{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:23:53Z","timestamp":1742912633057,"version":"3.40.3"},"publisher-location":"Cham","reference-count":50,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031590566"},{"type":"electronic","value":"9783031590573"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-59057-3_11","type":"book-chapter","created":{"date-parts":[[2024,5,7]],"date-time":"2024-05-07T22:02:19Z","timestamp":1715119339000},"page":"164-178","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["GAT-POSE: Graph Autoencoder-Transformer Fusion for\u00a0Future Pose Prediction"],"prefix":"10.1007","author":[{"given":"Armin Danesh","family":"Pazho","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gabriel","family":"Maldonado","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hamed","family":"Tabkhi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,5,8]]},"reference":[{"issue":"11","key":"11_CR1","doi-asserted-by":"publisher","first-page":"2335","DOI":"10.3390\/app9112335","volume":"9","author":"S Ahmed","year":"2019","unstructured":"Ahmed, S., Huda, M.N., Rajbhandari, S., Saha, C., Elshaw, M., Kanarachos, S.: Pedestrian and cyclist detection and intent estimation for autonomous vehicles: a survey. Appl. Sci. 9(11), 2335 (2019)","journal-title":"Appl. Sci."},{"key":"11_CR2","doi-asserted-by":"crossref","unstructured":"Aliakbarian, S., Saleh, F.S., Salzmann, M., Petersson, L., Gould, S.: A stochastic conditioning scheme for diverse human motion prediction. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5223\u20135232 (2020)","DOI":"10.1109\/CVPR42600.2020.00527"},{"key":"11_CR3","doi-asserted-by":"crossref","unstructured":"Barsoum, E., Kender, J., Liu, Z.: HP-GAN: probabilistic 3D human motion prediction via GAN. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 1418\u20131427 (2018)","DOI":"10.1109\/CVPRW.2018.00191"},{"key":"11_CR4","doi-asserted-by":"crossref","unstructured":"B\u00fctepage, J., Kjellstr\u00f6m, H., Kragic, D.: Anticipating many futures: online human motion prediction and generation for human-robot interaction. In: 2018 IEEE International Conference on Robotics and Automation (ICRA), pp. 4563\u20134570. IEEE (2018)","DOI":"10.1109\/ICRA.2018.8460651"},{"key":"11_CR5","doi-asserted-by":"crossref","unstructured":"Chao, X., et al.: Adversarial refinement network for human motion prediction. In: Proceedings of the Asian Conference on Computer Vision (2020)","DOI":"10.1007\/978-3-030-69532-3_28"},{"key":"11_CR6","doi-asserted-by":"crossref","unstructured":"Corona, E., Pumarola, A., Alenya, G., Moreno-Noguer, F.: Context-aware human motion prediction. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6992\u20137001 (2020)","DOI":"10.1109\/CVPR42600.2020.00702"},{"key":"11_CR7","doi-asserted-by":"crossref","unstructured":"Cui, Q., Sun, H., Yang, F.: Learning dynamic relationships for 3D human motion prediction. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6519\u20136527 (2020)","DOI":"10.1109\/CVPR42600.2020.00655"},{"key":"11_CR8","doi-asserted-by":"crossref","unstructured":"Cui, Q., Sun, H., Yang, F.: Learning dynamic relationships for 3D human motion prediction. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 6519\u20136527 (2020)","DOI":"10.1109\/CVPR42600.2020.00655"},{"key":"11_CR9","doi-asserted-by":"crossref","unstructured":"Guo, X., Choi, J.: Human motion prediction via learning local structure representations and temporal dependencies. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a033, pp. 2580\u20132587 (2019)","DOI":"10.1609\/aaai.v33i01.33012580"},{"key":"11_CR10","doi-asserted-by":"crossref","unstructured":"Huang, Z., Liu, Y., Fang, Y., Horn, B.K.: Video-based fall detection for seniors with human pose estimation. In: 2018 4th International Conference on Universal Village (UV), pp.