NeurIPS"},{"key":"14_CR11","doi-asserted-by":"crossref","unstructured":"Ghahremani, A., Kong, Y., Bondarev, E., de With, P.H.: Re-identification of vessels with convolutional neural networks. In: ICCTA, pp. 93\u201397 (2019)","DOI":"10.1145\/3323933.3324075"},{"key":"14_CR12","doi-asserted-by":"crossref","unstructured":"Guo, J., Yuan, Y., Huang, L., Zhang, C., Yao, J.G., Han, K.: Beyond human parts: dual part-aligned representations for person re-identification. In: ICCV, pp. 3642\u20133651 (2019)","DOI":"10.1109\/ICCV.2019.00374"},{"issue":"2","key":"14_CR13","first-page":"1953","volume":"25","author":"Q He","year":"2023","unstructured":"He, Q., Wang, Z., Zheng, Z., Hu, H.: Spatial and temporal dual-attention for unsupervised person re-identification. IEEE Trans. ITS 25(2), 1953\u20131965 (2023)","journal-title":"IEEE Trans. ITS"},{"key":"14_CR14","doi-asserted-by":"publisher","first-page":"879","DOI":"10.1609\/aaai.v36i1.19970","volume":"36","author":"T He","year":"2022","unstructured":"He, T., Shen, L., Guo, Y., Ding, G., Guo, Z.: Secret: self-consistent pseudo label refinement for unsupervised domain adaptive person re-identification. AAAI 36, 879\u2013887 (2022)","journal-title":"AAAI"},{"key":"14_CR15","doi-asserted-by":"crossref","unstructured":"Huang, Y., Zhang, Z., Wu, Q., Zhong, Y., Wang, L.: Attribute-guided pedestrian retrieval: bridging person re-id with internal attribute variability. In: CVPR, pp. 17689\u201317699 (2024)","DOI":"10.1109\/CVPR52733.2024.01675"},{"key":"14_CR16","unstructured":"Lee, C.Y., Gallagher, P.W., Tu, Z.: Generalizing pooling functions in convolutional neural networks: mixed, gated, and tree. In: AISTATS, pp. 464\u2013472. PMLR (2016)"},{"key":"14_CR17","doi-asserted-by":"crossref","unstructured":"Lee, G., Lee, S., Kim, D., Shin, Y., Yoon, Y., Ham, B.: Camera-driven representation learning for unsupervised domain adaptive person re-identification. In: ICCV, pp. 11453\u201311462 (2023)","DOI":"10.1109\/ICCV51070.2023.01052"},{"key":"14_CR18","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, vol.\u00a033, pp. 8738\u20138745 (2019)","DOI":"10.1609\/aaai.v33i01.33018738"},{"key":"14_CR19","unstructured":"Zhang, L., Liu, F.: View confusion feature learning for person re-identification. In: ICCV, pp. 6639\u20136648 (2019)"},{"issue":"1","key":"14_CR20","doi-asserted-by":"publisher","DOI":"10.1049\/cvi2.70007","volume":"19","author":"Z Lu","year":"2025","unstructured":"Lu, Z., Sun, L., Lv, P., Hao, J., Tang, B., Chen, X.: A new large-scale dataset for marine vessel re-identification based on swin transformer network in ocean surveillance scenario. IET Comput. Vis. 19(1), e70007 (2025)","journal-title":"IET Comput. Vis."},{"key":"14_CR21","doi-asserted-by":"crossref","unstructured":"Luo, X., Jiang, M., Kong, J., Tao, X.: Hierarchical camera-aware contrast extension for unsupervised person re-identification. IEEE Trans. MM (2024)","DOI":"10.1109\/TMM.2024.3369904"},{"key":"14_CR22","doi-asserted-by":"crossref","unstructured":"Miao, Y., Deng, J., Ding, G., Han, J.: Confidence-guided centroids for unsupervised person re-identification. IEEE Trans. IFS (2024)","DOI":"10.1109\/TIFS.2024.3414310"},{"key":"14_CR23","doi-asserted-by":"crossref","unstructured":"Selvaraju, R.R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., Batra, D.: Grad-cam: visual explanations from deep networks via gradient-based localization. In: ICCV, pp. 618\u2013626 (2017)","DOI":"10.1109\/ICCV.2017.74"},{"key":"14_CR24","volume":"143","author":"W