{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,3]],"date-time":"2026-11-03T03:56:59Z","timestamp":1793678219605,"version":"4.5.1"},"publisher-location":"Cham","reference-count":64,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031728969","type":"print"},{"value":"9783031728976","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,12,2]],"date-time":"2024-12-02T00:00:00Z","timestamp":1733097600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,2]],"date-time":"2024-12-02T00:00:00Z","timestamp":1733097600000},"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\/978-3-031-72897-6_25","type":"book-chapter","created":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T21:35:36Z","timestamp":1733088936000},"page":"440-458","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["SelEx: Self-expertise in\u00a0Fine-Grained Generalized Category Discovery"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4542-7388","authenticated-orcid":false,"given":"Sarah","family":"Rastegar","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9247-9439","authenticated-orcid":false,"given":"Mohammadreza","family":"Salehi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8533-4020","authenticated-orcid":false,"given":"Yuki M.","family":"Asano","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3670-3897","authenticated-orcid":false,"given":"Hazel","family":"Doughty","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9092-1556","authenticated-orcid":false,"given":"Cees G. M.","family":"Snoek","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,12,2]]},"reference":[{"key":"25_CR1","doi-asserted-by":"crossref","unstructured":"An, W., Tian, F., Zheng, Q., Ding, W., Wang, Q., Chen, P.: Generalized category discovery with decoupled prototypical network. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a037 (2023)","DOI":"10.1609\/aaai.v37i11.26475"},{"key":"25_CR2","unstructured":"Arthur, D., Vassilvitskii, S.: K-means++ the advantages of careful seeding. In: Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 1027\u20131035 (2007)"},{"key":"25_CR3","doi-asserted-by":"crossref","unstructured":"Banerjee, A., Kallooriyakath, L.S., Biswas, S.: Amend: adaptive margin and expanded neighborhood for efficient generalized category discovery. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 2101\u20132110 (2024)","DOI":"10.1109\/WACV57701.2024.00210"},{"key":"25_CR4","doi-asserted-by":"crossref","unstructured":"Boult, T.E., Cruz, S., Dhamija, A.R., Gunther, M., Henrydoss, J., Scheirer, W.J.: Learning and the unknown: surveying steps toward open world recognition. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a033, pp. 9801\u20139807 (2019)","DOI":"10.1609\/aaai.v33i01.33019801"},{"key":"25_CR5","unstructured":"Cao, K., Brbic, M., Leskovec, J.: Open-world semi-supervised learning. In: Proceedings of the International Conference on Learning Representations (2022)"},{"key":"25_CR6","doi-asserted-by":"crossref","unstructured":"Caron, M., Bojanowski, P., Joulin, A., Douze, M.: Deep clustering for unsupervised learning of visual features. In: Proceedings of the European Conference on Computer Vision, pp. 132\u2013149 (2018)","DOI":"10.1007\/978-3-030-01264-9_9"},{"key":"25_CR7","doi-asserted-by":"crossref","unstructured":"Caron, M., et al.: Emerging properties in self-supervised vision transformers. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 9650\u20139660 (2021)","DOI":"10.1109\/ICCV48922.2021.00951"},{"issue":"3","key":"25_CR8","doi-asserted-by":"publisher","first-page":"542","DOI":"10.1109\/TNN.2009.2015974","volume":"20","author":"O Chapelle","year":"2009","unstructured":"Chapelle, O., Scholkopf, B., Zien, A.: Semi-supervised learning. IEEE Trans. Neural Netw. 20(3), 542\u2013542 (2009)","journal-title":"IEEE Trans. Neural Netw."},{"key":"25_CR9","unstructured":"Chen, T., Kornblith, S., Norouzi, M., Hinton, G.: A simple framework for contrastive learning of visual representations. In: International Conference on Machine Learning, pp. 1597\u20131607. PMLR (2020)"},{"key":"25_CR10","doi-asserted-by":"crossref","unstructured":"Chiaroni, F., Dolz, J., Masud, Z.I., Mitiche, A., Ben\u00a0Ayed, I.: Parametric information maximization for generalized category discovery. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 1729\u20131739 (2023)","DOI":"10.1109\/ICCV51070.2023.00166"},{"key":"25_CR11","doi-asserted-by":"crossref","unstructured":"Choi, S., Kang, D., Cho, M.: Contrastive mean-shift learning for generalized category discovery. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2024)","DOI":"10.1109\/CVPR52733.2024.02179"},{"key":"25_CR12","doi-asserted-by":"crossref","unstructured":"Cole, E., Yang, X., Wilber, K., Mac\u00a0Aodha, O., Belongie, S.: When does contrastive visual representation learning work? In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 14755\u201314764 (2022)","DOI":"10.1109\/CVPR52688.2022.01434"},{"key":"25_CR13","doi-asserted-by":"crossref","unstructured":"Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L.: Imagenet: a large-scale hierarchical image database. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 248\u2013255 (2009)","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"25_CR14","doi-asserted-by":"crossref","unstructured":"Du, R., Chang, D., Liang, K., Hospedales, T., Song, Y.Z., Ma, Z.: On-the-fly category discovery. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11691\u201311700 (2023)","DOI":"10.1109\/CVPR52729.2023.01125"},{"key":"25_CR15","unstructured":"Fei, Y., Zhao, Z., Yang, S., Zhao, B.: Xcon: learning with experts for fine-grained category discovery. In: British Machine Vision Conference (2022)"},{"key":"25_CR16","doi-asserted-by":"crossref","unstructured":"Gao, F., Zhong, W., Cao, Z., Peng, X., Li, Z.: Opengcd: assisting open world recognition with generalized category discovery. arXiv preprint arXiv:2308.06926 (2023)","DOI":"10.2139\/ssrn.4903867"},{"key":"25_CR17","doi-asserted-by":"crossref","unstructured":"Guo, Y., et al.: Hcsc: hierarchical contrastive selective coding. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9706\u20139715 (2022)","DOI":"10.1109\/CVPR52688.2022.00948"},{"key":"25_CR18","unstructured":"Han, K., Rebuffi, S.A., Ehrhardt, S., Vedaldi, A., Zisserman, A.: Automatically discovering and learning new visual categories with ranking statistics. In: Proceedings of the International Conference on Learning Representations (2020)"},{"key":"25_CR19","unstructured":"Hao, S., Han, K., Wong, K.Y.K.: Cipr: an efficient framework with cross-instance positive relations for generalized category discovery. arXiv preprint arXiv:2304.06928 (2023)"},{"key":"25_CR20","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"25_CR21","doi-asserted-by":"crossref","unstructured":"Huang, G., Liu, Z., van\u00a0der Maaten, L., Weinberger, K.Q.: Densely connected convolutional networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4700\u20134708 (2017)","DOI":"10.1109\/CVPR.2017.243"},{"key":"25_CR22","doi-asserted-by":"crossref","unstructured":"Huynh, T., Kornblith, S., Walter, M.R., Maire, M., Khademi, M.: Boosting contrastive self-supervised learning with false negative cancellation. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 2785\u20132795 (2022)","DOI":"10.1109\/WACV51458.2022.00106"},{"issue":"1","key":"25_CR23","doi-asserted-by":"publisher","first-page":"2","DOI":"10.3390\/technologies9010002","volume":"9","author":"A Jaiswal","year":"2020","unstructured":"Jaiswal, A., Babu, A.R., Zadeh, M.Z., Banerjee, D., Makedon, F.: A survey on contrastive self-supervised learning. Technologies 9(1), 2 (2020)","journal-title":"Technologies"},{"key":"25_CR24","doi-asserted-by":"crossref","unstructured":"Khorasgani, S.H., Chen, Y., Shkurti, F.: Slic: self-supervised learning with iterative clustering for human action videos. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 16091\u201316101 (2022)","DOI":"10.1109\/CVPR52688.2022.01562"},{"key":"25_CR25","first-page":"18661","volume":"33","author":"P Khosla","year":"2020","unstructured":"Khosla, P., et al.: Supervised contrastive learning. Adv. Neural Inf. Process. Syst. 33, 18661\u201318673 (2020)","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"25_CR26","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: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 16688\u201316697 (2023)","DOI":"10.1109\/ICCV51070.2023.01530"},{"key":"25_CR27","doi-asserted-by":"crossref","unstructured":"Krause, J., Stark, M., Deng, J., Fei-Fei, L.: 3d object representations for fine-grained categorization. In: Proceedings of the IEEE International Conference on Computer Vision Workshops, pp. 554\u2013561 (2013)","DOI":"10.1109\/ICCVW.2013.77"},{"key":"25_CR28","unstructured":"Krizhevsky, A., Hinton, G.: Learning multiple layers of features from tiny images. Technical Report. University of Toronto, Toronto, Ontario (2009). https:\/\/www.cs.toronto.edu\/~kriz\/learning-features-2009-TR.pdf"},{"key":"25_CR29","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. Adv. Neural Inf. Process. Syst.