{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T17:42:35Z","timestamp":1743097355811,"version":"3.40.3"},"publisher-location":"Cham","reference-count":50,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031734632"},{"type":"electronic","value":"9783031734649"}],"license":[{"start":{"date-parts":[[2024,12,4]],"date-time":"2024-12-04T00:00:00Z","timestamp":1733270400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,4]],"date-time":"2024-12-04T00:00:00Z","timestamp":1733270400000},"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\/978-3-031-73464-9_6","type":"book-chapter","created":{"date-parts":[[2024,12,3]],"date-time":"2024-12-03T09:39:18Z","timestamp":1733218758000},"page":"87-104","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["3D Weakly Supervised Semantic Segmentation with\u00a02D Vision-Language Guidance"],"prefix":"10.1007","author":[{"given":"Xiaoxu","family":"Xu","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8701-7689","authenticated-orcid":false,"given":"Yitian","family":"Yuan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8746-4566","authenticated-orcid":false,"given":"Jinlong","family":"Li","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6067-8188","authenticated-orcid":false,"given":"Qiudan","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3038-5891","authenticated-orcid":false,"given":"Zequn","family":"Jie","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7331-6132","authenticated-orcid":false,"given":"Lin","family":"Ma","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2077-1246","authenticated-orcid":false,"given":"Hao","family":"Tang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6597-7248","authenticated-orcid":false,"given":"Nicu","family":"Sebe","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2948-6468","authenticated-orcid":false,"given":"Xu","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,12,4]]},"reference":[{"issue":"4","key":"6_CR1","doi-asserted-by":"publisher","first-page":"5432","DOI":"10.1109\/LRA.2020.3007440","volume":"5","author":"I Alonso","year":"2020","unstructured":"Alonso, I., Riazuelo, L., Montesano, L., Murillo, A.C.: 3D-mininet: learning a 2D representation from point clouds for fast and efficient 3D lidar semantic segmentation. IEEE Robot. Autom. Lett. 5(4), 5432\u20135439 (2020)","journal-title":"IEEE Robot. Autom. Lett."},{"key":"6_CR2","doi-asserted-by":"crossref","unstructured":"Ando, A., Gidaris, S., Bursuc, A., Puy, G., Boulch, A., Marlet, R.: Rangevit: towards vision transformers for 3D semantic segmentation in autonomous driving. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5240\u20135250 (2023)","DOI":"10.1109\/CVPR52729.2023.00507"},{"key":"6_CR3","doi-asserted-by":"crossref","unstructured":"Armeni, I., et al.: 3D semantic parsing of large-scale indoor spaces. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1534\u20131543 (2016)","DOI":"10.1109\/CVPR.2016.170"},{"key":"6_CR4","unstructured":"Bucher, M., Vu, T.H., Cord, M., P\u00e9rez, P.: Zero-shot semantic segmentation. In: Advances in Neural Information Processing Systems, vol. 32 (2019)"},{"key":"6_CR5","doi-asserted-by":"crossref","unstructured":"Cardace, A., Ramirez, P.Z., Salti, S., Di\u00a0Stefano, L.: Exploiting the complementarity of 2D and 3D networks to address domain-shift in 3D semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 98\u2013109 (2023)","DOI":"10.1109\/CVPRW59228.2023.00015"},{"key":"6_CR6","doi-asserted-by":"crossref","unstructured":"Chen, J., et al.: Exploring open-vocabulary semantic segmentation from clip vision encoder distillation only. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 699\u2013710 (2023)","DOI":"10.1109\/ICCV51070.2023.00071"},{"key":"6_CR7","unstructured":"Chen, R., et al.: Towards label-free scene understanding by vision foundation models. In: Advances in Neural Information Processing Systems, vol. 36 (2024)"},{"key":"6_CR8","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"681","DOI":"10.1007\/978-3-031-19821-2_39","volume-title":"ECCV 2022","author":"J Chibane","year":"2022","unstructured":"Chibane, J., Engelmann, F., Anh Tran, T., Pons-Moll, G.: Box2Mask: weakly supervised 3D semantic instance segmentation using bounding boxes. