{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T17:34:22Z","timestamp":1777656862121,"version":"3.51.4"},"publisher-location":"Cham","reference-count":51,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031730207","type":"print"},{"value":"9783031730214","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,11,21]],"date-time":"2024-11-21T00:00:00Z","timestamp":1732147200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,21]],"date-time":"2024-11-21T00:00:00Z","timestamp":1732147200000},"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\/978-3-031-73021-4_8","type":"book-chapter","created":{"date-parts":[[2024,11,20]],"date-time":"2024-11-20T09:20:09Z","timestamp":1732094409000},"page":"124-141","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["IFTR: An Instance-Level Fusion Transformer for\u00a0Visual Collaborative Perception"],"prefix":"10.1007","author":[{"given":"Shaohong","family":"Wang","sequence":"first","affiliation":[]},{"given":"Lu","family":"Bin","sequence":"additional","affiliation":[]},{"given":"Xinyu","family":"Xiao","sequence":"additional","affiliation":[]},{"given":"Zhiyu","family":"Xiang","sequence":"additional","affiliation":[]},{"given":"Hangguan","family":"Shan","sequence":"additional","affiliation":[]},{"given":"Eryun","family":"Liu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,11,21]]},"reference":[{"key":"8_CR1","doi-asserted-by":"publisher","first-page":"458","DOI":"10.1109\/OJITS.2022.3181510","volume":"3","author":"J Betz","year":"2022","unstructured":"Betz, J., et al.: Autonomous vehicles on the edge: a survey on autonomous vehicle racing. IEEE Open J. Intell. Transp. Syst. 3, 458\u2013488 (2022)","journal-title":"IEEE Open J. Intell. Transp. Syst."},{"key":"8_CR2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1007\/978-3-030-58452-8_13","volume-title":"Computer Vision \u2013 ECCV 2020","author":"N Carion","year":"2020","unstructured":"Carion, N., Massa, F., Synnaeve, G., Usunier, N., Kirillov, A., Zagoruyko, S.: End-to-end object detection with transformers. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12346, pp. 213\u2013229. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58452-8_13"},{"key":"8_CR3","doi-asserted-by":"crossref","unstructured":"Chen, Q., Ma, X., Tang, S., Guo, J., Yang, Q., Fu, S.: F-cooper: feature based cooperative perception for autonomous vehicle edge computing system using 3D point clouds. In: Proceedings of the 4th ACM\/IEEE Symposium on Edge Computing, pp. 88\u2013100 (2019)","DOI":"10.1145\/3318216.3363300"},{"key":"8_CR4","doi-asserted-by":"crossref","unstructured":"Chen, Z., Shi, Y., Jia, J.: Transiff: an instance-level feature fusion framework for vehicle-infrastructure cooperative 3D detection with transformers. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 18205\u201318214 (2023)","DOI":"10.1109\/ICCV51070.2023.01669"},{"key":"8_CR5","doi-asserted-by":"crossref","unstructured":"Deng, J., Shi, S., Li, P., Zhou, W., Zhang, Y., Li, H.: Voxel R-CNN: towards high performance voxel-based 3D object detection. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a035, pp. 1201\u20131209 (2021)","DOI":"10.1609\/aaai.v35i2.16207"},{"key":"8_CR6","unstructured":"Dosovitskiy, A., Ros, G., Codevilla, F., Lopez, A., Koltun, V.: Carla: an open urban driving simulator. In: Conference on Robot Learning, pp. 1\u201316. PMLR (2017)"},{"key":"8_CR7","unstructured":"Goodfellow, I., Warde-Farley, D., Mirza, M., Courville, A., Bengio, Y.: Maxout networks. In: International Conference on Machine Learning, pp. 1319\u20131327. PMLR (2013)"},{"issue":"1","key":"8_CR8","doi-asserted-by":"publisher","first-page":"522","DOI":"10.1109\/TITS.2020.3012678","volume":"23","author":"Y Guo","year":"2020","unstructured":"Guo, Y., Ma, J., Leslie, E., Huang, Z.: Evaluating the effectiveness of integrated connected automated vehicle applications applied to freeway managed lanes. IEEE Trans. Intell. Transp. Syst. 23(1), 522\u2013536 (2020)","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"8_CR9","unstructured":"Hu, Y., Fang, S., Lei, Z., Zhong, Y., Chen, S.: Where2comm: communication-efficient collaborative perception via spatial confidence maps. In: Advance in Neural Information Processing System, vol. 35, pp. 4874\u20134886 (2022)"},{"issue":"4","key":"8_CR10","doi-asserted-by":"publisher","first-page":"1959","DOI":"10.1109\/LRA.2023.3245421","volume":"8","author":"Y Hu","year":"2023","unstructured":"Hu, Y., Fang, S., Xie, W., Chen, S.: Aerial monocular 3D object detection. IEEE Robot. Autom. Lett. 8(4), 1959\u20131966 (2023)","journal-title":"IEEE Robot. Autom. Lett."