{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T07:02:36Z","timestamp":1790233356876,"version":"4.1.0"},"publisher-location":"Cham","reference-count":54,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032374608","type":"print"},{"value":"9783032374615","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\/978-3-032-37461-5_4","type":"book-chapter","created":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T06:32:32Z","timestamp":1790231552000},"page":"64-82","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["LangDriveCTRL: Natural Language Controllable Driving Scene Editing with Multi-modal Agents"],"prefix":"10.1007","author":[{"given":"Yun","family":"He","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesco","family":"Pittaluga","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziyu","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthias","family":"Zwicker","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Manmohan","family":"Chandraker","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zaid","family":"Tasneem","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,9,25]]},"reference":[{"key":"4_CR1","unstructured":"Achiam, J., Adler, S., Agarwal, S., Ahmad, L., Akkaya, I., Aleman, F.L., Almeida, D., Altenschmidt, J., Altman, S., Anadkat, S.: Gpt-4 technical report (2023). arXiv preprint arXiv:2303.08774"},{"key":"4_CR2","doi-asserted-by":"publisher","first-page":"134614","DOI":"10.52202\/079017-4278","volume":"37","author":"SK Aithal","year":"2024","unstructured":"Aithal, S.K., Maini, P., Lipton, Z., Kolter, J.Z.: Understanding hallucinations in diffusion models through mode interpolation. Adv. Neural. Inf. Process. Syst. 37, 134614\u2013134644 (2024)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"4_CR3","unstructured":"Ali, A., Bai, J., Bala, M., Balaji, Y., Blakeman, A., Cai, T., Cao, J., Cao, T., Cha, E., Chao, Y.W., et\u00a0al.: World simulation with video foundation models for physical ai. (2025). arXiv preprint arXiv:2511.00062"},{"key":"4_CR4","doi-asserted-by":"crossref","unstructured":"Brooks, T., Holynski, A., Efros, A.A.: Instructpix2pix: Learning to follow image editing instructions. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 18392\u201318402 (2023)","DOI":"10.1109\/CVPR52729.2023.01764"},{"key":"4_CR5","first-page":"1877","volume":"33","author":"T Brown","year":"2020","unstructured":"Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J.D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al.: Language models are few-shot learners. Adv. Neural. Inf. Process. Syst. 33, 1877\u20131901 (2020)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"4_CR6","doi-asserted-by":"crossref","unstructured":"Caron, M., Touvron, H., Misra, I., J\u00e9gou, H., Mairal, J., Bojanowski, P., Joulin, A.: 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"},{"key":"4_CR7","doi-asserted-by":"crossref","unstructured":"Chang, W.J., Zhan, W., Tomizuka, M., Chandraker, M., Pittaluga, F.: Langtraj: Diffusion model and dataset for language-conditioned trajectory simulation, (2025). arXiv preprint arXiv:2504.11521","DOI":"10.1109\/ICCV51701.2025.02471"},{"key":"4_CR8","unstructured":"Chen, Z., Yang, J., Huang, J., de\u00a0Lutio, R., Esturo, J.M., Ivanovic, B., Litany, O., Gojcic, Z., Fidler, S., Pavone, M., et\u00a0al.: Omnire: Omni urban scene reconstruction (2024). arXiv preprint arXiv:2408.16760"},{"key":"4_CR9","unstructured":"Cheng, Y., Li, L., Xu, Y., Li, X., Yang, Z., Wang, W., Yang, Y.: Segment and track anything (2023). arXiv preprint arXiv:2305.06558"},{"key":"4_CR10","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 (2017) PMLR"},{"key":"4_CR11","doi-asserted-by":"crossref","unstructured":"Duan, H., Yu, H.X., Chen, S., Fei-Fei, L., Wu, J.: Worldscore: A unified evaluation benchmark for world generation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 27713\u201327724 (2025)","DOI":"10.1109\/ICCV51701.2025.02573"},{"key":"4_CR12","doi-asserted-by":"crossref","unstructured":"Hassan, M., Stapf, S., Rahimi, A., Rezende, P., Haghighi, Y., Br\u00fcggemann, D., Katircioglu, I., Zhang, L., Chen, X., Saha, S.: Gem: A generalizable ego-vision multimodal world model for fine-grained ego-motion, object dynamics, and scene composition control. In: Proceedings of the Computer Vision and Pattern Recognition Conference, pp. 22404\u201322415 (2025)","DOI":"10.1109\/CVPR52734.2025.02087"},{"key":"4_CR13","doi-asserted-by":"crossref","unstructured":"He, Y., Ren, X., Tang, D., Zhang, Y., Xue, X., Fu, Y.: Density-preserving deep point cloud compression. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2333\u20132342 (2022)","DOI":"10.1109\/CVPR52688.2022.00237"},{"key":"4_CR14","doi-asserted-by":"crossref","unstructured":"He, Y., Tang, D., Zhang, Y., Xue, X., Fu, Y.: Grad-pu: Arbitrary-scale point cloud upsampling via gradient descent with learned distance functions. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5354\u20135363 (2023)","DOI":"10.1109\/CVPR52729.2023.00518"},{"key":"4_CR15","unstructured":"Heusel, M., Ramsauer, H., Unterthiner, T., Nessler, B., Hochreiter, S.: Gans trained by a two time-scale update rule converge to a local nash equilibrium. Advances in Neural Information Processing Systems, p. 30 (2017)"},{"key":"4_CR16","doi-asserted-by":"crossref","unstructured":"Hsu, H.Y., Lin, C.H., Zhai, A.J., Xia, H., Wang, S.: Autovfx: Physically realistic video editing from natural language instructions. In: 2025 International Conference on 3D Vision (3DV), pp. 769\u2013780. IEEE (2025)","DOI":"10.1109\/3DV66043.2025.00076"},{"key":"4_CR17","unstructured":"Hurst, A., Lerer, A., Goucher, A.P., Perelman, A., Ramesh, A., Clark, A., Ostrow, A., Welihinda, A., Hayes, A., Radford, A.: Gpt-4o system card (2024). arXiv preprint arXiv:2410.21276"},{"issue":"4","key":"4_CR18","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1145\/3592433","volume":"42","author":"B Kerbl","year":"2023","unstructured":"Kerbl, B., Kopanas, G., Leimk\u00fchler, T., Drettakis, G.: 3d gaussian splatting for real-time radiance field rendering. ACM Trans. Graph. 42(4), 139\u20131 (2023)","journal-title":"ACM Trans. Graph."},{"key":"4_CR19","doi-asserted-by":"crossref","unstructured":"Kirillov, A., Mintun, E., Ravi, N., Mao, H., Rolland, C., Gustafson, L., Xiao, T., Whitehead, S., Berg, A.C., Lo, W.Y.: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4015\u20134026 (2023). Segment anything","DOI":"10.1109\/ICCV51070.2023.00371"},{"key":"4_CR20","doi-asserted-by":"crossref","unstructured":"Li, M., Xie, C., Wu, Y., Zhang, L., Wang, M.: Five: A fine-grained video editing benchmark for evaluating emerging diffusion and rectified flow models (2025). arXiv preprint arXiv:2503.13684","DOI":"10.1109\/ICCV51701.2025.01548"},{"key":"4_CR21","doi-asserted-by":"crossref","unstructured":"Li, W., Zhou, R., Zhou, J., Song, Y., Herter, J., Qin, M., Huang, G., Pfister, H.: 4d langsplat: 4d language gaussian splatting via multimodal large language models. In: Proceedings of the Computer Vision and Pattern Recognition Conference, pp. 22001\u201322011 (2025)","DOI":"10.1109\/CVPR52734.2025.02049"},{"key":"4_CR22","doi-asserted-by":"crossref","unstructured":"Liang, R., Gojcic, Z., Ling, H., Munkberg, J., Hasselgren, J., Lin, C.H., Gao, J., Keller, A., Vijaykumar, N., Fidler, S.: Diffusion renderer: Neural inverse and forward rendering with video diffusion models. In: Proceedings of the Computer Vision and Pattern Recognition Conference, pp. 26069\u201326080 (2025)","DOI":"10.1109\/CVPR52734.2025.02428"},{"key":"4_CR23","doi-asserted-by":"crossref","unstructured":"Liang, Y., Yan, Z., Chen, L., Zhou, J., Yan, L., Zhong, S., Zou, X.: Driveeditor: A unified 3d information-guided framework for controllable object editing in driving scenes. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a039, pp. 5164\u20135172 (2025)","DOI":"10.1609\/aaai.v39i5.32548"},{"key":"4_CR24","doi-asserted-by":"crossref","unstructured":"Liu, S., Zeng, Z., Ren, T., Li, F., Zhang, H., Yang, J., Jiang, Q., Li, C., Yang, J., Su, H., et\u00a0al.: Grounding dino: Marrying dino with grounded pre-training for open-set object detection. In: European Conference on Computer Vision, pp. 38\u201355. Springer (2024)","DOI":"10.1007\/978-3-031-72970-6_3"},{"key":"4_CR25","unstructured":"Meng, C., He, Y., Song, Y., Song, J., Wu, J., Zhu, J.Y., Ermon, S.: Sdedit: Guided image synthesis and editing with stochastic differential equations. arXiv preprint arXiv:2108.01073 (2021)"},{"issue":"1","key":"4_CR26","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1145\/3503250","volume":"65","author":"B Mildenhall","year":"2021","unstructured":"Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. Commun. ACM 65(1), 99\u2013106 (2021)","journal-title":"Commun. ACM"},{"key":"4_CR27","doi-asserted-by":"crossref","unstructured":"Qin, M., Li, W., Zhou, J., Wang, H., Pfister, H.: Langsplat: 3d language gaussian splatting. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 20051\u201320060 (2024)","DOI":"10.1109\/CVPR52733.2024.01895"},{"key":"4_CR28","unstructured":"Ren, T., Liu, S., Zeng, A., Lin, J., Li, K., Cao, H., Chen, J., Huang, X., Chen, Y., Yan, F., et\u00a0al.: Grounded sam: Assembling open-world models for diverse visual tasks (2024). arXiv preprint arXiv:2401.14159"},{"key":"4_CR29","doi-asserted-by":"crossref","unstructured":"Shah, S., Dey, D., Lovett, C., Kapoor, A.: Airsim: High-fidelity visual and physical simulation for autonomous vehicles. In: Field and Service Robotics: Results of the 11th International Conference, pp. 621\u2013635. Springer (2017)","DOI":"10.1007\/978-3-319-67361-5_40"},{"key":"4_CR30","doi-asserted-by":"crossref","unstructured":"Shi, J.C., Wang, M., Duan, H.B., Guan, S.H.: Language embedded 3d gaussians for open-vocabulary scene understanding. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5333\u20135343 (2024)","DOI":"10.1109\/CVPR52733.2024.00510"},{"key":"4_CR31","unstructured":"Song, J., Meng, C., Ermon, S.: Denoising diffusion implicit models, (2020) arXiv preprint arXiv:2010.02502"},{"issue":"1","key":"4_CR32","doi-asserted-by":"publisher","first-page":"1847","DOI":"10.1109\/TIV.2023.3331024","volume":"9","author":"Z Song","year":"2023","unstructured":"Song, Z., He, Z., Li, X., Ma, Q., Ming, R., Mao, Z., Pei, H., Peng, L., Hu, J., Yao, D., et al.: Synthetic datasets for autonomous driving: a survey. IEEE Trans. Intell. Veh. 9(1), 1847\u20131864 (2023)","journal-title":"IEEE Trans. Intell. Veh."