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13691, pp. 681\u2013699. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19821-2_39"},{"key":"6_CR9","doi-asserted-by":"crossref","unstructured":"Choy, C., Gwak, J., Savarese, S.: 4D spatio-temporal convnets: minkowski convolutional neural networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3075\u20133084 (2019)","DOI":"10.1109\/CVPR.2019.00319"},{"key":"6_CR10","doi-asserted-by":"crossref","unstructured":"Dai, A., Chang, A.X., Savva, M., Halber, M., Funkhouser, T., Nie\u00dfner, M.: Scannet: richly-annotated 3d reconstructions of indoor scenes. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5828\u20135839 (2017)","DOI":"10.1109\/CVPR.2017.261"},{"key":"6_CR11","doi-asserted-by":"crossref","unstructured":"Genova, K., et al.: Learning 3D semantic segmentation with only 2D image supervision. In: 2021 International Conference on 3D Vision (3DV), pp. 361\u2013372 (2021)","DOI":"10.1109\/3DV53792.2021.00046"},{"key":"6_CR12","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"540","DOI":"10.1007\/978-3-031-20059-5_31","volume-title":"ECCV 2022","author":"G Ghiasi","year":"2022","unstructured":"Ghiasi, G., Gu, X., Cui, Y., Lin, T.Y.: Scaling open-vocabulary image segmentation with image-level labels. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13696, pp. 540\u2013557. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-20059-5_31"},{"key":"6_CR13","doi-asserted-by":"crossref","unstructured":"Hegde, D., Valanarasu, J.M.J., Patel, V.: Clip goes 3D: leveraging prompt tuning for language grounded 3D recognition. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 2028\u20132038 (2023)","DOI":"10.1109\/ICCVW60793.2023.00217"},{"key":"6_CR14","doi-asserted-by":"crossref","unstructured":"Hou, J., Xie, S., Graham, B., Dai, A., Nie\u00dfner, M.: Pri3D: can 3D priors help 2D representation learning? In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 5693\u20135702 (2021)","DOI":"10.1109\/ICCV48922.2021.00564"},{"key":"6_CR15","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1007\/978-3-031-19812-0_35","volume-title":"ECCV 2022","author":"Q Hu","year":"2022","unstructured":"Hu, Q., et al.: SQN: weakly-supervised semantic segmentation of large-scale 3D point clouds. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13687, pp. 600\u2013619. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19812-0_35"},{"key":"6_CR16","doi-asserted-by":"crossref","unstructured":"Hu, Q., et al.: Randla-net: efficient semantic segmentation of large-scale point clouds. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11108\u201311117 (2020)","DOI":"10.1109\/CVPR42600.2020.01112"},{"key":"6_CR17","doi-asserted-by":"crossref","unstructured":"Hu, W., Zhao, H., Jiang, L., Jia, J., Wong, T.T.: Bidirectional projection network for cross dimension scene understanding. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 14373\u201314382 (2021)","DOI":"10.1109\/CVPR46437.2021.01414"},{"key":"6_CR18","unstructured":"Kweon, H., Yoon, K.J.: Joint learning of 2D\u20133D weakly supervised semantic segmentation. In: Advances in Neural Information Processing Systems, vol. 35, pp. 30499\u201330511 (2022)"},{"key":"6_CR19","doi-asserted-by":"crossref","unstructured":"Lahoud, J., Ghanem, B.: 2D-driven 3D object detection in RGB-D images. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4622\u20134630 (2017)","DOI":"10.1109\/ICCV.2017.495"},{"key":"6_CR20","doi-asserted-by":"crossref","unstructured":"Li, J., Dai, H., Han, H., Ding, Y.: Mseg3D: multi-modal 3d semantic segmentation for autonomous driving. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 21694\u201321704 (2023)","DOI":"10.1109\/CVPR52729.2023.02078"},{"key":"6_CR21","unstructured":"Li, J., Jie, Z., Ricci, E., Ma, L., Sebe, N.: Enhancing robustness of vision-language models through orthogonality learning and cross-regularization (2024). https:\/\/arxiv.org\/abs\/2407.08374"},{"key":"6_CR22","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.