{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T20:59:04Z","timestamp":1768424344459,"version":"3.49.0"},"publisher-location":"Singapore","reference-count":25,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819549863","type":"print"},{"value":"9789819549870","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\/978-981-95-4987-0_17","type":"book-chapter","created":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T12:29:24Z","timestamp":1768393764000},"page":"234-247","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Generalized Few-Shot Semantic Segmentation Based on\u00a0Relevant Intrinsic Feature Enhancement"],"prefix":"10.1007","author":[{"given":"Lulu","family":"Jiang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yaozheng","family":"Xia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shaorong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,1,15]]},"reference":[{"key":"17_CR1","doi-asserted-by":"crossref","unstructured":"Tian, Z., et al.: Generalized few-shot semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11563\u201311572 (2022)","DOI":"10.1109\/CVPR52688.2022.01127"},{"key":"17_CR2","doi-asserted-by":"crossref","unstructured":"Shaban, A.,\u00a0Bansal, S.,\u00a0Liu, Z.,\u00a0Essa, I.,\u00a0BootsB.: One-shot learning for semantic segmentation. arXiv preprint arXiv:1709.03410 (2017)","DOI":"10.5244\/C.31.167"},{"key":"17_CR3","unstructured":"Rakelly, K.,\u00a0Shelhamer, E,.\u00a0Darrell, T.,\u00a0Efros, A.A., LevineS.: Few-shot segmentation propagation with guided networks. arXiv preprint arXiv:1806.07373 (2018)"},{"key":"17_CR4","doi-asserted-by":"crossref","unstructured":"Lu, Z.,\u00a0He, S.,\u00a0Zhu, X.,\u00a0Zhang, L.,\u00a0Song, Y.Z., XiangT.: Simpler is better: few-shot semantic segmentation with classifier weight transformer. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 8741\u20138750 (2021)","DOI":"10.1109\/ICCV48922.2021.00862"},{"issue":"11","key":"17_CR5","doi-asserted-by":"publisher","first-page":"6484","DOI":"10.1109\/TNNLS.2021.3081693","volume":"33","author":"X Zhang","year":"2021","unstructured":"Zhang, X., Wei, Y., Li, Z., Yan, C., Yang, Y.: Rich embedding features for one-shot semantic segmentation. IEEE Trans. Neural Netw. Learn. Syst. 33(11), 6484\u20136493 (2021)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"4","key":"17_CR6","first-page":"4","volume":"3","author":"N Dong","year":"2018","unstructured":"Dong, N., Xing, E.P.: Few-shot semantic segmentation with prototype learning. BMVC 3(4), 4 (2018)","journal-title":"BMVC"},{"key":"17_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"763","DOI":"10.1007\/978-3-030-58598-3_45","volume-title":"Computer Vision \u2013 ECCV 2020","author":"B Yang","year":"2020","unstructured":"Yang, B., Liu, C., Li, B., Jiao, J., Ye, Q.: Prototype mixture models for few-shot semantic segmentation. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12353, pp. 763\u2013778. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58598-3_45"},{"key":"17_CR8","doi-asserted-by":"crossref","unstructured":"Zhang, C.,\u00a0Lin, G.,\u00a0Liu, F.,\u00a0Guo, J.,\u00a0Wu, Q.,\u00a0Yao, R.: Pyramid graph networks with connection attentions for region-based one-shot semantic segmentation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 9587\u20139595 (2019)","DOI":"10.1109\/ICCV.2019.00968"},{"key":"17_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"730","DOI":"10.1007\/978-3-030-58601-0_43","volume-title":"Computer Vision \u2013 ECCV 2020","author":"H Wang","year":"2020","unstructured":"Wang, H., Zhang, X., Hu, Y., Yang, Y., Cao, X., Zhen, X.: Few-shot semantic segmentation with democratic attention networks. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12358, pp. 730\u2013746. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58601-0_43"},{"key":"17_CR10","doi-asserted-by":"crossref","unstructured":"Okazawa, A.: Interclass prototype relation for few-shot segmentation. In: European Conference on Computer Vision, pp. 362\u2013378. Springer (2022)","DOI":"10.1007\/978-3-031-19818-2_21"},{"key":"17_CR11","doi-asserted-by":"crossref","unstructured":"Fan, Q.,\u00a0Pei, W.,\u00a0Tai, Y.W., Tang, C.K.: Self-support few-shot semantic segmentation. In: European Conference on Computer Vision, pp. 701\u2013719 Springer (2022)","DOI":"10.1007\/978-3-031-19800-7_41"},{"key":"17_CR12","doi-asserted-by":"crossref","unstructured":"Wu, Z.,\u00a0Shi, X.,\u00a0Lin, G.,\u00a0Cai, J.: Learning meta-class memory for few-shot semantic segmentation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 517\u2013526 (2021)","DOI":"10.1109\/ICCV48922.2021.00056"},{"key":"17_CR13","doi-asserted-by":"crossref","unstructured":"Zhang, Y.,\u00a0et al.: Datasetgan: efficient labeled data factory with minimal human effort. