{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T20:20:09Z","timestamp":1788985209636,"version":"build-2803163510"},"publisher-location":"Cham","reference-count":88,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032376268","type":"print"},{"value":"9783032376275","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\/978-3-032-37627-5_5","type":"book-chapter","created":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T20:04:29Z","timestamp":1788984269000},"page":"77-96","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["SPEAR: A Simulator for\u00a0Photorealistic Embodied AI Research"],"prefix":"10.1007","author":[{"given":"Mike","family":"Roberts","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Renhan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rushikesh","family":"Zawar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rachith","family":"Dey-Prakash","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Quentin","family":"Leboutet","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephan R.","family":"Richter","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthias","family":"M\u00fcller","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"German","family":"Ros","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rui","family":"Tang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefan","family":"Leutenegger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yannick","family":"Hold-Geoffroy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kalyan","family":"Sunkavalli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vladlen","family":"Koltun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,9,10]]},"reference":[{"key":"5_CR1","unstructured":"Blueprints visual scripting. Epic Games Developer Documentation"},{"key":"5_CR2","unstructured":"Console variables and commands. Epic Games Developer Documentation"},{"key":"5_CR3","unstructured":"NVIDIA Isaac Sim. https:\/\/developer.nvidia.com\/isaac\/sim"},{"key":"5_CR4","unstructured":"An overview of components. Epic Games Developer Documentation"},{"key":"5_CR5","unstructured":"Panda3D. https:\/\/www.panda3d.org"},{"key":"5_CR6","unstructured":"Scripting the Unreal Editor using Python. Epic Games Developer Documentation"},{"key":"5_CR7","unstructured":"Unity. https:\/\/unity.com"},{"key":"5_CR8","unstructured":"Unreal Engine. https:\/\/www.unrealengine.com"},{"key":"5_CR9","unstructured":"Unreal Engine reflection system. Epic Games Developer Documentation"},{"key":"5_CR10","unstructured":"Black Myth: Wukong tops 25 million copies sold as its merchandise sales skyrocket in China. Game World Observer (2025)"},{"key":"5_CR11","unstructured":"Clair Obscur takes home 9 Game Awards including Game of the Year. Epic Games Store News (2025)"},{"key":"5_CR12","doi-asserted-by":"crossref","unstructured":"Bachmann, R., et al.: 4M-21: an any-to-any vision model for tens of tasks and modalities. In: NeurIPS (2024)","DOI":"10.52202\/079017-1977"},{"key":"5_CR13","doi-asserted-by":"crossref","unstructured":"Bai, J., et al.: ReCamMaster: camera-controlled generative rendering from a single video. In: ICCV (2025)","DOI":"10.1109\/ICCV51701.2025.01376"},{"key":"5_CR14","unstructured":"Beattie, C., et al.: DeepMind Lab. arXiv (2016)"},{"key":"5_CR15","doi-asserted-by":"crossref","unstructured":"Bellemare, M.G., Naddaf, Y., Veness, J., Bowling, M.: The arcade learning environment: an evaluation platform for general agents. J. Artif. Intell. Res. 