{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T12:12:50Z","timestamp":1769256770263,"version":"3.49.0"},"publisher-location":"Singapore","reference-count":29,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819557639","type":"print"},{"value":"9789819557646","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\/978-981-95-5764-6_15","type":"book-chapter","created":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T06:07:59Z","timestamp":1769148479000},"page":"215-229","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Adaptive Prototype Learning for\u00a0Weakly Supervised Semantic Segmentation"],"prefix":"10.1007","author":[{"given":"Jiaqi","family":"Han","sequence":"first","affiliation":[]},{"given":"Xuezhuan","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Lingling","family":"Li","sequence":"additional","affiliation":[]},{"given":"Chaoliang","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Suqiao","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,1,24]]},"reference":[{"key":"15_CR1","doi-asserted-by":"crossref","unstructured":"Lee, J., Kim, E., Yoon, S.: Anti-adversarially manipulated attributions for weakly and semi-supervised semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 4071\u20134080 (2021)","DOI":"10.1109\/CVPR46437.2021.00406"},{"key":"15_CR2","doi-asserted-by":"crossref","unstructured":"Xu, L., Ouyang, W., Bennamoun, M., Boussaid, F., Xu, D.: Multi-class token transformer for weakly supervised semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 4310\u20134319 (2022)","DOI":"10.1109\/CVPR52688.2022.00427"},{"issue":"4","key":"15_CR3","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1007\/s00138-024-01567-7","volume":"35","author":"A Englebert","year":"2024","unstructured":"Englebert, A., Cornu, O., De Vleeschouwer, C.: Poly-CAM: high resolution class activation map for convolutional neural networks. Mach. Vis. Appl. 35(4), 89 (2024)","journal-title":"Mach. Vis. Appl."},{"key":"15_CR4","doi-asserted-by":"crossref","unstructured":"Chen, Z., Wang, T., Wu, X., Hua, X.-S., Zhang, H., Sun, Q.: Class re-activation maps for weakly-supervised semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 969\u2013978 (2022)","DOI":"10.1109\/CVPR52688.2022.00104"},{"key":"15_CR5","doi-asserted-by":"crossref","unstructured":"Ru, L., Zhan, Y., Yu, B., Du, B.: Learning affinity from attention: end-to-end weakly-supervised semantic segmentation with transformers. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 16846\u201316855 (2022)","DOI":"10.1109\/CVPR52688.2022.01634"},{"issue":"1","key":"15_CR6","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1109\/TPAMI.2022.3152247","volume":"45","author":"K Han","year":"2022","unstructured":"Han, K., et al.: A survey on Vision Transformer. IEEE Trans. Pattern Anal. Mach. Intell. 45(1), 87\u2013110 (2022)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"15_CR7","doi-asserted-by":"crossref","unstructured":"Chen, L., Lei, C., Li, R., Li, S., Zhang, Z., Zhang, L.: FPR: false positive rectification for weakly supervised semantic segmentation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 1108\u20131118 (2023)","DOI":"10.1109\/ICCV51070.2023.00108"},{"key":"15_CR8","doi-asserted-by":"crossref","unstructured":"Tang, F., Xu, Z., Qu, Z., Feng, W., Jiang, X., Ge, Z.: Hunting attributes: context prototype-aware learning for weakly supervised semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3324\u20133334 (2024)","DOI":"10.1109\/CVPR52733.2024.00320"},{"key":"15_CR9","doi-asserted-by":"crossref","unstructured":"Chen, Q., Yang, L., Lai, J.-H., Xie, X.: Self-supervised image-specific prototype exploration for weakly supervised semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4288\u20134298 (2022)","DOI":"10.1109\/CVPR52688.2022.00425"},{"key":"15_CR10","doi-asserted-by":"crossref","unstructured":"Du, Y., Fu, Z., Liu, Q., Wang, Y.: Weakly supervised semantic segmentation by pixel-to-prototype contrast. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4320\u20134329 (2022)","DOI":"10.1109\/CVPR52688.2022.00428"},{"key":"15_CR11","doi-asserted-by":"crossref","unstructured":"Chen, Z., Sun, Q.: Extracting class activation maps from non-discriminative features as well. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3135\u20133144 (2023)","DOI":"10.1109\/CVPR52729.2023.00306"},{"key":"15_CR12","doi-asserted-by":"crossref","unstructured":"Zhao, X., Yang, Z., Dai, T., Zhang, B., Xiao, J.: PSDPM: prototype-based secondary discriminative pixels mining for weakly supervised semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3437\u20133446 (2024)","DOI":"10.1109\/CVPR52733.2024.00330"},{"key":"15_CR13","doi-asserted-by":"crossref","unstructured":"Xie, J., Xiang, J., Chen, J., Hou, X., Zhao, X., Shen, L.: Contrastive learning of class-agnostic activation map for weakly supervised object localization and semantic segmentation. arXiv preprint arXiv:2203.13505 (2022)","DOI":"10.1109\/CVPR52688.2022.00106"},{"key":"15_CR14","doi-asserted-by":"crossref","unstructured":"Zhou, T., Zhang, M., Zhao, F., Li, J.: Regional semantic contrast and aggregation for weakly supervised semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4299\u20134309 (2022)","DOI":"10.1109\/CVPR52688.2022.00426"},{"key":"15_CR15","doi-asserted-by":"crossref","unstructured":"Ru, L., Zheng, H., Zhan, Y., Du, B.: Token contrast for weakly-supervised semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3093\u20133102 (2023)","DOI":"10.1109\/CVPR52729.2023.00302"},{"key":"15_CR16","doi-asserted-by":"crossref","unstructured":"Wu, F., He, J., Yin, Y., Hao, Y., Huang, G., Cheng, L.: Masked collaborative contrast for weakly supervised semantic segmentation. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 862\u2013871 (2024)","DOI":"10.1109\/WACV57701.2024.00091"},{"key":"15_CR17","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1007\/s11263-009-0275-4","volume":"88","author":"M Everingham","year":"2010","unstructured":"Everingham, M., Van Gool, L., Williams, C.K.I., Winn, J., Zisserman, A.: The pascal visual object classes (VOC) challenge. Int. J. Comput. Vision 88, 303\u2013338 (2010)","journal-title":"Int. J. Comput. Vision"},{"key":"15_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"740","DOI":"10.1007\/978-3-319-10602-1_48","volume-title":"Computer Vision \u2013 ECCV 2014","author":"T-Y Lin","year":"2014","unstructured":"Lin, T.-Y., et al.: Microsoft COCO: common objects in context. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8693, pp. 740\u2013755. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10602-1_48"},{"key":"15_CR19","doi-asserted-by":"crossref","unstructured":"Hariharan, B., Arbel\u00e1ez, P., Bourdev, L., Maji, S., Malik, J.: Semantic contours from inverse detectors. In: 2011 International Conference on Computer Vision, pp. 991\u2013998. IEEE, (2011)","DOI":"10.1109\/ICCV.2011.6126343"},{"key":"15_CR20","doi-asserted-by":"crossref","unstructured":"Lin, Y., et al.: Clip is also an efficient segmenter: a text-driven approach for weakly supervised semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 15305\u201315314 (2023)","DOI":"10.1109\/CVPR52729.2023.01469"},{"issue":"4","key":"15_CR21","doi-asserted-by":"publisher","first-page":"1127","DOI":"10.1007\/s11263-022-01586-9","volume":"130","author":"L Ru","year":"2022","unstructured":"Ru, L., Du, B., Zhan, Y., Wu, C.: Weakly-supervised semantic segmentation with visual words learning and hybrid pooling. Int. J. Comput. Vision 130(4), 1127\u20131144 (2022)","journal-title":"Int. J. Comput. Vision"},{"key":"15_CR22","doi-asserted-by":"crossref","unstructured":"Lee, J., Oh, S.J., Yun, S., Choe, J., Kim, E., Yoon, S.: Weakly supervised semantic segmentation using out-of-distribution data. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 16897\u201316906 (2022)","DOI":"10.1109\/CVPR52688.2022.01639"},{"key":"15_CR23","unstructured":"Li, J., Jie, Z., Wang, X., Wei, X., Ma, L.: Expansion and shrinkage of localization for weakly-supervised semantic segmentation. In: Advances in Neural Information Processing Systems, vol. 35, pp. 16037\u201316051 (2022)"},{"key":"15_CR24","doi-asserted-by":"crossref","unstructured":"Cheng, Z., et al.: Out-of-candidate rectification for weakly supervised semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 23673\u201323684 (2023)","DOI":"10.1109\/CVPR52729.2023.02267"},{"key":"15_CR25","doi-asserted-by":"crossref","unstructured":"Kweon, H., Yoon, S.-H., Yoon, K.-J.: Weakly supervised semantic segmentation via adversarial learning of classifier and reconstructor. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11329\u201311339 (2023)","DOI":"10.1109\/CVPR52729.2023.01090"},{"key":"15_CR26","doi-asserted-by":"publisher","first-page":"2960","DOI":"10.1109\/TIP.2023.3275913","volume":"32","author":"T Chen","year":"2023","unstructured":"Chen, T., Yao, Y., Tang, J.: Multi-granularity denoising and bidirectional alignment for weakly supervised semantic segmentation. IEEE Trans. Image Process. 32, 2960\u20132971 (2023)","journal-title":"IEEE Trans. Image Process."},{"issue":"5","key":"15_CR27","doi-asserted-by":"publisher","first-page":"1181","DOI":"10.1007\/s11263-022-01590-z","volume":"130","author":"J Pan","year":"2022","unstructured":"Pan, J., et al.: Learning self-supervised low-rank network for single-stage weakly and semi-supervised semantic segmentation. Int. J. Comput. Vision 130(5), 1181\u20131195 (2022)","journal-title":"Int. J. Comput. Vision"},{"key":"15_CR28","doi-asserted-by":"crossref","unstructured":"Xu, R., Wang, C., Sun, J., Xu, S., Meng, W., Zhang, X.: Self correspondence distillation for end-to-end weakly-supervised semantic segmentation. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 37, no. 3, pp. 3045\u20133053 (2023)","DOI":"10.1609\/aaai.v37i3.25408"},{"key":"15_CR29","doi-asserted-by":"crossref","unstructured":"Shao, X., Han, J., Li, L., Zhao, X., Yan, J.: CPEWS: contextual prototype-based end-to-end weakly supervised semantic segmentation. Comput. Mater. Continua 83(1) (2025)","DOI":"10.32604\/cmc.2025.060295"}],"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\/978-981-95-5764-6_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T06:08:05Z","timestamp":1769148485000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-5764-6_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819557639","9789819557646"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-5764-6_15","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":"24 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"}}]}}