\u00a01\u20134. IEEE (2018)","DOI":"10.1109\/UV.2018.8642130"},{"issue":"7","key":"11_CR11","doi-asserted-by":"publisher","first-page":"1325","DOI":"10.1109\/TPAMI.2013.248","volume":"36","author":"C Ionescu","year":"2013","unstructured":"Ionescu, C., Papava, D., Olaru, V., Sminchisescu, C.: Human3.6m: large scale datasets and predictive methods for 3D human sensing in natural environments. IEEE Trans. Pattern Anal. Mach. Intell. 36(7), 1325\u20131339 (2013)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"18","key":"11_CR12","doi-asserted-by":"publisher","first-page":"14579","DOI":"10.1007\/s00521-020-04941-4","volume":"32","author":"DK Jain","year":"2020","unstructured":"Jain, D.K., Zareapoor, M., Jain, R., Kathuria, A., Bachhety, S.: GAN-poser: an improvised bidirectional GAN model for human motion prediction. Neural Comput. Appl. 32(18), 14579\u201314591 (2020)","journal-title":"Neural Comput. Appl."},{"key":"11_CR13","doi-asserted-by":"crossref","unstructured":"Jeon, H., Yoon, Y., Kim, D.: Lightweight 2D human pose estimation for fitness coaching system. In: 2021 36th International Technical Conference on Circuits\/Systems, Computers and Communications (ITC-CSCC), pp.\u00a01\u20134. IEEE (2021)","DOI":"10.1109\/ITC-CSCC52171.2021.9501458"},{"key":"11_CR14","doi-asserted-by":"crossref","unstructured":"Kundu, J.N., Gor, M., Babu, R.V.: BiHMP-GAN: bidirectional 3D human motion prediction GAN. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a033, pp. 8553\u20138560 (2019)","DOI":"10.1609\/aaai.v33i01.33018553"},{"key":"11_CR15","doi-asserted-by":"crossref","unstructured":"Li, C., Zhang, Z., Lee, W.S., Lee, G.H.: Convolutional sequence to sequence model for human dynamics. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5226\u20135234 (2018)","DOI":"10.1109\/CVPR.2018.00548"},{"key":"11_CR16","doi-asserted-by":"crossref","unstructured":"Li, C., Zhang, Z., Lee, W.S., Lee, G.H.: Convolutional sequence to sequence model for human dynamics. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5226\u20135234 (2018)","DOI":"10.1109\/CVPR.2018.00548"},{"key":"11_CR17","doi-asserted-by":"crossref","unstructured":"Li, M., Chen, S., Zhao, Y., Zhang, Y., Wang, Y., Tian, Q.: Dynamic multiscale graph neural networks for 3D skeleton based human motion prediction. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 214\u2013223 (2020)","DOI":"10.1109\/CVPR42600.2020.00029"},{"key":"11_CR18","doi-asserted-by":"publisher","first-page":"7760","DOI":"10.1109\/TIP.2021.3108708","volume":"30","author":"M Li","year":"2021","unstructured":"Li, M., Chen, S., Zhao, Y., Zhang, Y., Wang, Y., Tian, Q.: Multiscale spatio-temporal graph neural networks for 3D skeleton-based motion prediction. IEEE Trans. Image Process. 30, 7760\u20137775 (2021)","journal-title":"IEEE Trans. Image Process."},{"key":"11_CR19","doi-asserted-by":"publisher","first-page":"1143","DOI":"10.1007\/s00371-019-01692-9","volume":"35","author":"Y Li","year":"2019","unstructured":"Li, Y., et al.: Efficient convolutional hierarchical autoencoder for human motion prediction. Vis. Comput. 35, 1143\u20131156 (2019)","journal-title":"Vis. Comput."},{"issue":"5","key":"11_CR20","doi-asserted-by":"publisher","first-page":"3296","DOI":"10.3390\/app13053296","volume":"13","author":"D Liu","year":"2023","unstructured":"Liu, D., Li, Q., Li, S., Kong, J., Qi, M.: Non-autoregressive sparse transformer networks for pedestrian trajectory prediction. Appl. Sci. 13(5), 3296 (2023)","journal-title":"Appl. Sci."