{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T19:18:46Z","timestamp":1743103126482,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":19,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819723867"},{"type":"electronic","value":"9789819723874"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-981-97-2387-4_24","type":"book-chapter","created":{"date-parts":[[2024,4,27]],"date-time":"2024-04-27T18:02:02Z","timestamp":1714240922000},"page":"358-372","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Multi-level Matching of\u00a0Natural Language-Based Vehicle Retrieval"],"prefix":"10.1007","author":[{"given":"Ying","family":"Liu","sequence":"first","affiliation":[]},{"given":"Zhongshuai","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Xiaochun","family":"Yang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,4,28]]},"reference":[{"key":"24_CR1","doi-asserted-by":"crossref","unstructured":"Bai, S., et al.: Connecting language and vision for natural language-based vehicle retrieval. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4034\u20134043 (2021)","DOI":"10.1109\/CVPRW53098.2021.00455"},{"key":"24_CR2","doi-asserted-by":"crossref","unstructured":"Bastani, F., et al.: MIRIS: fast object track queries in video. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1907\u20131921 (2020)","DOI":"10.1145\/3318464.3389692"},{"key":"24_CR3","unstructured":"Bochkovskiy, A., Wang, C.Y., Liao, H.Y.M.: YOLOv4: optimal speed and accuracy of object detection. arXiv preprint arXiv:2004.10934 (2020)"},{"key":"24_CR4","unstructured":"Feng, Q., Ablavsky, V., Sclaroff, S.: CityFlow-NL: tracking and retrieval of vehicles at city scale by natural language descriptions. arXiv preprint arXiv:2101.04741 (2021)"},{"issue":"4","key":"24_CR5","doi-asserted-by":"publisher","first-page":"1649","DOI":"10.1007\/s11280-022-01014-5","volume":"25","author":"G Gao","year":"2022","unstructured":"Gao, G., Shao, H., Wu, F., Yang, M., Yu, Y.: Leaning compact and representative features for cross-modality person re-identification. World Wide Web 25(4), 1649\u20131666 (2022)","journal-title":"World Wide Web"},{"key":"24_CR6","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"24_CR7","doi-asserted-by":"crossref","unstructured":"Hui, T., et al.: Collaborative spatial-temporal modeling for language-queried video actor segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4187\u20134196 (2021)","DOI":"10.1109\/CVPR46437.2021.00417"},{"key":"24_CR8","doi-asserted-by":"crossref","unstructured":"Kang, D., Emmons, J., Abuzaid, F., Bailis, P., Zaharia, M.: NoScope: optimizing neural network queries over video at scale. arXiv preprint arXiv:1703.02529 (2017)","DOI":"10.14778\/3137628.3137664"},{"key":"24_CR9","doi-asserted-by":"crossref","unstructured":"Kang, D., Guibas, J., Bailis, P.D., Hashimoto, T., Zaharia, M.: TASTI: semantic indexes for machine learning-based queries over unstructured data. In: Proceedings of the 2022 International Conference on Management of Data, pp. 1934\u20131947 (2022)","DOI":"10.1145\/3514221.3517897"},{"key":"24_CR10","doi-asserted-by":"crossref","unstructured":"Mai, S., Hu, H., Xing, S.: Modality to modality translation: an adversarial representation learning and graph fusion network for multimodal fusion. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a034, pp. 164\u2013172 (2020)","DOI":"10.1609\/aaai.v34i01.5347"},{"key":"24_CR11","doi-asserted-by":"crossref","unstructured":"Pennington, J., Socher, R., Manning, C.D.: GloVe: global vectors for word representation. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1532\u20131543 (2014)","DOI":"10.3115\/v1\/D14-1162"},{"key":"24_CR12","doi-asserted-by":"crossref","unstructured":"Sun, Z., Liu, X., Bi, X., Nie, X., Yin, Y.: DUN: dual-path temporal matching network for natural language-based vehicle retrieval. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4061\u20134067 (2021)","DOI":"10.1109\/CVPRW53098.2021.00458"},{"key":"24_CR13","doi-asserted-by":"publisher","first-page":"805","DOI":"10.1007\/s11280-021-00877-4","volume":"24","author":"F Wang","year":"2021","unstructured":"Wang, F., Xu, J., Liu, C., Zhou, R., Zhao, P.: On prediction of traffic flows in smart cities: a multitask deep learning based approach. World Wide Web 24, 805\u2013823 (2021)","journal-title":"World Wide Web"},{"key":"24_CR14","doi-asserted-by":"crossref","unstructured":"Wojke, N., Bewley, A., Paulus, D.: Simple online and realtime tracking with a deep association metric. In: 2017 IEEE International Conference on Image Processing (ICIP), pp. 3645\u20133649. IEEE (2017)","DOI":"10.1109\/ICIP.2017.8296962"},{"key":"24_CR15","doi-asserted-by":"crossref","unstructured":"Zhang, J., et al.: A multi-granularity retrieval system for natural language-based vehicle retrieval. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3216\u20133225 (2022)","DOI":"10.1109\/CVPRW56347.2022.00363"},{"key":"24_CR16","doi-asserted-by":"publisher","first-page":"563","DOI":"10.1007\/s11280-020-00859-y","volume":"24","author":"PF Zhang","year":"2021","unstructured":"Zhang, P.F., Luo, Y., Huang, Z., Xu, X.S., Song, J.: High-order nonlocal hashing for unsupervised cross-modal retrieval. World Wide Web 24, 563\u2013583 (2021)","journal-title":"World Wide Web"},{"key":"24_CR17","doi-asserted-by":"crossref","unstructured":"Zhao, C., et al.: Symmetric network with spatial relationship modeling for natural language-based vehicle retrieval. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3226\u20133233 (2022)","DOI":"10.1109\/CVPRW56347.2022.00364"},{"key":"24_CR18","doi-asserted-by":"crossref","unstructured":"Zhong, Z., Zheng, L., Cao, D., Li, S.: Re-ranking person re-identification with k-reciprocal encoding. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1318\u20131327 (2017)","DOI":"10.1109\/CVPR.2017.389"},{"key":"24_CR19","doi-asserted-by":"crossref","unstructured":"Zhu, X., Luo, Z., Fu, P., Ji, X.: VOC-ReID: vehicle re-identification based on vehicle-orientation-camera. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 602\u2013603 (2020)","DOI":"10.1109\/CVPRW50498.2020.00309"}],"container-title":["Lecture Notes in Computer Science","Web and Big Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-2387-4_24","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,27]],"date-time":"2024-04-27T18:08:22Z","timestamp":1714241302000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-2387-4_24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819723867","9789819723874"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-2387-4_24","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"28 April 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"APWeb-WAIM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Wuhan","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":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 October 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 October 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"apwebwaim2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.apweb-waim2023.com\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}