{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T06:47:21Z","timestamp":1743058041873,"version":"3.40.3"},"publisher-location":"Cham","reference-count":56,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031730009"},{"type":"electronic","value":"9783031730016"}],"license":[{"start":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T00:00:00Z","timestamp":1732665600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T00:00:00Z","timestamp":1732665600000},"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":[[2025]]},"DOI":"10.1007\/978-3-031-73001-6_12","type":"book-chapter","created":{"date-parts":[[2024,11,26]],"date-time":"2024-11-26T10:24:19Z","timestamp":1732616659000},"page":"201-218","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Labeled Data Selection for\u00a0Category Discovery"],"prefix":"10.1007","author":[{"given":"Bingchen","family":"Zhao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nico","family":"Lang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Serge","family":"Belongie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Oisin Mac","family":"Aodha","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,11,27]]},"reference":[{"key":"12_CR1","unstructured":"Arthur, D., Vassilvitskii, S., et\u00a0al.: k-means++: the advantages of careful seeding. In: Symposium on Discrete Algorithms (2007)"},{"issue":"9","key":"12_CR2","doi-asserted-by":"publisher","first-page":"1790","DOI":"10.1109\/TPAMI.2015.2500224","volume":"38","author":"H Azizpour","year":"2015","unstructured":"Azizpour, H., Razavian, A.S., Sullivan, J., Maki, A., Carlsson, S.: Factors of transferability for a generic convnet representation. PAMI 38(9), 1790\u20131802 (2015)","journal-title":"PAMI"},{"key":"12_CR3","doi-asserted-by":"crossref","unstructured":"Bao, Y., et al.: An information-theoretic approach to transferability in task transfer learning. In: ICIP (2019)","DOI":"10.1109\/ICIP.2019.8803726"},{"key":"12_CR4","unstructured":"Bolya, D., Mittapalli, R., Hoffman, J.: Scalable diverse model selection for accessible transfer learning. In: NeurIPS (2021)"},{"key":"12_CR5","unstructured":"Cao, K., Brbi\u0107, M., Leskovec, J.: Open-world semi-supervised learning. In: ICLR (2022)"},{"key":"12_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1007\/978-3-030-01264-9_9","volume-title":"Computer Vision \u2013 ECCV 2018","author":"M Caron","year":"2018","unstructured":"Caron, M., Bojanowski, P., Joulin, A., Douze, M.: Deep clustering for unsupervised learning of visual features. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) Computer Vision \u2013 ECCV 2018. LNCS, vol. 11218, pp. 139\u2013156. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01264-9_9"},{"key":"12_CR7","unstructured":"Chi, H., et al.: Meta discovery: learning to discover novel classes given very limited data. In: ICLR (2022)"},{"key":"12_CR8","doi-asserted-by":"publisher","first-page":"604","DOI":"10.1007\/978-3-031-20080-9_35","volume-title":"ECCV 2022","author":"E Cole","year":"2022","unstructured":"Cole, E., et al.: On label granularity and object localization. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13670, pp. 604\u2013620. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-20080-9_35"},{"key":"12_CR9","doi-asserted-by":"crossref","unstructured":"Cui, Y., Song, Y., Sun, C., Howard, A., Belongie, S.: Large scale fine-grained categorization and domain-specific transfer learning. In: CVPR (2018)","DOI":"10.1109\/CVPR.2018.00432"},{"key":"12_CR10","unstructured":"Dehghani, M., et\u00a0al.: Scaling vision transformers to 22 billion parameters. In: ICML (2023)"},{"key":"12_CR11","unstructured":"Dosovitskiy, A., et\u00a0al.: An image is worth $$16\\times 16$$ words: transformers for image recognition at scale. In: ICLR (2021)"},{"key":"12_CR12","doi-asserted-by":"crossref","unstructured":"Du, R., Chang, D., Liang, K., Hospedales, T., Song, Y.Z., Ma, Z.: On-the-fly category discovery. In: CVPR (2023)","DOI":"10.1109\/CVPR52729.2023.01125"},{"key":"12_CR13","unstructured":"Fang, A., Jose, A.M., Jain, A., Schmidt, L., Toshev, A., Shankar, V.: Data filtering networks. In: ICLR (2024)"},{"key":"12_CR14","unstructured":"Fei, Y., Zhao, Z., Yang, S., Zhao, B.: XCon: learning with experts for fine-grained category discovery. In: BMVC (2022)"},{"key":"12_CR15","doi-asserted-by":"crossref","unstructured":"Fini, E., Sangineto, E., Lathuili\u00e8re, S., Zhong, Z., Nabi, M., Ricci, E.: A unified objective for novel class discovery. In: ICCV (2021)","DOI":"10.1109\/ICCV48922.2021.00915"},{"key":"12_CR16","doi-asserted-by":"crossref","unstructured":"Gidaris, S., Komodakis, N.: Dynamic few-shot visual learning without forgetting. In: CVPR (2018)","DOI":"10.1109\/CVPR.2018.00459"},{"key":"12_CR17","doi-asserted-by":"crossref","unstructured":"Guo, S., et al.: The imaterialist fashion attribute dataset. In: ICCV Workshops (2019)","DOI":"10.1109\/ICCVW.2019.00377"},{"key":"12_CR18","unstructured":"Han, K., Rebuffi, S.A., Ehrhardt, S., Vedaldi, A., Zisserman, A.: Automatically discovering and learning new visual categories with ranking statistics. In: ICLR (2020)"},{"issue":"10","key":"12_CR19","doi-asserted-by":"publisher","first-page":"6767","DOI":"10.1109\/TPAMI.2021.3091944","volume":"44","author":"K Han","year":"2021","unstructured":"Han, K., Rebuffi, S.A., Ehrhardt, S., Vedaldi, A., Zisserman, A.: AutoNovel: automatically discovering and learning novel visual categories. PAMI 44(10), 6767\u20136781 (2021)","journal-title":"PAMI"},{"key":"12_CR20","doi-asserted-by":"crossref","unstructured":"Han, K., Vedaldi, A., Zisserman, A.: Learning to discover novel visual categories via deep transfer clustering. In: ICCV (2019)","DOI":"10.1109\/ICCV.2019.00849"},{"key":"12_CR21","doi-asserted-by":"crossref","unstructured":"Ji, X., Henriques, J.F., Vedaldi, A.: Invariant information clustering for unsupervised image classification and segmentation. In: ICCV (2019)","DOI":"10.1109\/ICCV.2019.00996"},{"key":"12_CR22","unstructured":"Katharopoulos, A., Fleuret, F.: Not all samples are created equal: deep learning with importance sampling. In: ICML (2018)"},{"key":"12_CR23","unstructured":"Khosla, A., Jayadevaprakash, N., Yao, B., Fei-Fei, L.: Novel dataset for fine-grained image categorization. In: FGVC Workshop at CVPR (2011)"},{"key":"12_CR24","doi-asserted-by":"crossref","unstructured":"Kim, H., Suh, S., Kim, D., Jeong, D., Cho, H., Kim, J.: Proxy anchor-based unsupervised learning for continuous generalized category discovery. In: ICCV (2023)","DOI":"10.1109\/ICCV51070.2023.01530"},{"key":"12_CR25","doi-asserted-by":"crossref","unstructured":"Krause, J., Stark, M., Deng, J., Fei-Fei, L.: 3D object representations for fine-grained categorization. In: ICCV Workshops (2013)","DOI":"10.1109\/ICCVW.2013.77"},{"key":"12_CR26","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":"12_CR27","unstructured":"Loshchilov, I., Hutter, F.: Online batch selection for faster training of neural networks. In: ICLR Workshops (2016)"},{"key":"12_CR28","unstructured":"MacQueen, J.: Some methods for classification and analysis of multivariate observations. In: Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability (1967)"},{"key":"12_CR29","unstructured":"Maji, S., Rahtu, E., Kannala, J., Blaschko, M., Vedaldi, A.: Fine-grained visual classification of aircraft. arXiv:1306.5151 (2013)"},{"key":"12_CR30","unstructured":"Mindermann, S., et\u00a0al.: Prioritized training on points that are learnable, worth learning, and not yet learnt. In: ICML (2022)"},{"key":"12_CR31","unstructured":"Nguyen, C., Hassner, T., Seeger, M., Archambeau, C.: LEEP: a new measure to evaluate transferability of learned representations. In: ICML (2020)"},{"key":"12_CR32","unstructured":"Oquab, M., et\u00a0al.: DINOv2: learning robust visual features without supervision. TMLR (2024)"},{"key":"12_CR33","doi-asserted-by":"crossref","unstructured":"Pu, N., Zhong, Z., Sebe, N.: Dynamic conceptional contrastive learning for generalized category discovery. In: CVPR (2023)","DOI":"10.1109\/CVPR52729.2023.00732"},{"key":"12_CR34","unstructured":"Rastegar, S., Doughty, H., Snoek, C.: Learn to categorize or categorize to learn? Self-coding for generalized category discovery. In: NeurIPS (2023)"},{"key":"12_CR35","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s11263-015-0816-y","volume":"115","author":"O Russakovsky","year":"2015","unstructured":"Russakovsky, O., et al.: ImageNet large scale visual recognition challenge. IJCV 115, 211\u2013252 (2015)","journal-title":"IJCV"},{"key":"12_CR36","doi-asserted-by":"crossref","unstructured":"Shao, D., Zhao, Y., Dai, B., Lin, D.: FineGym: a hierarchical video dataset for fine-grained action understanding. In: CVPR (2020)","DOI":"10.1109\/CVPR42600.2020.00269"},{"key":"12_CR37","doi-asserted-by":"crossref","unstructured":"Sun, C., Shrivastava, A., Singh, S., Gupta, A.: Revisiting unreasonable effectiveness of data in deep learning era. In: ICCV (2017)","DOI":"10.1109\/ICCV.2017.97"},{"key":"12_CR38","unstructured":"Sun, Y., Shi, Z., Li, Y.: A graph-theoretic framework for understanding open-world semi-supervised learning. In: NeurIPS (2023)"},{"key":"12_CR39","unstructured":"Sun, Y., Shi, Z., Liang, Y., Li, Y.: When and how does known class help discover unknown ones? Provable understanding through spectral analysis. In: ICML (2023)"},{"key":"12_CR40","unstructured":"Tan, K.C., Liu, Y., Ambrose, B., Tulig, M., Belongie, S.: The herbarium challenge 2019 dataset. In: FGVC Workshop at CVPR (2019)"},{"key":"12_CR41","doi-asserted-by":"crossref","unstructured":"Tran, A.T., Nguyen, C.V., Hassner, T.: Transferability and hardness of supervised classification tasks. In: ICCV (2019)","DOI":"10.1109\/ICCV.2019.00148"},{"key":"12_CR42","doi-asserted-by":"crossref","unstructured":"Van\u00a0Horn, G., et al.: Building a bird recognition app and large scale dataset with citizen scientists: the fine print in fine-grained dataset collection. In: CVPR (2015)","DOI":"10.1109\/CVPR.2015.7298658"},{"key":"12_CR43","doi-asserted-by":"crossref","unstructured":"Van\u00a0Horn, G., Cole, E., Beery, S., Wilber, K., Belongie, S., Mac\u00a0Aodha, O.: Benchmarking representation learning for natural world collections. In: CVPR (2021)","DOI":"10.1109\/CVPR46437.2021.01269"},{"key":"12_CR44","doi-asserted-by":"crossref","unstructured":"Van\u00a0Horn, G., et al.: The inaturalist species classification and detection dataset. In: CVPR (2018)","DOI":"10.1109\/CVPR.2018.00914"},{"key":"12_CR45","doi-asserted-by":"crossref","unstructured":"Vaze, S., Han, K., Vedaldi, A., Zisserman, A.: Generalized category discovery. In: CVPR (2022)","DOI":"10.1109\/CVPR52688.2022.00734"},{"key":"12_CR46","unstructured":"Vaze, S., Han, K., Vedaldi, A., Zisserman, A.: Open-set recognition: a good closed-set classifier is all you need? In: ICLR (2022)"},{"key":"12_CR47","doi-asserted-by":"crossref","unstructured":"Vaze, S., Vedaldi, A., Zisserman, A.: No representation rules them all in category discovery. In: NeurIPS (2023)","DOI":"10.1109\/CVPR52688.2022.00734"},{"key":"12_CR48","unstructured":"Wah, C., Branson, S., Welinder, P., Perona, P., Belongie, S.: Caltech-UCSD Birds 200. Computation & neural systems technical report (2010)"},{"key":"12_CR49","doi-asserted-by":"crossref","unstructured":"Wen, X., Zhao, B., Qi, X.: Parametric classification for generalized category discovery: a baseline study. In: ICCV (2023)","DOI":"10.1109\/ICCV51070.2023.01521"},{"key":"12_CR50","unstructured":"Xu, H., et al.: Demystifying CLIP data. In: ICLR (2024)"},{"key":"12_CR51","doi-asserted-by":"crossref","unstructured":"Zhang, S., Khan, S., Shen, Z., Naseer, M., Chen, G., Khan, F.: PromptCAL: contrastive affinity learning via auxiliary prompts for generalized novel category discovery. In: CVPR (2023)","DOI":"10.1109\/CVPR52729.2023.00339"},{"key":"12_CR52","unstructured":"Zhang, X., et al.: Grow and merge: a unified framework for continuous categories discovery. In: NeurIPS (2022)"},{"key":"12_CR53","unstructured":"Zhao, B., Han, K.: Novel visual category discovery with dual ranking statistics and mutual knowledge distillation. In: NeurIPS (2021)"},{"key":"12_CR54","doi-asserted-by":"crossref","unstructured":"Zhao, B., Mac\u00a0Aodha, O.: Incremental generalized category discovery. In: ICCV (2023)","DOI":"10.1109\/ICCV51070.2023.01753"},{"key":"12_CR55","doi-asserted-by":"crossref","unstructured":"Zhao, B., Wen, X., Han, K.: Learning semi-supervised gaussian mixture models for generalized category discovery. In: ICCV (2023)","DOI":"10.1109\/ICCV51070.2023.01524"},{"key":"12_CR56","doi-asserted-by":"crossref","unstructured":"Zhong, Z., Fini, E., Roy, S., Luo, Z., Ricci, E., Sebe, N.: Neighborhood contrastive learning for novel class discovery. In: CVPR (2021)","DOI":"10.1109\/CVPR46437.2021.01072"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-73001-6_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,26]],"date-time":"2024-11-26T11:09:38Z","timestamp":1732619378000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-73001-6_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,27]]},"ISBN":["9783031730009","9783031730016"],"references-count":56,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-73001-6_12","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,11,27]]},"assertion":[{"value":"27 November 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Milan","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2024.ecva.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}