},{"issue":"1","key":"11_CR21","doi-asserted-by":"publisher","first-page":"1106","DOI":"10.1109\/TPAMI.2022.3155712","volume":"45","author":"S Liu","year":"2022","unstructured":"Liu, S., Huang, X., Fu, N., Li, C., Su, Z., Ostadabbas, S.: Simultaneously-collected multimodal lying pose dataset: enabling in-bed human pose monitoring. IEEE Trans. Pattern Anal. Mach. Intell. 45(1), 1106\u20131118 (2022)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"6","key":"11_CR22","doi-asserted-by":"publisher","first-page":"2133","DOI":"10.1109\/TCSVT.2020.3021409","volume":"31","author":"X Liu","year":"2020","unstructured":"Liu, X., Yin, J., Liu, J., Ding, P., Liu, J., Liu, H.: TrajectoryCNN: a new spatio-temporal feature learning network for human motion prediction. IEEE Trans. Circuits Syst. Video Technol. 31(6), 2133\u20132146 (2020)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"11_CR23","doi-asserted-by":"crossref","unstructured":"Liu, Z., et al.: Motion prediction using trajectory cues. In: IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 13299\u201313308 (2021)","DOI":"10.1109\/ICCV48922.2021.01305"},{"key":"11_CR24","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1016\/j.neucom.2022.02.045","volume":"489","author":"K Lyu","year":"2022","unstructured":"Lyu, K., Chen, H., Liu, Z., Zhang, B., Wang, R.: 3D human motion prediction: a survey. Neurocomputing 489, 345\u2013365 (2022)","journal-title":"Neurocomputing"},{"key":"11_CR25","doi-asserted-by":"crossref","unstructured":"Lyu, K., Liu, Z., Wu, S., Chen, H., Zhang, X., Yin, Y.: Learning human motion prediction via stochastic differential equations. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 4976\u20134984 (2021)","DOI":"10.1145\/3474085.3475630"},{"key":"11_CR26","doi-asserted-by":"crossref","unstructured":"Ma, T., Nie, Y., Long, C., Zhang, Q., Li, G.: Progressively generating better initial guesses towards next stages for high-quality human motion prediction. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 6437\u20136446 (2022)","DOI":"10.1109\/CVPR52688.2022.00633"},{"key":"11_CR27","doi-asserted-by":"crossref","unstructured":"Mahdavian, M., Nikdel, P., TaherAhmadi, M., Chen, M.: STPOTR: simultaneous human trajectory and pose prediction using a non-autoregressive transformer for robot follow-ahead. In: 2023 IEEE International Conference on Robotics and Automation (ICRA), pp. 9959\u20139965. IEEE (2023)","DOI":"10.1109\/ICRA48891.2023.10160538"},{"key":"11_CR28","doi-asserted-by":"crossref","unstructured":"Mandal, S., Biswas, S., Balas, V.E., Shaw, R.N., Ghosh, A.: Motion prediction for autonomous vehicles from Lyft dataset using deep learning. In: 2020 IEEE 5th International Conference on Computing Communication and Automation (ICCCA), pp. 768\u2013773. IEEE (2020)","DOI":"10.1109\/ICCCA49541.2020.9250790"},{"key":"11_CR29","doi-asserted-by":"crossref","unstructured":"Mangalam, K., Adeli, E., Lee, K.H., Gaidon, A., Niebles, J.C.: Disentangling human dynamics for pedestrian locomotion forecasting with noisy supervision. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 2784\u20132793 (2020)","DOI":"10.1109\/WACV45572.2020.9093350"},{"key":"11_CR30","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"474","DOI":"10.1007\/978-3-030-58568-6_28","volume-title":"Computer Vision \u2013 ECCV 2020","author":"W Mao","year":"2020","unstructured":"Mao, W., Liu, M., Salzmann, M.: History repeats itself: human motion prediction via motion attention. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12359, pp. 474\u2013489. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58568-6_28"},{"key":"11_CR31","doi-asserted-by":"crossref","unstructured":"Mao, W., Liu, M., Salzmann, M., Li, H.: Learning trajectory dependencies for human motion prediction. In: IEEE\/CVF International Conference on Computer Vision (ICCV) (2019)","DOI":"10.1109\/ICCV.2019.00958"},{"key":"11_CR32","doi-asserted-by":"crossref","unstructured":"Martinez, J., Black, M.J., Romero, J.: On human motion prediction using recurrent neural networks. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2891\u20132900 (2017)","DOI":"10.1109\/CVPR.2017.497"},{"key":"11_CR33","doi-asserted-by":"crossref","unstructured":"Mart\u00ednez-Gonz\u00e1lez, A., Villamizar, M., Odobez, J.M.: Pose transformers (POTR): human motion prediction with non-autoregressive transformers. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 2276\u20132284 (2021)","DOI":"10.1109\/ICCVW54120.2021.00257"},{"issue":"64\u201367","key":"11_CR34","first-page":"2","volume":"5","author":"LR Medsker","year":"2001","unstructured":"Medsker, L.R., Jain, L.: Recurrent neural networks. Des. Appl. 5(64\u201367), 2 (2001)","journal-title":"Des. Appl."},{"key":"11_CR35","doi-asserted-by":"crossref","unstructured":"Nikdel, P., Mahdavian, M., Chen, M.: DMMGAN: diverse multi motion prediction of 3D human joints using attention-based generative adversarial network. In: 2023 IEEE International Conference on Robotics and Automation (ICRA), pp. 9938\u20139944. IEEE (2023)","DOI":"10.1109\/ICRA48891.2023.10160401"},{"key":"11_CR36","unstructured":"Noghre, G.A., Pazho, A.D., Katariya, V., Tabkhi, H.: Understanding the challenges and opportunities of pose-based anomaly detection. arXiv preprint arXiv:2303.05463 (2023)"},{"key":"11_CR37","unstructured":"Pazho, A.D., et al.: Ancilia: scalable intelligent video surveillance for the artificial intelligence of things. IEEE Internet Things J. (2023)"},{"key":"11_CR38","doi-asserted-by":"publisher","unstructured":"Saadatnejad, S., et\u00a0al.: A generic diffusion-based approach for 3D human pose prediction in the wild. In: 2023 IEEE International Conference on Robotics and Automation (ICRA), pp. 8246\u20138253 (2023). https:\/\/doi.org\/10.1109\/ICRA48891.2023.10160399","DOI":"10.1109\/ICRA48891.2023.10160399"},{"key":"11_CR39","doi-asserted-by":"crossref","unstructured":"Saadatnejad, S., et al.: A generic diffusion-based approach for 3D human pose prediction in the wild. In: 2023 IEEE International Conference on Robotics and Automation (ICRA), pp. 8246\u20138253. IEEE (2023)","DOI":"10.1109\/ICRA48891.2023.10160399"},{"key":"11_CR40","doi-asserted-by":"crossref","unstructured":"Sofianos, T., Sampieri, A., Franco, L., Galasso, F.: Space-time-separable graph convolutional network for pose forecasting. In: IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 11209\u201311218 (2021)","DOI":"10.1109\/ICCV48922.2021.01102"},{"key":"11_CR41","doi-asserted-by":"crossref","unstructured":"Tang, Y., et al.: Flag3D: a 3D fitness activity dataset with language instruction. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 22106\u201322117 (2023)","DOI":"10.1109\/CVPR52729.2023.02117"},{"key":"11_CR42","doi-asserted-by":"publisher","first-page":"6096","DOI":"10.1109\/TIP.2021.3089380","volume":"30","author":"H Wang","year":"2021","unstructured":"Wang, H., Dong, J., Cheng, B., Feng, J.: PVRED: a position-velocity recurrent encoder-decoder for human motion prediction. IEEE Trans. Image Process. 30, 6096\u20136106 (2021)","journal-title":"IEEE Trans. Image Process."