Sun","year":"2025","unstructured":"Sun, W., Guan, F., Zhang, X., Shen, X., Wang, K.: Ship re-identification in foggy weather: a two-branch network with dynamic feature enhancement and dual attention. Eng. Appl. AI 143, 109974 (2025)","journal-title":"Eng. Appl. AI"},{"key":"14_CR25","doi-asserted-by":"crossref","unstructured":"Tao, X., Kong, J., Jiang, M., Lu, M., Mian, A.: Unsupervised learning of intrinsic semantics with diffusion model for person re-identification. IEEE Trans. IP (2024)","DOI":"10.1109\/TIP.2024.3514360"},{"key":"14_CR26","doi-asserted-by":"crossref","unstructured":"Wang, D., Zhang, S.: Unsupervised person re-identification via multi-label classification. In: CVPR, pp. 10981\u201310990 (2020)","DOI":"10.1109\/CVPR42600.2020.01099"},{"key":"14_CR27","doi-asserted-by":"crossref","unstructured":"Wang, G., Yuan, Y., Chen, X., Li, J., Zhou, X.: Learning discriminative features with multiple granularities for person re-identification. In: ACM MM, pp. 274\u2013282 (2018)","DOI":"10.1145\/3240508.3240552"},{"key":"14_CR28","first-page":"3222","volume":"18","author":"H Wang","year":"2023","unstructured":"Wang, H., Yang, M., Liu, J., Zheng, W.S.: Pseudo-label noise prevention, suppression and softening for unsupervised person re-identification. IEEE Trans. IFS 18, 3222\u20133237 (2023)","journal-title":"IEEE Trans. IFS"},{"key":"14_CR29","doi-asserted-by":"publisher","first-page":"2764","DOI":"10.1609\/aaai.v35i4.16381","volume":"35","author":"M Wang","year":"2021","unstructured":"Wang, M., Lai, B., Huang, J., Gong, X., Hua, X.S.: Camera-aware proxies for unsupervised person re-identification. AAAI 35, 2764\u20132772 (2021)","journal-title":"AAAI"},{"key":"14_CR30","doi-asserted-by":"crossref","unstructured":"Wen, Z., Wu, J., Lv, Y., Wu, Q.: Cross-modality vessel re-identification with deep alignment decomposition network. IEEE Trans. MM (2024)","DOI":"10.1109\/TMM.2024.3406193"},{"key":"14_CR31","doi-asserted-by":"crossref","unstructured":"Xu, H., Huang, L., Chen, Y., Zhu, J., Zeng, H.: Unsupervised military-civilian cross-domain vessel re-identification using improved momentum contrast learning. In: NTCI, pp. 106\u2013110. IEEE (2024)","DOI":"10.1109\/NTCI64025.2024.10776541"},{"key":"14_CR32","doi-asserted-by":"crossref","unstructured":"Xuan, S., Zhang, S.: Intra-inter camera similarity for unsupervised person re-identification. In: CVPR, pp. 11926\u201311935 (2021)","DOI":"10.1109\/CVPR46437.2021.01175"},{"key":"14_CR33","first-page":"2309","volume":"32","author":"J Yin","year":"2023","unstructured":"Yin, J., Zhang, X., Ma, Z., Guo, J., Liu, Y.: A real-time memory updating strategy for unsupervised person re-identification. IEEE Trans. IP 32, 2309\u20132321 (2023)","journal-title":"IEEE Trans. IP"},{"key":"14_CR34","doi-asserted-by":"crossref","unstructured":"Yu, C., Liu, X., Zhu, J., Wang, Y., Zhang, P., Lu, H.: Climb-reid: a hybrid clip-mamba framework for person re-identification. In: AAAI, vol.