},{"key":"8_CR11","unstructured":"Huang, J., Huang, G.: Bevdet4d: exploit temporal cues in multi-camera 3D object detection. arXiv preprint arXiv:2203.17054 (2022)"},{"key":"8_CR12","unstructured":"Huang, J., Huang, G., Zhu, Z., Ye, Y., Du, D.: Bevdet: high-performance multi-camera 3d object detection in bird-eye-view. arXiv preprint arXiv:2112.11790 (2021)"},{"key":"8_CR13","doi-asserted-by":"crossref","unstructured":"Lang, A.H., Vora, S., Caesar, H., Zhou, L., Yang, J., Beijbom, O.: Pointpillars: fast encoders for object detection from point clouds. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12697\u201312705 (2019)","DOI":"10.1109\/CVPR.2019.01298"},{"key":"8_CR14","doi-asserted-by":"publisher","first-page":"103999","DOI":"10.1016\/j.robot.2021.103999","volume":"150","author":"J Li","year":"2022","unstructured":"Li, J., Li, R., Li, J., Wang, J., Wu, Q., Liu, X.: Dual-view 3D object recognition and detection via lidar point cloud and camera image. Robot. Auton. Syst. 150, 103999 (2022)","journal-title":"Robot. Auton. Syst."},{"key":"8_CR15","unstructured":"Li, Y., Ren, S., Wu, P., Chen, S., Feng, C., Zhang, W.: Learning distilled collaboration graph for multi-agent perception. In: Advance in Neural Information Processing System, vol. 34, pp. 29541\u201329552 (2021)"},{"key":"8_CR16","doi-asserted-by":"crossref","unstructured":"Li, Y., et al.: BEVDepth: Acquisition of reliable depth for multi-view 3D object detection. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a037, pp. 1477\u20131485 (2023)","DOI":"10.1609\/aaai.v37i2.25233"},{"key":"8_CR17","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-031-20077-9_1","volume-title":"ECCV 2022","author":"Z Li","year":"2022","unstructured":"Li, Z., et al.: BEVformer: learning bird\u2019s-eye-view representation from multi-camera images via spatiotemporal transformers. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13669, pp. 1\u201318. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-20077-9_1"},{"key":"8_CR18","doi-asserted-by":"crossref","unstructured":"Lin, T.Y., Goyal, P., Girshick, R., He, K., Doll\u00e1r, P.: Focal loss for dense object detection. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2980\u20132988 (2017)","DOI":"10.1109\/ICCV.2017.324"},{"key":"8_CR19","doi-asserted-by":"crossref","unstructured":"Liu, H., Teng, Y., Lu, T., Wang, H., Wang, L.: Sparsebev: high-performance sparse 3d object detection from multi-camera videos. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 18580\u201318590 (2023)","DOI":"10.1109\/ICCV51070.2023.01703"},{"key":"8_CR20","doi-asserted-by":"crossref","unstructured":"Liu, Y.C., Tian, J., Glaser, N., Kira, Z.: When2com: multi-agent perception via communication graph grouping. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4106\u20134115 (2020)","DOI":"10.1109\/CVPR42600.2020.00416"},{"key":"8_CR21","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"531","DOI":"10.1007\/978-3-031-19812-0_31","volume-title":"ECCV 2022","author":"Y Liu","year":"2022","unstructured":"Liu, Y., Wang, T., Zhang, X., Sun, J.: Petr: position embedding transformation for multi-view 3D object detection. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13687, pp. 531\u2013548. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19812-0_31"},{"key":"8_CR22","doi-asserted-by":"crossref","unstructured":"Liu, Y., et al.: Petrv2: a unified framework for 3D perception from multi-camera images. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 3262\u20133272 (2023)","DOI":"10.1109\/ICCV51070.2023.00302"},{"key":"8_CR23","doi-asserted-by":"crossref","unstructured":"Liu, Z., Wu, Z., T\u00f3th, R.: Smoke: single-stage monocular 3D object detection via keypoint estimation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 996\u2013997 (2020)","DOI":"10.1109\/CVPRW50498.2020.00506"},{"key":"8_CR24","unstructured":"Lu, Y., Hu, Y., Zhong, Y., Wang, D., Chen, S., Wang, Y.: An extensible framework for open heterogeneous collaborative perception. arXiv preprint arXiv:2401.13964 (2024)"},{"key":"8_CR25","doi-asserted-by":"crossref","unstructured":"Lu, Y., et al.: Robust collaborative 3D object detection in presence of pose errors. In: 2023 IEEE International Conference on Robotics and Automation (ICRA), pp. 4812\u20134818. IEEE (2023)","DOI":"10.1109\/ICRA48891.2023.10160546"},{"key":"8_CR26","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"194","DOI":"10.1007\/978-3-030-58568-6_12","volume-title":"Computer Vision \u2013 ECCV 2020","author":"J Philion","year":"2020","unstructured":"Philion, J., Fidler, S.: Lift, splat, shoot: encoding images from arbitrary camera rigs by implicitly unprojecting to 3D. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12359, pp. 194\u2013210. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58568-6_12"},{"key":"8_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 Conference on Computer Vision and Pattern Recognition, pp. 652\u2013660 (2017)"},{"issue":"1","key":"8_CR28","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1080\/15472450.2020.1775085","volume":"25","author":"K Raboy","year":"2021","unstructured":"Raboy, K., Ma, J., Leslie, E., Zhou, F.: A proof-of-concept field experiment on cooperative lane change maneuvers using a prototype connected automated vehicle testing platform. J. Intell. Transp. Syst. 25(1), 77\u201392 (2021)","journal-title":"J. Intell. Transp. Syst."},{"key":"8_CR29","doi-asserted-by":"crossref","unstructured":"Reading, C., Harakeh, A., Chae, J., Waslander, S.L.: Categorical depth distribution network for monocular 3D object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8555\u20138564 (2021)","DOI":"10.1109\/CVPR46437.2021.00845"},{"key":"8_CR30","unstructured":"Roddick, T., Kendall, A., Cipolla, R.: Orthographic feature transform for monocular 3d object detection. arXiv preprint arXiv:1811.08188 (2018)"},{"key":"8_CR31","doi-asserted-by":"crossref","unstructured":"Rukhovich, D., Vorontsova, A., Konushin, A.: Imvoxelnet: image to voxels projection for monocular and multi-view general-purpose 3D object detection. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 2397\u20132406 (2022)","DOI":"10.1109\/WACV51458.2022.00133"},{"key":"8_CR32","doi-asserted-by":"publisher","first-page":"216","DOI":"10.1109\/OJITS.2021.3099976","volume":"2","author":"SE Shladover","year":"2021","unstructured":"Shladover, S.E.: Opportunities and challenges in cooperative road vehicle automation. IEEE Open J. Intell. Transp. Syst. 2, 216\u2013224 (2021)","journal-title":"IEEE Open J. Intell. Transp. Syst."},{"key":"8_CR33","unstructured":"Tan, M., Le, Q.: Efficientnet: rethinking model scaling for convolutional neural networks. In: International Conference on Machine Learning, pp. 6105\u20136114. PMLR (2019)"},{"key":"8_CR34","unstructured":"Tan, M., Le, Q.: Efficientnetv2: smaller models and faster training. In: International Conference on Machine Learning, pp. 10096\u201310106. PMLR (2021)"},{"key":"8_CR35","doi-asserted-by":"crossref","unstructured":"Wang, T., Zhu, X., Pang, J., Lin, D.: Fcos3d: fully convolutional one-stage monocular 3D object detection. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 913\u2013922 (2021)","DOI":"10.1109\/ICCVW54120.2021.00107"},{"key":"8_CR36","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"605","DOI":"10.1007\/978-3-030-58536-5_36","volume-title":"Computer Vision \u2013 ECCV 2020","author":"T-H Wang","year":"2020","unstructured":"Wang, T.-H., Manivasagam, S., Liang, M., Yang, B., Zeng, W., Urtasun, R.: V2VNet: vehicle-to-vehicle communication for joint perception and prediction. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12347, pp. 605\u2013621. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58536-5_36"},{"key":"8_CR37","doi-asserted-by":"crossref","unstructured":"Wang, Y., Chao, W.L., Garg, D., Hariharan, B., Campbell, M., Weinberger, K.Q.: Pseudo-lidar from visual depth estimation: bridging the gap in 3D object detection for autonomous driving. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8445\u20138453 (2019)","DOI":"10.1109\/CVPR.2019.00864"},{"key":"8_CR38","unstructured":"Wang, Y., Guizilini, V.C., Zhang, T., Wang, Y., Zhao, H., Solomon, J.: Detr3d: 3D object detection from multi-view images via 3D-to-2D queries. In: Conference on Robot Learning, pp. 180\u2013191. PMLR (2022)"},{"key":"8_CR39","doi-asserted-by":"crossref","unstructured":"Xiang, H., Xu, R., Ma, J.: HM-ViT: hetero-modal vehicle-to-vehicle cooperative perception with vision transformer. arXiv preprint arXiv:2304.10628 (2023)","DOI":"10.1109\/ICCV51070.2023.00033"},{"key":"8_CR40","doi-asserted-by":"crossref","unstructured":"Xu, R., Guo, Y., Han, X., Xia, X., Xiang, H., Ma, J.: OpenCDA: an open cooperative driving automation framework integrated with co-simulation. In: 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), pp. 1155\u20131162. IEEE (2021)","DOI":"10.1109\/ITSC48978.2021.9564825"},{"key":"8_CR41","unstructured":"Xu, R., Tu, Z., Xiang, H., Shao, W., Zhou, B., Ma, J.: CoBEVT: cooperative bird\u2019s eye view semantic segmentation with sparse transformers. arXiv preprint arXiv:2207.02202 (2022)"},{"key":"8_CR42","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1007\/978-3-031-19842-7_7","volume-title":"ECCV 2022","author":"R Xu","year":"2022","unstructured":"Xu, R., Xiang, H., Tu, Z., Xia, X., Yang, M.H., Ma, J.: V2X-ViT: vehicle-to-everything cooperative perception with vision transformer. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13699, pp. 107\u2013124. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19842-7_7"},{"key":"8_CR43","doi-asserted-by":"crossref","unstructured":"Xu, R., Xiang, H., Xia, X., Han, X., Li, J., Ma, J.: OPV2V: an open benchmark dataset and fusion pipeline for perception with vehicle-to-vehicle communication. In: 2022 International Conference on Robotics and Automation (ICRA), pp. 2583\u20132589. IEEE (2022)","DOI":"10.1109\/ICRA46639.2022.9812038"},{"issue":"10","key":"8_CR44","doi-asserted-by":"publisher","first-page":"3337","DOI":"10.3390\/s18103337","volume":"18","author":"Y Yan","year":"2018","unstructured":"Yan, Y., Mao, Y., Li, B.: Second: sparsely embedded convolutional detection. Sensors 18(10), 3337 (2018)","journal-title":"Sensors"},{"key":"8_CR45","doi-asserted-by":"crossref","unstructured":"Yang, C., et\u00a0al.: BEVFormer v2: adapting modern image backbones to bird\u2019s-eye-view recognition via perspective supervision. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 17830\u201317839 (2023)","DOI":"10.1109\/CVPR52729.2023.01710"},{"key":"8_CR46","doi-asserted-by":"crossref","unstructured":"Yin, T., Zhou, X., Krahenbuhl, P.: Center-based 3D object detection and tracking. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11784\u201311793 (2021)","DOI":"10.1109\/CVPR46437.2021.01161"},{"key":"8_CR47","doi-asserted-by":"crossref","unstructured":"Yu, H., et\u00a0al.: DAIR-V2X: a large-scale dataset for vehicle-infrastructure cooperative 3D object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 21361\u201321370 (2022)","DOI":"10.1109\/CVPR52688.2022.02067"},{"key":"8_CR48","doi-asserted-by":"crossref","unstructured":"Zhang, R., et al.: MonoDETR: depth-guided transformer for monocular 3D object detection. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 9155\u20139166 (2023)","DOI":"10.1109\/ICCV51070.2023.00840"},{"key":"8_CR49","doi-asserted-by":"crossref","unstructured":"Zhou, B., Kr\u00e4henb\u00fchl, P.: Cross-view transformers for real-time map-view semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 13760\u201313769 (2022)","DOI":"10.1109\/CVPR52688.2022.01339"},{"key":"8_CR50","doi-asserted-by":"crossref","unstructured":"Zhou, Y., Tuzel, O.: VoxeLNet: end-to-end learning for point cloud based 3D object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4490\u20134499 (2018)","DOI":"10.1109\/CVPR.2018.00472"},{"key":"8_CR51","unstructured":"Zhu, X., Su, W., Lu, L., Li, B., Wang, X., Dai, J.: Deformable DETR: deformable transformers for end-to-end object detection. arXiv preprint arXiv:2010.04159 (2020)"}],"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\/978-3-031-73021-4_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,20]],"date-time":"2024-11-20T09:41:51Z","timestamp":1732095711000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-73021-4_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,21]]},"ISBN":["9783031730207","9783031730214"],"references-count":51,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-73021-4_8","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,21]]},"assertion":[{"value":"21 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"}}]}}