},{"key":"4_CR33","unstructured":"Strickland, E.: Are self-driving cars closer than we think? Discover how synthetic data is Paving the way\u2014spectrum.ieee.org. https:\/\/spectrum.ieee.org\/synthetic-data-self-driving (2025) [Accessed 13-11-2025]"},{"issue":"37","key":"4_CR34","doi-asserted-by":"publisher","first-page":"1450","DOI":"10.21105\/joss.01450","volume":"4","author":"C Sullivan","year":"2019","unstructured":"Sullivan, C., Kaszynski, A.: Pyvista: 3d plotting and mesh analysis through a streamlined interface for the visualization toolkit (vtk). J. Open Source Software 4(37), 1450 (2019)","journal-title":"J. Open Source Software"},{"key":"4_CR35","doi-asserted-by":"crossref","unstructured":"Sun, P., Kretzschmar, H., Dotiwalla, X., Chouard, A., Patnaik, V., Tsui, P., Guo, J., Zhou, Y., Chai, Y., Caine, B.: Scalability in perception for autonomous driving: waymo open dataset. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2446\u20132454 (2020)","DOI":"10.1109\/CVPR42600.2020.00252"},{"key":"4_CR36","doi-asserted-by":"crossref","unstructured":"Sun, S., Zhuang, B., Jiang, Z., Liu, B., Xie, X., Chandraker, M.: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 19563\u201319572 (2024) Lidarf: Delving into lidar for neural radiance field on street scenes","DOI":"10.1109\/CVPR52733.2024.01850"},{"key":"4_CR37","doi-asserted-by":"crossref","unstructured":"Tancik, M., Casser, V., Yan, X., Pradhan, S., Mildenhall, B., Srinivasan, P.P., Barron, J.T., Kretzschmar, H.: Block-nerf: Scalable large scene neural view synthesis. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern recognition, pp. 8248\u20138258 (2022)","DOI":"10.1109\/CVPR52688.2022.00807"},{"key":"4_CR38","doi-asserted-by":"crossref","unstructured":"Tasneem, Z., Dave, A., Singh, A., Tiwary, K., Vepakomma, P., Veeraraghavan, A., Raskar, R.: Decentnerfs: Decentralized neural radiance fields from crowdsourced images. In: European Conference on Computer Vision, pp. 144\u2013161. Springer (2024)","DOI":"10.1007\/978-3-031-73202-7_9"},{"key":"4_CR39","unstructured":"Unterthiner, T., Van\u00a0Steenkiste, S., Kurach, K., Marinier, R., Michalski, M., Gelly, S.: Towards accurate generative models of video: a new metric & challenges. arXiv preprint arXiv:1812.01717 (2018)"},{"key":"4_CR40","unstructured":"Wan, T., Wang, A., Ai, B., Wen, B., Mao, C., Xie, C.W., Chen, D., Yu, F., Zhao, H., Yang, J., et\u00a0al.: Wan: Open and advanced large-scale video generative models. arXiv preprint arXiv:2503.20314 (2025)"},{"key":"4_CR41","unstructured":"Wei, Y., Wang, J., Du, Y., Wang, D., Pan, L., Xu, C., Feng, Y., Dai, B., Chen, S.: Chatdyn: Language-driven multi-actor dynamics generation in street scenes. arXiv preprint arXiv:2412.08685 (2024)"},{"key":"4_CR42","doi-asserted-by":"crossref","unstructured":"Wei, Y., Wang, Z., Lu, Y., Xu, C., Liu, C., Zhao, H., Chen, S., Wang, Y.: Editable scene simulation for autonomous driving via collaborative llm-agents. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 15077\u201315087 (2024)","DOI":"10.1109\/CVPR52733.2024.01428"},{"key":"4_CR43","unstructured":"Wu, J.Z., Ren, X., Shen, T., Cao, T., He, K., Lu, Y., Gao, R., Xie, E., Lan, S., Alvarez, J.M.: Chronoedit: Towards temporal reasoning for image editing and world simulation, (2025). arXiv preprint arXiv:2510.04290"},{"key":"4_CR44","doi-asserted-by":"crossref","unstructured":"Wu, J.Z., Zhang, Y., Turki, H., Ren, X., Gao, J., Shou, M.Z., Fidler, S., Gojcic, Z., Ling, H.: Difix3d+: Improving 3d reconstructions with single-step diffusion models. In: Proceedings of the Computer Vision and Pattern Recognition Conference, pp. 26024\u201326035 (2025)","DOI":"10.1109\/CVPR52734.2025.02424"},{"key":"4_CR45","doi-asserted-by":"crossref","unstructured":"Xiong, Y., Zhou, X., Wan, Y., Sun, D., Yang, M.H.: Drivinggaussian++: Towards realistic reconstruction and editable simulation for surrounding dynamic driving scenes (2025). arXiv preprint