\u00a039, pp. 9589\u20139597 (2025)","DOI":"10.1609\/aaai.v39i9.33039"},{"key":"14_CR35","doi-asserted-by":"crossref","unstructured":"Yu, D., Wang, H., Chen, P., Wei, Z.: Mixed pooling for convolutional neural networks. In RSKT, pp. 364\u2013375. Springer (2014)","DOI":"10.1007\/978-3-319-11740-9_34"},{"key":"14_CR36","volume":"125","author":"G Zeng","year":"2023","unstructured":"Zeng, G., Wang, R., Yu, W., Lin, A., Li, H., Shang, Y.: A transfer learning-based approach to maritime warships re-identification. Eng. Appl. AI 125, 106696 (2023)","journal-title":"Eng. Appl. AI"},{"issue":"4","key":"14_CR37","first-page":"1490","volume":"31","author":"L Zhang","year":"2020","unstructured":"Zhang, L., Liu, F., Zhang, D.: Adversarial view confusion feature learning for person re-identification. IEEE Trans. CSVT 31(4), 1490\u20131502 (2020)","journal-title":"IEEE Trans. CSVT"},{"key":"14_CR38","doi-asserted-by":"crossref","unstructured":"Zhang, Q., Yan, Y., Gao, L., Xu, C., Su, N., Feng, S.: A third-modality collaborative learning approach for visible-infrared vessel re-identification. IEEE J. Sel. Top. Earth Obs. Remote Sens. (2024)","DOI":"10.1109\/JSTARS.2024.3479423"},{"issue":"5","key":"14_CR39","first-page":"5406","volume":"24","author":"Q Zhang","year":"2023","unstructured":"Zhang, Q., Zhang, M., Liu, J., He, X., Song, R., Zhang, W.: Unsupervised maritime vessel re-identification with multi-level contrastive learning. IEEE Trans. ITS 24(5), 5406\u20135418 (2023)","journal-title":"IEEE Trans. ITS"},{"key":"14_CR40","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: CVPR, pp. 3436\u20133445 (2021)","DOI":"10.1109\/CVPR46437.2021.00344"},{"issue":"1","key":"14_CR41","doi-asserted-by":"publisher","first-page":"1589","DOI":"10.1038\/s41598-024-51258-6","volume":"14","author":"L Zhao","year":"2024","unstructured":"Zhao, L., Zhang, Z.: A improved pooling method for convolutional neural networks. Sci. Rep. 14(1), 1589 (2024)","journal-title":"Sci. Rep."},{"key":"14_CR42","doi-asserted-by":"crossref","unstructured":"Zheng, L., Shen, L., Tian, L., Wang, S., Wang, J., Tian, Q.: Scalable person re-identification: a benchmark. In: IEEE Int. Conf. Comput. Vis., pp. 1116\u20131124 (2015)","DOI":"10.1109\/ICCV.2015.133"},{"key":"14_CR43","doi-asserted-by":"crossref","unstructured":"Zheng, Y., et al.: Online pseudo label generation by hierarchical cluster dynamics for adaptive person re-identification. In: ICCV, pp. 8371\u20138381 (2021)","DOI":"10.1109\/ICCV48922.2021.00826"},{"key":"14_CR44","doi-asserted-by":"crossref","unstructured":"Zhong, Z., Zheng, L., Cao, D., Li, S.: Re-ranking person re-identification with k-reciprocal encoding. In: CVPR, pp. 1318\u20131327 (2017)","DOI":"10.1109\/CVPR.2017.389"},{"issue":"7","key":"14_CR45","first-page":"3275","volume":"27","author":"Y Zhou","year":"2018","unstructured":"Zhou, Y., Liu, L., Shao, L.: Vehicle re-identification by deep hidden multi-view inference. IEEE Trans. IP 27(7), 3275\u20133287 (2018)","journal-title":"IEEE Trans. IP"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-5693-9_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T21:22:34Z","timestamp":1768944154000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-5693-9_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819556922","9789819556939"],"references-count":45,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-5693-9_14","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"21 January 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chinese Conference on Pattern Recognition and Computer Vision  (PRCV)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shanghai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 October 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 October 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccprcv2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2025.prcv.cn\/index.asp","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}