47(1) (2013)","DOI":"10.1613\/jair.3912"},{"key":"5_CR16","doi-asserted-by":"crossref","unstructured":"Bordes, F., Shekhar, S., Ibrahim, M., Bouchacourt, D., Vincent, P., Morcos, A.S.: PUG: photorealistic and semantically controllable synthetic data for representation learning. In: NeurIPS (2023)","DOI":"10.52202\/075280-1952"},{"key":"5_CR17","unstructured":"Brockman, G., et al.: OpenAI Gym. arXiv (2016)"},{"key":"5_CR18","unstructured":"Dosovitskiy, A., Ros, G., Codevilla, F., Lopez, A., Koltun, V.: CARLA: an open urban driving simulator. In: CoRL (2017)"},{"key":"5_CR19","doi-asserted-by":"crossref","unstructured":"Fan, L., et al.: MineDojo: building open-ended embodied agents with internet-scale knowledge. In: NeurIPS 2022 Datasets and Benchmarks Track (2022)","DOI":"10.52202\/068431-1333"},{"key":"5_CR20","unstructured":"Gabeur, V., et al.: Image generators are generalist vision learners. arXiv (2026)"},{"key":"5_CR21","unstructured":"Gan, C., et al.: ThreeDWorld: a platform for interactive multi-modal physical simulation. In: NeurIPS 2021 Datasets and Benchmarks Track (2021)"},{"key":"5_CR22","doi-asserted-by":"crossref","unstructured":"Ge, Y., et al.: BEHAVIOR vision suite: customizable dataset generation via simulation. In: CVPR (2024)","DOI":"10.1109\/CVPR52733.2024.02114"},{"key":"5_CR23","doi-asserted-by":"crossref","unstructured":"Gong, R., et al.: Arnold: a benchmark for language-grounded task learning with continuous states in realistic 3D scenes. In: ICCV (2023)","DOI":"10.1109\/ICCV51070.2023.01873"},{"key":"5_CR24","doi-asserted-by":"crossref","unstructured":"Hwangbo, J., et al.: Learning agile and dynamic motor skills for legged robots. Sci. Robot. 4(26) (2019)","DOI":"10.1126\/scirobotics.aau5872"},{"key":"5_CR25","doi-asserted-by":"crossref","unstructured":"Jaderberg, M., et al.: Human-level performance in 3D multiplayer games with population-based deep reinforcement learning. Science 364(6443) (2019)","DOI":"10.1126\/science.aau6249"},{"key":"5_CR26","unstructured":"Jakob, W.: nanobind: tiny and efficient C++\/Python bindings. https:\/\/github.com\/wjakob\/nanobind"},{"key":"5_CR27","unstructured":"Johnson, M., Hofmann, K., Hutton, T., Bignell, D.: The Malmo platform for artificial intelligence experimentation. In: IJCAI (2016)"},{"key":"5_CR28","unstructured":"Juliani, A., et al.: Unity: a general platform for intelligent agents. arXiv (2018)"},{"key":"5_CR29","unstructured":"Karis, B., Stubbe, R., Wihlidal, G.: A deep dive into Nanite virtualized geometry. In: SIGGRAPH 2021 Course on Advances in Real-Time Rendering and Games (2021)"},{"key":"5_CR30","doi-asserted-by":"crossref","unstructured":"Kaufmann, E., Bauersfeld, L., Loquercio, A., M\u00fcller, M., Koltun, V., Scaramuzza, D.: Champion-level drone racing using deep reinforcement learning. Nature 620(7976) (2023)","DOI":"10.1038\/s41586-023-06419-4"},{"key":"5_CR31","unstructured":"Kaufmann, E., Loquercio, A., Ranftl, R., Dosovitskiy, A., Koltun, V., Scaramuzza, D.: Deep drone racing: learning agile flight in dynamic environments. In: CoRL (2018)"},{"key":"5_CR32","doi-asserted-by":"crossref","unstructured":"Kaufmann, E., Loquercio, A., Ranftl, R., M\u00fcller, M., Koltun, V., Scaramuzza, D.: Deep drone acrobatics. In: RSS (2020)","DOI":"10.15607\/RSS.2020.XVI.040"},{"key":"5_CR33","doi-asserted-by":"crossref","unstructured":"Ke, B., Obukhov, A., Huang, S., Metzger, N., Daudt, R.C., Schindler, K.: Repurposing diffusion-based image generators for