},{"key":"11_CR43","doi-asserted-by":"crossref","unstructured":"Wang, Y., Wang, X., Jiang, P., Wang, F.: RNN-based human motion prediction via differential sequence representation. In: 2019 IEEE 6th International Conference on Cloud Computing and Intelligence Systems (CCIS), pp. 138\u2013143. IEEE (2019)","DOI":"10.1109\/CCIS48116.2019.9073734"},{"key":"11_CR44","doi-asserted-by":"crossref","unstructured":"Yang, X., Ren, X., Chen, M., Wang, L., Ding, Y.: Human posture recognition in intelligent healthcare. In: Journal of Physics: Conference Series, vol.\u00a01437, p. 012014. IOP Publishing (2020)","DOI":"10.1088\/1742-6596\/1437\/1\/012014"},{"key":"11_CR45","doi-asserted-by":"crossref","unstructured":"Yu, H., et al.: Towards realistic 3D human motion prediction with a spatio-temporal cross-transformer approach. IEEE Trans. Circuits Syst. Video Technol. (2023)","DOI":"10.1109\/TCSVT.2023.3255186"},{"key":"11_CR46","doi-asserted-by":"crossref","unstructured":"Yu, S., et al.: Regularity learning via explicit distribution modeling for skeletal video anomaly detection. IEEE Trans. Circuits Syst. Video Technol. (2023)","DOI":"10.1109\/TCSVT.2023.3296118"},{"key":"11_CR47","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1007\/978-3-030-58545-7_20","volume-title":"Computer Vision \u2013 ECCV 2020","author":"Y Yuan","year":"2020","unstructured":"Yuan, Y., Kitani, K.: DLow: diversifying latent flows for diverse human motion prediction. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12354, pp. 346\u2013364. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58545-7_20"},{"key":"11_CR48","doi-asserted-by":"crossref","unstructured":"Zhong, C., Hu, L., Zhang, Z., Ye, Y., Xia, S.: Spatio-temporal gating-adjacency GCN for human motion prediction. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 6447\u20136456 (2022)","DOI":"10.1109\/CVPR52688.2022.00634"},{"key":"11_CR49","doi-asserted-by":"crossref","unstructured":"Zimmermann, C., Welschehold, T., Dornhege, C., Burgard, W., Brox, T.: 3D human pose estimation in RGBD images for robotic task learning. In: 2018 IEEE International Conference on Robotics and Automation (ICRA), pp. 1986\u20131992. IEEE (2018)","DOI":"10.1109\/ICRA.2018.8462833"},{"key":"11_CR50","series-title":"Lecture Notes in Electrical Engineering","doi-asserted-by":"publisher","first-page":"593","DOI":"10.1007\/978-981-13-7123-3_69","volume-title":"Signal and Information Processing, Networking and Computers","author":"J Zou","year":"2019","unstructured":"Zou, J., et al.: Intelligent fitness trainer system based on human pose estimation. In: Sun, S., Fu, M., Xu, L. (eds.) ICSINC 2018. LNEE, vol. 550, pp. 593\u2013599. Springer, Singapore (2019). https:\/\/doi.org\/10.1007\/978-981-13-7123-3_69"}],"container-title":["Communications in Computer and Information Science","Robotics, Computer Vision and Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-59057-3_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,18]],"date-time":"2024-11-18T06:58:32Z","timestamp":1731913112000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-59057-3_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031590566","9783031590573"],"references-count":50,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-59057-3_11","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"8 May 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ROBOVIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Robotics, Computer Vision and Intelligent Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Rome","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":"25 February 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 February 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"robovis2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/robovis.scitevents.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}