\u00a025 (2012)"},{"key":"25_CR30","unstructured":"Li, J., Zhou, P., Xiong, C., Hoi, S.: Prototypical contrastive learning of unsupervised representations. In: International Conference on Learning Representations (2021)"},{"issue":"1","key":"25_CR31","first-page":"857","volume":"35","author":"X Liu","year":"2021","unstructured":"Liu, X., et al.: Self-supervised learning: generative or contrastive. IEEE Trans. Knowl. Data Eng. 35(1), 857\u2013876 (2021)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"25_CR32","doi-asserted-by":"crossref","unstructured":"Mahdavi, A., Carvalho, M.: A survey on open set recognition. In: 2021 IEEE Fourth International Conference on Artificial Intelligence and Knowledge Engineering (AIKE), pp. 37\u201344 (2021)","DOI":"10.1109\/AIKE52691.2021.00013"},{"key":"25_CR33","unstructured":"Maji, S., Rahtu, E., Kannala, J., Blaschko, M., Vedaldi, A.: Fine-grained visual classification of aircraft. arXiv preprint arXiv:1306.5151 (2013)"},{"key":"25_CR34","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1007\/978-3-319-46466-4_5","volume-title":"Computer Vision \u2013 ECCV 2016","author":"M Noroozi","year":"2016","unstructured":"Noroozi, M., Favaro, P.: Unsupervised learning of visual representations by solving jigsaw puzzles. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9910, pp. 69\u201384. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46466-4_5"},{"key":"25_CR35","unstructured":"Oliver, A., Odena, A., Raffel, C.A., Cubuk, E.D., Goodfellow, I.: Realistic evaluation of deep semi-supervised learning algorithms. Adv. Neural Inf. Process. Syst.\u00a031 (2018)"},{"key":"25_CR36","unstructured":"Oquab, M., et al.: DINOv2: learning robust visual features without supervision. Trans. Mach. Learn. Res. (2024)"},{"key":"25_CR37","doi-asserted-by":"crossref","unstructured":"Otholt, J., Meinel, C., Yang, H.: Guided cluster aggregation: a hierarchical approach to generalized category discovery. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 2618\u20132627 (2024)","DOI":"10.1109\/WACV57701.2024.00260"},{"key":"25_CR38","unstructured":"Ouali, Y., Hudelot, C., Tami, M.: An overview of deep semi-supervised learning. arXiv preprint arXiv:2006.05278 (2020)"},{"key":"25_CR39","doi-asserted-by":"crossref","unstructured":"Parkhi, O.M., Vedaldi, A., Zisserman, A., Jawahar, C.: Cats and dogs. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3498\u20133505 (2012)","DOI":"10.1109\/CVPR.2012.6248092"},{"key":"25_CR40","doi-asserted-by":"crossref","unstructured":"Pu, N., Zhong, Z., Sebe, N.: Dynamic conceptional contrastive learning for generalized category discovery. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2023)","DOI":"10.1109\/CVPR52729.2023.00732"},{"key":"25_CR41","unstructured":"Rastegar, S., Doughty, H., Snoek, C.G.M.: Learn to categorize or categorize to learn? self-coding for generalized category discovery. Adv. Neural Inf. Process. Syst. (2023)"},{"key":"25_CR42","doi-asserted-by":"crossref","unstructured":"Rebuffi, S.A., Ehrhardt, S., Han, K., Vedaldi, A., Zisserman, A.: Semi-supervised learning with scarce annotations. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 762\u2013763 (2020)","DOI":"10.1109\/CVPRW50498.2020.00389"},{"key":"25_CR43","unstructured":"Salehi, M., Mirzaei, H., Hendrycks, D., Li, Y., Rohban, M.H., Sabokrou, M.: A unified survey on anomaly, novelty, open-set, and out of-distribution detection: Solutions and future challenges. Trans. Mach. Learn. Res. (2022)"},{"key":"25_CR44","doi-asserted-by":"crossref","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. In: Proceedings of the International Conference on Learning Representations (2015)","DOI":"10.1109\/ICCV.2015.314"},{"key":"25_CR45","doi-asserted-by":"crossref","unstructured":"Szegedy, C., et al.: Going deeper with convolutions. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.\u00a01\u20139 (2015)","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"25_CR46","unstructured":"Tan, K.C., Liu, Y., Ambrose, B., Tulig, M., Belongie, S.: The herbarium challenge 2019 dataset. arXiv preprint arXiv:1906.05372 (2019)"},{"key":"25_CR47","unstructured":"Tan, Z., Zhang, C., Yang, X., Sun, J., Huang, K.: Revisiting mutual information maximization for generalized category discovery. arXiv preprint arXiv:2405.20711 (2024)"},{"key":"25_CR48","unstructured":"Troisemaine, C., Lemaire, V., Gosselin, S., Reiffers-Masson, A., Flocon-Cholet, J., Vaton, S.: Novel class discovery: an introduction and key concepts. arXiv preprint arXiv:2302.12028 (2023)"},{"key":"25_CR49","doi-asserted-by":"crossref","unstructured":"Vaze, S., Han, K., Vedaldi, A., Zisserman, A.: Generalized category discovery. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2022)","DOI":"10.1109\/CVPR52688.2022.00734"},{"key":"25_CR50","unstructured":"Vaze, S., Vedaldi, A., Zisserman, A.: No representation rules them all in category discovery. Adv. Neural Inf. Process. Syst. 37 (2023)"},{"key":"25_CR51","unstructured":"Wah, C., Branson, S., Welinder, P., Perona, P., Belongie, S.: The Caltech-UCSD birds-200-2011 dataset (2011)"},{"key":"25_CR52","unstructured":"Wang, H., Vaze, S., Han, K.: SPTNet: an efficient alternative framework for generalized category discovery with spatial prompt tuning. In: Proceedings of the International Conference on Learning Representations (2024)"},{"key":"25_CR53","unstructured":"Wang, Y., Wang, Y., Wu, Y., Zhao, B., Qian, X.: Beyond known clusters: probe new prototypes for efficient generalized class discovery. arXiv preprint arXiv:2404.08995 (2024)"},{"key":"25_CR54","unstructured":"Wang, Y., et al.: Discover and align taxonomic context priors for open-world semi-supervised learning. Adv. Neural Inf. Process. Syst. (2023)"},{"key":"25_CR55","doi-asserted-by":"crossref","unstructured":"Wen, X., Zhao, B., Qi, X.: Parametric classification for generalized category discovery: a baseline study. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 16590\u201316600 (2023)","DOI":"10.1109\/ICCV51070.2023.01521"},{"key":"25_CR56","doi-asserted-by":"crossref","unstructured":"Xiao, R., et al.: Targeted representation alignment for open-world semi-supervised learning. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 23072\u201323082 (2024)","DOI":"10.1109\/CVPR52733.2024.02177"},{"key":"25_CR57","doi-asserted-by":"crossref","unstructured":"Yang, M., Wang, L., Deng, C., Zhang, H.: Bootstrap your own prior: towards distribution-agnostic novel class discovery. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3459\u20133468 (2023)","DOI":"10.1109\/CVPR52729.2023.00337"},{"key":"25_CR58","doi-asserted-by":"publisher","first-page":"8934","DOI":"10.1109\/TKDE.2022.3220219","volume":"35","author":"X Yang","year":"2022","unstructured":"Yang, X., Song, Z., King, I., Xu, Z.: A survey on deep semi-supervised learning. IEEE Trans. Knowl. Data Eng. 35, 8934\u20138954 (2022)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"25_CR59","doi-asserted-by":"crossref","unstructured":"Zhai, X., Oliver, A., Kolesnikov, A., Beyer, L.: S4l: self-supervised semi-supervised learning. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 1476\u20131485 (2019)","DOI":"10.1109\/ICCV.2019.00156"},{"key":"25_CR60","unstructured":"Zhang, L., Qi, L., Yang, X., Qiao, H., Yang, M.H., Liu, Z.: Automatically discovering novel visual categories with self-supervised prototype learning. arXiv preprint arXiv:2208.00979 (2022)"},{"key":"25_CR61","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: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2023)","DOI":"10.1109\/CVPR52729.2023.00339"},{"key":"25_CR62","doi-asserted-by":"crossref","unstructured":"Zhang, S., Xu, R., Xiong, C., Ramaiah, C.: Use all the labels: a hierarchical multi-label contrastive learning framework. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 16660\u201316669 (2022)","DOI":"10.1109\/CVPR52688.2022.01616"},{"key":"25_CR63","doi-asserted-by":"crossref","unstructured":"Zhao, B., Wen, X., Han, K.: Learning semi-supervised gaussian mixture models for generalized category discovery. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (2023)","DOI":"10.1109\/ICCV51070.2023.01524"},{"key":"25_CR64","unstructured":"Zhu, F., Ma, S., Cheng, Z., Zhang, X.Y., Zhang, Z., Liu, C.L.: Open-world machine learning: a review and new outlooks. arXiv preprint arXiv:2403.01759 (2024)"}],"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\/978-3-031-72897-6_25","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T23:20:48Z","timestamp":1733095248000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-72897-6_25"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,2]]},"ISBN":["9783031728969","9783031728976"],"references-count":64,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-72897-6_25","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,2]]},"assertion":[{"value":"2 December 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"}}]}}