{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T17:28:01Z","timestamp":1787246881385,"version":"build-2736575974"},"publisher-location":"Singapore","reference-count":22,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819540969","type":"print"},{"value":"9789819540976","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T00:00:00Z","timestamp":1763078400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T00:00:00Z","timestamp":1763078400000},"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\/978-981-95-4097-6_21","type":"book-chapter","created":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T05:01:25Z","timestamp":1763010085000},"page":"306-320","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Hermite Curves and Multi-kernel Fusion for Large-Angle Curved and Rotated Text Spotting"],"prefix":"10.1007","author":[{"given":"Jiawhen","family":"Chen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bo","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tianyue","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunhua","family":"Deng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,11,14]]},"reference":[{"key":"21_CR1","doi-asserted-by":"crossref","unstructured":"Liu, Y., et al.: ABCNet v2: adaptive bezier-curve network for real-time end-to-end text spotting. IEEE Trans. Pattern Anal. Mach. Intell., 1 (2021)","DOI":"10.1109\/TPAMI.2021.3107437"},{"key":"21_CR2","doi-asserted-by":"crossref","unstructured":"Zhang, S.-X., et al.: Deep relational reasoning graph network for arbitrary shape text detection. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9699\u20139708 (2020)","DOI":"10.1109\/CVPR42600.2020.00972"},{"key":"21_CR3","doi-asserted-by":"publisher","unstructured":"Wang, P., Zhang, C., Qi, F., et al.: PGNet: Real-time arbitrarily-shaped text spotting with point gathering network (2021). https:\/\/doi.org\/10.48550\/arXiv.2104.05458","DOI":"10.48550\/arXiv.2104.05458"},{"key":"21_CR4","unstructured":"Farin, G.: Curves and Surfaces for CAGD: A Practical Guide, 5th edn. Academic Press (1990)"},{"issue":"2","key":"21_CR5","doi-asserted-by":"publisher","first-page":"532","DOI":"10.1109\/TPAMI.2019.2937086","volume":"43","author":"M Liao","year":"2021","unstructured":"Liao, M., Lyu, P., He, M., Yao, C., Wu, W., Bai, X.: Mask TextSpotter: an end-to-end trainable neural network for spottingtext with arbitrary shapes. IEEE Trans. Pattern Anal. Mach. Intell. 43(2), 532\u2013548 (2021)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"21_CR6","doi-asserted-by":"crossref","unstructured":"Sun, Y., Zhang, C., Huang, Z., Liu, J., Han, J., Ding, E.: TextNet: irregular text reading from images with an end-to-end trainable network. arXiv preprint arXiv:1812.09900 (2018)","DOI":"10.1007\/978-3-030-20893-6_6"},{"issue":"2","key":"21_CR7","doi-asserted-by":"publisher","first-page":"532","DOI":"10.1109\/TPAMI.2019.2937086","volume":"43","author":"M Liao","year":"2021","unstructured":"Liao, M., Lyu, P., He, M., Yao, C., Wu, W., Bai, X.: Mask TextSpotter: an end-to-end trainable neural network for spotting text with arbitrary shapes. IEEE Trans. Pattern Anal. Mach. Intell. 43(2), 532\u2013548 (2021)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"21_CR8","doi-asserted-by":"crossref","unstructured":"Zhu, Y., Chen, J., Liang, L., Kuang, Z., Jin, L., Zhang, W.: Fourier contour embedding for arbitrary-shaped text detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3123\u20133131 (2021)","DOI":"10.1109\/CVPR46437.2021.00314"},{"issue":"3","key":"21_CR9","first-page":"3241","volume":"37","author":"M Ye","year":"2023","unstructured":"Ye, M., Zhang, J., Zhao, S., Liu, J., Du, B., Tao, D.: DPText-DETR: towards better scene text detection with dynamic points in transformer. Proc. AAAI Conf. Artif. Intell. 37(3), 3241\u20133249 (2023)","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"21_CR10","unstructured":"Wang, W.: TPSNet: thin-plate-spline representation for arbitrary shape scene text detection (2021)"},{"key":"21_CR11","doi-asserted-by":"crossref","unstructured":"Chng, C.-K., et al.: ICDAR2019 robust reading challenge on arbitrary-shaped text (RRC-ArT). In: IAPR International Conference on Document Analysis and Recognition (2019)","DOI":"10.1109\/ICDAR.2019.00252"},{"key":"21_CR12","unstructured":"Burden, R.L., Faires, J.D.: Numerical Analysis, 9th edn.. Cengage Learning (2011)"},{"key":"21_CR13","unstructured":"Jaderberg, M., et al.: Spatial transformer networks. In: Proceedings of the Advances in Neural Information Processing System, pp. 2017\u20132025 (2015)"},{"key":"21_CR14","unstructured":"Shi, B., Bai, X., Yao, C.: An end-to-end trainable neural network for image-based sequence recognition and its application to scene text recognition (2015)"},{"key":"21_CR15","unstructured":"Kirillov, A., et al..: Segment anything. arXiv preprint arXiv:2304.02643 (2023)"},{"key":"21_CR16","unstructured":"Rosen, K.H.: Discrete Mathematics and Its Applications, 8th edn. McGraw-Hill Education (2018)"},{"key":"21_CR17","doi-asserted-by":"crossref","unstructured":"Chng, C.-K., Chan, C.-S.: Total-text: a comprehensive dataset for scene text detection and recognition. In: Proceedings of the IAPR International Conference on Document Analysis and Recognition, pp. 935\u2013942 (2017)","DOI":"10.1109\/ICDAR.2017.157"},{"key":"21_CR18","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1016\/j.patcog.2019.02.002","volume":"90","author":"Y Liu","year":"2019","unstructured":"Liu, Y., Jin, L., Zhang, S., Luo, C., Zhang, S.: Curved scene text detection via transverse and longitudinal sequence connection. Pattern Recogn. 90, 337\u2013345 (2019)","journal-title":"Pattern Recogn."},{"key":"21_CR19","unstructured":"Kingma, D., Ba, J.: Adam: a method for stochastic optimization. Comput. Sci. (2014)"},{"key":"21_CR20","doi-asserted-by":"crossref","unstructured":"Wang, Q., Liu, J., Zhu, Z., Deng, C.: MA-CharNet: multi-angle fusion character recognition network. PLoS ONE 17(8), e0272601 (2022)","DOI":"10.1371\/journal.pone.0272601"},{"key":"21_CR21","doi-asserted-by":"publisher","unstructured":"Huang, M., et al.: ESTextSpotter: towards better scene text spotting with explicit synergy in transformer. In: Proceedings of the 2023 IEEE\/CVF International Conference on Computer Vision (ICCV), Paris, France, pp. 19438\u201319448 (2023). https:\/\/doi.org\/10.1109\/ICCV51070.2023.01786","DOI":"10.1109\/ICCV51070.2023.01786"},{"key":"21_CR22","unstructured":"Liu, Y., Yang, B., Liu, Q., et al.: TextMonkey: an OCR-free large multimodal model for understanding document. arXiv preprint arXiv:2403.04473 (2024)"}],"container-title":["Communications in Computer and Information Science","Neural Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-4097-6_21","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T16:53:22Z","timestamp":1787244802000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-4097-6_21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,14]]},"ISBN":["9789819540969","9789819540976"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-4097-6_21","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,14]]},"assertion":[{"value":"14 November 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICONIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Neural Information Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Okinawa","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Japan","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":"20 November 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 November 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"32","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iconip2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/iconip2025.apnns.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}