{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T20:07:04Z","timestamp":1783973224882,"version":"3.55.0"},"publisher-location":"Singapore","reference-count":14,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819234912","type":"print"},{"value":"9789819234929","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T00:00:00Z","timestamp":1783987200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T00:00:00Z","timestamp":1783987200000},"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":[[2027]]},"DOI":"10.1007\/978-981-92-3492-9_14","type":"book-chapter","created":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T19:40:40Z","timestamp":1783971640000},"page":"166-178","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Few-Shot Semantic Segmentation via Latent Knowledge Mining and Dense Feature Alignment"],"prefix":"10.1007","author":[{"given":"Jingkai","family":"Wen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lan","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qingguo","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,14]]},"reference":[{"key":"14_CR1","doi-asserted-by":"crossref","unstructured":"Zhang, C., Lin, G., Liu, F., Shen, C., et al.: CANet: class-agnostic segmentation networks with iterative refinement and attentive few-shot learning. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7197\u20137206 (2019)","DOI":"10.1109\/CVPR.2019.00536"},{"issue":"9","key":"14_CR2","doi-asserted-by":"publisher","first-page":"3881","DOI":"10.1109\/TCYB.2020.2992433","volume":"50","author":"X Zhang","year":"2020","unstructured":"Zhang, X., Wei, Y., Yang, Y., Huang, T.S.: SG-One: similarity guidance network for one-shot semantic segmentation. IEEE Trans. Cybern. 50(9), 3855\u20133865 (2020)","journal-title":"IEEE Trans. Cybern."},{"key":"14_CR3","doi-asserted-by":"crossref","unstructured":"Nguyen, K., Todorovic, S.: Feature weighting and boosting for few-shot segmentation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 622\u2013631 (2019)","DOI":"10.1109\/ICCV.2019.00071"},{"issue":"2","key":"14_CR4","doi-asserted-by":"publisher","first-page":"1050","DOI":"10.1109\/TPAMI.2020.3013717","volume":"44","author":"Z Tian","year":"2022","unstructured":"Tian, Z., Zhao, H., Shu, M., Yang, Z., Li, R., Jia, J.: Prior guided feature enrichment network for few-shot segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 44(2), 1050\u20131065 (2022)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"14_CR5","doi-asserted-by":"publisher","unstructured":"Liu, Y., Zhang, X., Zhang, S., He, X.: Part-aware prototype network for few-shot semantic segmentation.  In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.M. (eds.) Computer Vision \u2013 ECCV 2020. ECCV 2020. LNCS, vol. 12354, pp. 142\u2013158. Springer, Cham  (2020). https:\/\/doi.org\/10.1007\/978-3-030-58545-7_9","DOI":"10.1007\/978-3-030-58545-7_9"},{"key":"14_CR6","doi-asserted-by":"crossref","unstructured":"Li, G., Jampani, V., Sevilla-Lara, L., Sun, D., Kim, J., Kim, J.: Adaptive prototype learning and allocation for few-shot segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8334\u20138343 (2021)","DOI":"10.1109\/CVPR46437.2021.00823"},{"key":"14_CR7","doi-asserted-by":"crossref","unstructured":"Min, J., Kang, D., Cho, M.: Hypercorrelation squeeze for few-shot segmentation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 6941\u20136952 (2021)","DOI":"10.1109\/ICCV48922.2021.00686"},{"key":"14_CR8","doi-asserted-by":"publisher","unstructured":"Shi, X., et al.: Dense cross-query and support attention weighted mask aggregation for few-shot segmentation. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) Computer Vision \u2013 ECCV 2022. ECCV 2022. LNCS, vol. 13680, pp. 151\u2013168. Springer, Cham.  (2022). https:\/\/doi.org\/10.1007\/978-3-031-20044-1_9","DOI":"10.1007\/978-3-031-20044-1_9"},{"key":"14_CR9","doi-asserted-by":"publisher","unstructured":"Fan, Q., Pei, W., Tai, Y.W., Tang, C.K.: Self-support few-shot semantic segmentation. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) Computer Vision \u2013 ECCV 2022. ECCV 2022. LNCS, vol.13679, pp. 701\u2013719. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19800-7_41","DOI":"10.1007\/978-3-031-19800-7_41"},{"key":"14_CR10","unstructured":"Zhang, G., Kang, G., Yi, Y., Wei, Y.: Few-shot segmentation via cycle-consistent transformer. In: Advances in Neural Information Processing Systems, vol. 34, pp. 21984\u201321996 (2021)"},{"key":"14_CR11","doi-asserted-by":"crossref","unstructured":"Liu, Y., Liu, N., Yao, X., Han, J.: Intermediate prototype mining transformer for few-shot semantic segmentation. In: Advances in Neural Information Processing Systems, vol. 35, pp. 38020\u201338031 (2022)","DOI":"10.52202\/068431-2755"},{"key":"14_CR12","doi-asserted-by":"crossref","unstructured":"Peng, B., et al.: Hierarchical dense correlation distillation for few-shot segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 23641\u201323651 (2023)","DOI":"10.1109\/CVPR52729.2023.02264"},{"key":"14_CR13","unstructured":"Dou, J., et al.: DNA: uncovering universal latent forgery knowledge, arXiv preprint arXiv:2601.22515 (2026)"},{"key":"14_CR14","doi-asserted-by":"crossref","unstructured":"Lang, C., Cheng, G., Tu, B., Han, J.: Learning what not to segment: a new perspective on few-shot segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8057\u20138067 (2022)","DOI":"10.1109\/CVPR52688.2022.00789"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-92-3492-9_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T19:40:42Z","timestamp":1783971642000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-92-3492-9_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,14]]},"ISBN":["9789819234912","9789819234929"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-981-92-3492-9_14","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,14]]},"assertion":[{"value":"14 July 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Toronto","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 July 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2026a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2026\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}