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10145\u201310155 (2021)","DOI":"10.1109\/CVPR46437.2021.01001"},{"key":"17_CR14","doi-asserted-by":"crossref","unstructured":"Tritrong, N.,\u00a0Rewatbowornwong, P.,\u00a0Suwajanakorn, S.: Repurposing GANs for one-shot semantic part segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4475\u20134485 (2021)","DOI":"10.1109\/CVPR46437.2021.00445"},{"key":"17_CR15","doi-asserted-by":"crossref","unstructured":"Wang, H.,\u00a0Yang, Y.,\u00a0Cao, X.,\u00a0Zhen, X.,\u00a0Snoek, C.,\u00a0Shao, L.: Variational prototype inference for few-shot semantic segmentation. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 525\u2013534 (2021)","DOI":"10.1109\/WACV48630.2021.00057"},{"key":"17_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.109726","volume":"142","author":"H Sun","year":"2023","unstructured":"Sun, H., et al.: Attentional prototype inference for few-shot segmentation. Pattern Recogn. 142, 109726 (2023)","journal-title":"Pattern Recogn."},{"key":"17_CR17","doi-asserted-by":"crossref","unstructured":"Saha, O.,\u00a0Cheng, Z.,\u00a0Maji, S.: Ganorcon: are generative models useful for few-shot segmentation? In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9991\u201310000 (2022)","DOI":"10.1109\/CVPR52688.2022.00975"},{"key":"17_CR18","doi-asserted-by":"publisher","first-page":"3311","DOI":"10.1109\/TIP.2023.3282070","volume":"32","author":"Z Lu","year":"2023","unstructured":"Lu, Z., He, S., Li, D., Song, Y.-Z., Xiang, T.: Prediction calibration for generalized few-shot semantic segmentation. IEEE Trans. Image Process. 32, 3311\u20133323 (2023)","journal-title":"IEEE Trans. Image Process."},{"issue":"4","key":"17_CR19","doi-asserted-by":"publisher","first-page":"1277","DOI":"10.1007\/s11263-023-01939-y","volume":"132","author":"W Liu","year":"2024","unstructured":"Liu, W., et al.: Harmonizing base and novel classes: a class-contrastive approach for generalized few-shot segmentation. Int. J. Comput. Vision 132(4), 1277\u20131291 (2024)","journal-title":"Int. J. Comput. Vision"},{"key":"17_CR20","doi-asserted-by":"crossref","unstructured":"Liu, S.A., Zhang, Y.,\u00a0Qiu, Z.,\u00a0Xie, H.,\u00a0Zhang, Y.,\u00a0Yao, T.: Learning orthogonal prototypes for generalized few-shot semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11319\u201311328 (2023)","DOI":"10.1109\/CVPR52729.2023.01089"},{"key":"17_CR21","doi-asserted-by":"crossref","unstructured":"Hajimiri, S.,\u00a0Boudiaf, M.,\u00a0Ben\u00a0Ayed, I.,\u00a0Dolz, J.: A strong baseline for generalized few-shot semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11269\u201311278 (2023)","DOI":"10.1109\/CVPR52729.2023.01084"},{"key":"17_CR22","doi-asserted-by":"crossref","unstructured":"Huang, K.,\u00a0Wang, F.,\u00a0Xi, Y.,\u00a0Gao, Y.: Prototypical kernel learning and open-set foreground perception for generalized few-shot semantic segmentation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 19256\u201319265 (2023)","DOI":"10.1109\/ICCV51070.2023.01764"},{"key":"17_CR23","unstructured":"Sakai, T.,\u00a0Qiu, H.,\u00a0Katsuki, T.,\u00a0Kimura, D.,\u00a0Osogami, T.,\u00a0Inoue, T.: A surprisingly simple approach to generalized few-shot semantic segmentation. In: The Thirty-Eighth Annual Conference on Neural Information Processing Systems (2024)"},{"key":"17_CR24","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2022.105431","volume":"116","author":"Z Chang","year":"2022","unstructured":"Chang, Z., Lu, Y., Wang, X., Ran, X.: Mgnet: mutual-guidance network for few-shot semantic segmentation. Eng. Appl. Artif. Intell. 116, 105431 (2022)","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"9","key":"17_CR25","doi-asserted-by":"publisher","first-page":"10669","DOI":"10.1109\/TPAMI.2023.3265865","volume":"45","author":"C Lang","year":"2023","unstructured":"Lang, C., Cheng, G., Tu, B., Li, C., Han, J.: Base and meta: a new perspective on few-shot segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 45(9), 10669\u201310686 (2023)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"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\/978-981-95-4987-0_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T12:29:29Z","timestamp":1768393769000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-4987-0_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819549863","9789819549870"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-4987-0_17","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":"15 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"}}]}}