\u00a035, pp. 16037\u201316051 (2022)"},{"key":"6_CR23","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2023.126821","volume":"561","author":"J Li","year":"2023","unstructured":"Li, J., Jie, Z., Wang, X., Zhou, Y., Ma, L., Jiang, J.: Weakly supervised semantic segmentation via self-supervised destruction learning. Neurocomputing 561, 126821 (2023)","journal-title":"Neurocomputing"},{"key":"6_CR24","doi-asserted-by":"publisher","first-page":"1686","DOI":"10.1109\/TMM.2022.3152388","volume":"25","author":"J Li","year":"2022","unstructured":"Li, J., Jie, Z., Wang, X., Zhou, Y., Wei, X., Ma, L.: Weakly supervised semantic segmentation via progressive patch learning. IEEE Trans. Multimed. 25, 1686\u20131699 (2022)","journal-title":"IEEE Trans. Multimed."},{"key":"6_CR25","doi-asserted-by":"crossref","unstructured":"Liang, F., et al.: Open-vocabulary semantic segmentation with mask-adapted clip. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7061\u20137070 (2023)","DOI":"10.1109\/CVPR52729.2023.00682"},{"key":"6_CR26","doi-asserted-by":"crossref","unstructured":"Qi, C.R., Liu, W., Wu, C., Su, H., Guibas, L.J.: Frustum pointnets for 3D object detection from RGB-D data. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 918\u2013927 (2018)","DOI":"10.1109\/CVPR.2018.00102"},{"key":"6_CR27","unstructured":"Qi, C.R., Su, H., Mo, K., Guibas, L.J.: Pointnet: deep learning on point sets for 3D classification and segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 652\u2013660 (2017)"},{"key":"6_CR28","unstructured":"Qi, C.R., Yi, L., Su, H., Guibas, L.J.: Pointnet++: deep hierarchical feature learning on point sets in a metric space. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"key":"6_CR29","unstructured":"Qian, G., et al.: Pointnext: revisiting pointnet++ with improved training and scaling strategies. In: Advances in Neural Information Processing Systems, vol. 35, pp. 23192\u201323204 (2022)"},{"key":"6_CR30","unstructured":"Radford, A., et\u00a0al.: Learning transferable visual models from natural language supervision. In: International Conference on Machine Learning, pp. 8748\u20138763 (2021)"},{"key":"6_CR31","doi-asserted-by":"crossref","unstructured":"Ren, Z., Misra, I., Schwing, A.G., Girdhar, R.: 3D spatial recognition without spatially labeled 3D. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 13204\u201313213 (2021)","DOI":"10.1109\/CVPR46437.2021.01300"},{"key":"6_CR32","doi-asserted-by":"crossref","unstructured":"Robert, D., Vallet, B., Landrieu, L.: Learning multi-view aggregation in the wild for large-scale 3D semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5575\u20135584 (2022)","DOI":"10.1109\/CVPR52688.2022.00549"},{"key":"6_CR33","doi-asserted-by":"crossref","unstructured":"Tatarchenko, M., Park, J., Koltun, V., Zhou, Q.Y.: Tangent convolutions for dense prediction in 3D. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3887\u20133896 (2018)","DOI":"10.1109\/CVPR.2018.00409"},{"key":"6_CR34","doi-asserted-by":"crossref","unstructured":"Thomas, H., Qi, C.R., Deschaud, J.E., Marcotegui, B., Goulette, F., Guibas, L.J.: KPConv: flexible and deformable convolution for point clouds. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 6411\u20136420 (2019)","DOI":"10.1109\/ICCV.2019.00651"},{"key":"6_CR35","doi-asserted-by":"crossref","unstructured":"Wang, Z., Rao, Y., Yu, X., Zhou, J., Lu, J.: Semaffinet: semantic-affine transformation for point cloud segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11819\u201311829 (2022)","DOI":"10.1109\/CVPR52688.2022.01152"},{"key":"6_CR36","doi-asserted-by":"crossref","unstructured":"Wei, J., Lin, G., Yap, K.H., Hung, T.Y., Xie, L.: Multi-path region mining for weakly supervised 3D semantic segmentation on point clouds. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4384\u20134393 (2020)","DOI":"10.1109\/CVPR42600.2020.00444"},{"key":"6_CR37","doi-asserted-by":"crossref","unstructured":"Xian, Y., Choudhury, S., He, Y., Schiele, B., Akata, Z.: Semantic projection network for zero-and few-label semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8256\u20138265 (2019)","DOI":"10.1109\/CVPR.2019.00845"},{"key":"6_CR38","doi-asserted-by":"crossref","unstructured":"Xu, D., Anguelov, D., Jain, A.: Pointfusion: deep sensor fusion for 3D bounding box estimation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 244\u2013253 (2018)","DOI":"10.1109\/CVPR.2018.00033"},{"key":"6_CR39","doi-asserted-by":"crossref","unstructured":"Xu, J., et al.: Learning open-vocabulary semantic segmentation models from natural language supervision. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2935\u20132944 (2023)","DOI":"10.1109\/CVPR52729.2023.00287"},{"key":"6_CR40","doi-asserted-by":"crossref","unstructured":"Xu, M., Zhang, Z., Wei, F., Hu, H., Bai, X.: Side adapter network for open-vocabulary semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2945\u20132954 (2023)","DOI":"10.1109\/CVPR52729.2023.00288"},{"key":"6_CR41","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"736","DOI":"10.1007\/978-3-031-19818-2_42","volume-title":"ECCV 2022","author":"M Xu","year":"2022","unstructured":"Xu, M., et al.: A simple baseline for open-vocabulary semantic segmentation with pre-trained vision-language model. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13689, pp. 736\u2013753. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19818-2_42"},{"key":"6_CR42","unstructured":"Xu, X., et al.: Weakly-supervised 3D visual grounding based on visual linguistic alignment. arXiv preprint arXiv:2312.09625 (2023)"},{"key":"6_CR43","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"677","DOI":"10.1007\/978-3-031-19815-1_39","volume-title":"ECCV 2022","author":"X Yan","year":"2022","unstructured":"Yan, X., et al.: 2DPASS: 2D priors assisted semantic segmentation on LiDAR point clouds. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13688, pp. 677\u2013695. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19815-1_39"},{"key":"6_CR44","doi-asserted-by":"crossref","unstructured":"Yang, C.K., Chen, M.H., Chuang, Y.Y., Lin, Y.Y.: 2D-3D interlaced transformer for point cloud segmentation with scene-level supervision. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 977\u2013987 (2023)","DOI":"10.1109\/ICCV51070.2023.00096"},{"key":"6_CR45","doi-asserted-by":"crossref","unstructured":"Yang, C.K., Wu, J.J., Chen, K.S., Chuang, Y.Y., Lin, Y.Y.: An mil-derived transformer for weakly supervised point cloud segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11830\u201311839 (2022)","DOI":"10.1109\/CVPR52688.2022.01153"},{"key":"6_CR46","doi-asserted-by":"crossref","unstructured":"Yun, S., Park, S.H., Seo, P.H., Shin, J.: IFSeg: image-free semantic segmentation via vision-language model. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2967\u20132977 (2023)","DOI":"10.1109\/CVPR52729.2023.00290"},{"key":"6_CR47","doi-asserted-by":"crossref","unstructured":"Zhang, R., Wang, L., Qiao, Y., Gao, P., Li, H.: Learning 3D representations from 2D pre-trained models via image-to-point masked autoencoders. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 21769\u201321780 (2023)","DOI":"10.1109\/CVPR52729.2023.02085"},{"key":"6_CR48","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Hu, Q., Xu, G., Ma, Y., Wan, J., Guo, Y.: Not all points are equal: learning highly efficient point-based detectors for 3D lidar point clouds. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 18953\u201318962 (2022)","DOI":"10.1109\/CVPR52688.2022.01838"},{"key":"6_CR49","doi-asserted-by":"crossref","unstructured":"Zhao, H., Jiang, L., Jia, J., Torr, P.H., Koltun, V.: Point transformer. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 16259\u201316268 (2021)","DOI":"10.1109\/ICCV48922.2021.01595"},{"key":"6_CR50","doi-asserted-by":"crossref","unstructured":"Zhou, B., Khosla, A., Lapedriza, A., Oliva, A., Torralba, A.: Learning deep features for discriminative localization. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2921\u20132929 (2016)","DOI":"10.1109\/CVPR.2016.319"}],"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\/978-3-031-73464-9_6","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,3]],"date-time":"2024-12-03T10:04:35Z","timestamp":1733220275000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-73464-9_6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,4]]},"ISBN":["9783031734632","9783031734649"],"references-count":50,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-73464-9_6","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,12,4]]},"assertion":[{"value":"4 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"}}]}}