arXiv:2508.20965","DOI":"10.1109\/TPAMI.2026.3667072"},{"key":"4_CR46","unstructured":"Xu, R., Lin, H., Jeon, W., Feng, H., Zou, Y., Sun, L., Gorman, J., Tolstaya, K., Tang, S., White, B.: Wod-e2e: Waymo open dataset for end-to-end driving in challenging long-tail scenarios, (2025) arXiv preprint arXiv:2510.26125"},{"key":"4_CR47","unstructured":"Yang, J., Gao, M., Li, Z., Gao, S., Wang, F., Zheng, F.: Track anything: Segment anything meets videos. (2023) arXiv preprint arXiv:2304.11968"},{"key":"4_CR48","unstructured":"Yang, Z., Teng, J., Zheng, W., Ding, M., Huang, S., Xu, J., Yang, Y., Hong, W., Zhang, X., Feng, G., et\u00a0al.: Cogvideox: text-to-video diffusion models with an expert transformer (2024) arXiv preprint arXiv:2408.06072"},{"key":"4_CR49","doi-asserted-by":"crossref","unstructured":"YU, M., Hu, W., Xing, J., Shan, Y.: Trajectorycrafter: Redirecting camera trajectory for monocular videos via diffusion models. (2025) arXiv preprint arXiv:2503.05638","DOI":"10.1109\/ICCV51701.2025.00017"},{"key":"4_CR50","doi-asserted-by":"crossref","unstructured":"Zhang, L., Rao, A., Agrawala, M.: Adding conditional control to text-to-image diffusion models. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 3836\u20133847 (2023)","DOI":"10.1109\/ICCV51070.2023.00355"},{"key":"4_CR51","doi-asserted-by":"crossref","unstructured":"Zhao, G., Ni, C., Wang, X., Zhu, Z., Zhang, X., Wang, Y., Huang, G., Chen, X., Wang, B., Zhang, Y., et\u00a0al.: Drivedreamer4d: World models are effective data machines for 4d driving scene representation. In: Proceedings of the Computer Vision and Pattern Recognition Conference, pp. 12015\u201312026 (2025)","DOI":"10.1109\/CVPR52734.2025.01122"},{"key":"4_CR52","doi-asserted-by":"crossref","unstructured":"Zhao, G., Wang, X., Zhu, Z., Chen, X., Huang, G., Bao, X., Wang, X.: Drivedreamer-2: Llm-enhanced world models for diverse driving video generation. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a039, pp. 10412\u201310420 (2025)","DOI":"10.1609\/aaai.v39i10.33130"},{"key":"4_CR53","unstructured":"Zhao, Z., Lai, Z., Lin, Q., Zhao, Y., Liu, H., Yang, S., Feng, Y., Yang, M., Zhang, S., Yang, X., et\u00a0al.: Hunyuan3d 2.0: Scaling diffusion models for high resolution textured 3d assets generation. arXiv preprint arXiv:2501.12202 (2025)"},{"key":"4_CR54","doi-asserted-by":"crossref","unstructured":"Zhu, Z., Zou, Y., Jiang, C.M., Sun, B., Casser, V., Huang, X., Wang, J., Yang, Z., Gao, R., Guibas, L.: Scenecrafter: Controllable multi-view driving scene editing. In: Proceedings of the Computer Vision and Pattern Recognition Conference, pp. 6812\u20136822 (2025)","DOI":"10.1109\/CVPR52734.2025.00639"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2026"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-37461-5_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T06:32:43Z","timestamp":1790231563000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-37461-5_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9783032374608","9783032374615"],"references-count":54,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-37461-5_4","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":"25 September 2026","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":"Malm\u00f6","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sweden","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 September 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 September 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2026","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv.ecva.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}