monocular depth estimation. In: CVPR (2024)","DOI":"10.1109\/CVPR52733.2024.00907"},{"key":"5_CR34","doi-asserted-by":"crossref","unstructured":"Kempka, M., Wydmuch, M., Runc, G., Toczek, J., Ja\u015bkowski, W.: ViZDoom: a doom-based AI research platform for visual reinforcement learning. In: Computational Intelligence and Games (2016)","DOI":"10.1109\/CIG.2016.7860433"},{"key":"5_CR35","doi-asserted-by":"crossref","unstructured":"Kirillov, A., et al.: Segment anything. In: ICCV (2023)","DOI":"10.1109\/ICCV51070.2023.00371"},{"key":"5_CR36","unstructured":"Kolve, E., et al.: AI2-THOR: an interactive 3D environment for visual AI. arXiv (2017)"},{"key":"5_CR37","doi-asserted-by":"crossref","unstructured":"Kr\u00e4henb\u00fchl, P.: Free supervision from video games. In: CVPR (2018)","DOI":"10.1109\/CVPR.2018.00312"},{"key":"5_CR38","unstructured":"Langmead, A.: Procedural content generation in UE5. In: Game Developers Conference (2023)"},{"key":"5_CR39","doi-asserted-by":"crossref","unstructured":"Lee, J., Hwangbo, J., Wellhausen, L., Koltun, V., Hutter, M.: Learning quadrupedal locomotion over challenging terrain. Sci. Robot. 5(47) (2020)","DOI":"10.1126\/scirobotics.abc5986"},{"key":"5_CR40","unstructured":"Lerer, A., Gross, S., Fergus, R.: Learning physical intuition of block towers by example. In: ICML (2016)"},{"key":"5_CR41","unstructured":"Li, C., et al.: iGibson 2.0: object-centric simulation for robot learning of everyday household tasks. In: CoRL (2021)"},{"key":"5_CR42","unstructured":"Li, C., et al.: BEHAVIOR-1K: a human-centered, embodied AI benchmark with 1,000 everyday activities and realistic simulation. In: CoRL (2022)"},{"key":"5_CR43","doi-asserted-by":"crossref","unstructured":"Loquercio, A., Kaufmann, E., Ranftl, R., Dosovitskiy, A., Koltun, V., Scaramuzza, D.: Deep drone racing: from simulation to reality with domain randomization. Trans. Robot. 36(1) (2020)","DOI":"10.1109\/TRO.2019.2942989"},{"key":"5_CR44","doi-asserted-by":"crossref","unstructured":"Loquercio, A., Kaufmann, E., Ranftl, R., M\u00fcller, M., Koltun, V., Scaramuzza, D.: Learning high-speed flight in the wild. Sci. Robot. 6(59) (2021)","DOI":"10.1126\/scirobotics.abg5810"},{"key":"5_CR45","doi-asserted-by":"crossref","unstructured":"Maes, P.: Concepts and experiments in computational reflection. In: OOPSLA (1987)","DOI":"10.1145\/38765.38821"},{"key":"5_CR46","unstructured":"Magne, L., et al.: NitroGen: an open foundation model for generalist gaming agents. arXiv (2026)"},{"key":"5_CR47","doi-asserted-by":"crossref","unstructured":"Martinez-Gonzalez, P., et al.: UnrealROX+: an improved tool for acquiring synthetic data from virtual 3D environments. In: IJCNN (2021)","DOI":"10.1109\/IJCNN52387.2021.9534447"},{"key":"5_CR48","doi-asserted-by":"crossref","unstructured":"Martinez-Gonzalez, P., Oprea, S., Garcia-Garcia, A., Jover-Alvarez, A., Orts-Escolano, S., Garcia-Rodriguez, J.: UnrealROX: an extremely photorealistic virtual reality environment for robotics simulations and synthetic data generation. Virtual Reality 24 (2019)","DOI":"10.1007\/s10055-019-00399-5"},{"key":"5_CR49","doi-asserted-by":"crossref","unstructured":"Mazur, K., Bae, G., Davison, A.J.: SuperPrimitive: scene reconstruction at a primitive level. In: CVPR (2024)","DOI":"10.1109\/CVPR52733.2024.00476"},{"key":"5_CR50","doi-asserted-by":"crossref","unstructured":"Miki, T., Lee, J., Hwangbo, J., Wellhausen, L., Koltun, V., Hutter, M.: Learning robust perceptive locomotion for quadrupedal robots in the wild. Sci. Robot. 7(62) (2022)","DOI":"10.1126\/scirobotics.abk2822"},{"key":"5_CR51","doi-asserted-by":"crossref","unstructured":"Mizrahi, D., et al.: 4M: massively multimodal masked modeling. In: NeurIPS (2023)","DOI":"10.52202\/075280-2544"},{"key":"5_CR52","doi-asserted-by":"crossref","unstructured":"Mnih, V., et al.: Human-level control through deep reinforcement learning. Nature 518(7540) (2015)","DOI":"10.1038\/nature14236"},{"key":"5_CR53","unstructured":"M\u00fcller, M., Dosovitskiy, A., Ghanem, B., Koltun, V.: Driving policy transfer via modularity and abstraction. In: CoRL (2018)"},{"key":"5_CR54","unstructured":"Narkowicz, K., Costa, T.: MegaLights: stochastic direct lighting in unreal engine 5. In: SIGGRAPH 2025 Advances in Real-Time Rendering in Games (2025)"},{"key":"5_CR55","unstructured":"Akkaya, I., et al.: Solving Rubik\u2019s Cube with a robot hand. arXiv (2019)"},{"key":"5_CR56","unstructured":"Berner, C., et al.: Dota 2 with large scale deep reinforcement learning. arXiv (2019)"},{"key":"5_CR57","unstructured":"Puig, X., et al.: Habitat 3.0: a co-habitat for humans, avatars and robots. In: ICLR (2024)"},{"key":"5_CR58","doi-asserted-by":"crossref","unstructured":"Qiu, W., et al.: UnrealCV: virtual worlds for computer vision. In: Multimedia (2017)","DOI":"10.1145\/3123266.3129396"},{"key":"5_CR59","unstructured":"Ravi, N., et al.: SAM 2: segment anything in images and videos. In: ICLR (2025)"},{"key":"5_CR60","doi-asserted-by":"crossref","unstructured":"Richter, S., Vineet, V., Roth, S., Koltun, V.: Playing for data: ground truth from computer games. In: ECCV (2016)","DOI":"10.1007\/978-3-319-46475-6_7"},{"key":"5_CR61","doi-asserted-by":"crossref","unstructured":"Richter, S.R., Hayder, Z., Koltun, V.: Playing for benchmarks. In: ICCV (2017)","DOI":"10.1109\/ICCV.2017.243"},{"key":"5_CR62","doi-asserted-by":"crossref","unstructured":"Roberts, M., et al.: Hypersim: a photorealistic synthetic dataset for holistic indoor scene understanding. In: ICCV (2021)","DOI":"10.1109\/ICCV48922.2021.01073"},{"key":"5_CR63","unstructured":"van Rossum, G., Coghlan, A.: PEP 343: The \u201cwith\u201d statement. Python Enhancement Proposals"},{"key":"5_CR64","unstructured":"Savva, M., Chang, A.X., Dosovitskiy, A., Funkhouser, T., Koltun, V.: MINOS: multimodal indoor simulator for navigation in complex environments. arXiv (2017)"},{"key":"5_CR65","doi-asserted-by":"crossref","unstructured":"Savva, M., et al.: Habitat: a platform for embodied AI research. In: ICCV (2019)","DOI":"10.1109\/ICCV.2019.00943"},{"key":"5_CR66","unstructured":"Sch\u00e4ling, B.: The Boost C++ Libraries. XML Press (2011)"},{"key":"5_CR67","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 (2017)","DOI":"10.1007\/978-3-319-67361-5_40"},{"key":"5_CR68","doi-asserted-by":"crossref","unstructured":"Shen, B., et al.: iGibson 1.0: a simulation environment for interactive tasks in large realistic scenes. In: IROS (2021)","DOI":"10.1109\/IROS51168.2021.9636667"},{"key":"5_CR69","unstructured":"Sim\u00e9oni, O., et al.: DINOv3. arXiv (2025)"},{"key":"5_CR70","unstructured":"Szelei, T.: rpclib: modern msgpack-rpc for C++. http:\/\/rpclib.net"},{"key":"5_CR71","unstructured":"Szot, A., et al.: Habitat 2.0: training home assistants to rearrange their habitat. In: NeurIPS (2021)"},{"key":"5_CR72","doi-asserted-by":"crossref","unstructured":"Todorov, E., Erez, T., Tassa, Y.: MuJoCo: a physics engine for model-based control. In: IROS (2012)","DOI":"10.1109\/IROS.2012.6386109"},{"key":"5_CR73","doi-asserted-by":"crossref","unstructured":"Tong, S., et al.: Cambrian-1: a fully open, vision-centric exploration of multimodal LLMs. In: NeurIPS (2024)","DOI":"10.52202\/079017-2771"},{"key":"5_CR74","unstructured":"Vandevoorde, D., Josuttis, N.M., Gregor, D.: C++ Templates: The Complete Guide, 2 edn. Addison-Wesley Professional (2017)"},{"key":"5_CR75","doi-asserted-by":"crossref","unstructured":"Vinyals, O., et al.: Grandmaster level in StarCraft II using multi-agent reinforcement learning. Nature 575 (2019)","DOI":"10.1038\/s41586-019-1724-z"},{"key":"5_CR76","unstructured":"Vinyals, O., et al.: StarCraft II: a new challenge for reinforcement learning. arXiv (2017)"},{"key":"5_CR77","doi-asserted-by":"crossref","unstructured":"Wang, J., Chen, M., Karaev, N., Vedaldi, A., Rupprecht, C., Novotny, D.: VGGT: visual geometry grounded transformer. In: CVPR (2025)","DOI":"10.1109\/CVPR52734.2025.00499"},{"key":"5_CR78","unstructured":"Wang, J., et al.: VGGT-$$\\Omega $$. In: CVPR (2026)"},{"key":"5_CR79","unstructured":"Wright, D., Narkowicz, K., Kelly, P.: Lumen: real-time global illumination in Unreal Engine 5. In: SIGGRAPH 2022 Advances in Real-Time Rendering in Games (2022)"},{"key":"5_CR80","unstructured":"Wu, W., et al.: MetaUrban: an embodied AI simulation platform for urban micromobility. In: ICLR (2025)"},{"key":"5_CR81","doi-asserted-by":"crossref","unstructured":"Wu, W., et al.: Towards autonomous micromobility through scalable urban simulation. In: CVPR (2025)","DOI":"10.1109\/CVPR52734.2025.02566"},{"key":"5_CR82","doi-asserted-by":"crossref","unstructured":"Wurman, P.R., et al.: Outracing champion gran turismo drivers with deep reinforcement learning. Nature 602 (2022)","DOI":"10.1038\/s41586-021-04357-7"},{"key":"5_CR83","doi-asserted-by":"crossref","unstructured":"Xia, F., Zamir, A.R., He, Z.Y., Sax, A., Malik, J., Savarese, S.: Gibson env: real-world perception for embodied agents. In: CVPR (2018)","DOI":"10.1109\/CVPR.2018.00945"},{"key":"5_CR84","doi-asserted-by":"crossref","unstructured":"Xiang, F., et al.: SAPIEN: a simulated part-based interactive environment. In: CVPR (2020)","DOI":"10.1109\/CVPR42600.2020.01111"},{"key":"5_CR85","unstructured":"Yang, S., et al.: Cambrian-S: towards spatial supersensing in video. arXiv (2025)"},{"key":"5_CR86","doi-asserted-by":"crossref","unstructured":"Ye, X., et al.: SimWorld: an open-ended simulator for agents in physical and social worlds. In: NeurIPS (2025)","DOI":"10.52202\/085713-5519"},{"key":"5_CR87","doi-asserted-by":"crossref","unstructured":"Zhong, F., et al.: UnrealZoo: enriching photo-realistic virtual worlds for embodied AI. In: ICCV (2025)","DOI":"10.1109\/ICCV51701.2025.00546"},{"key":"5_CR88","doi-asserted-by":"crossref","unstructured":"Zhou, B., Kr\u00e4henb\u00fchl, P., Koltun, V.: Does computer vision matter for action? Sci. Robot. 4(30) (2018)","DOI":"10.1126\/scirobotics.aaw6661"}],"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\/978-3-032-37627-5_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T20:04:40Z","timestamp":1788984280000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-37627-5_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9783032376268","9783032376275"],"references-count":88,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-37627-5_5","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":"10 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"}}]}}