{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T08:40:31Z","timestamp":1774255231176,"version":"3.50.1"},"publisher-location":"Singapore","reference-count":14,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819785049","type":"print"},{"value":"9789819785056","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,11,7]],"date-time":"2024-11-07T00:00:00Z","timestamp":1730937600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,7]],"date-time":"2024-11-07T00:00:00Z","timestamp":1730937600000},"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\/978-981-97-8505-6_21","type":"book-chapter","created":{"date-parts":[[2024,11,6]],"date-time":"2024-11-06T22:04:35Z","timestamp":1730930675000},"page":"297-311","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Pedestrian Trajectory Prediction Using Spatio-Temporal VAE"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-8587-6974","authenticated-orcid":false,"given":"Qing","family":"Yu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-4156-1226","authenticated-orcid":false,"given":"Zhenwei","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-2571-9731","authenticated-orcid":false,"given":"Yaoyong","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhida","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wushouer","family":"Silamu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,11,7]]},"reference":[{"issue":"3","key":"21_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3583741","volume":"12","author":"C Mavrogiannis","year":"2023","unstructured":"Mavrogiannis, C., Baldini, F., Wang, A., et al.: Core challenges of social robot navigation: a survey [J]. ACM Trans. Hum. Robot Interact. 12(3), 1\u201339 (2023)","journal-title":"ACM Trans. Hum. Robot Interact."},{"key":"21_CR2","doi-asserted-by":"crossref","unstructured":"Gao, K., Li, X., Chen, B., et al.: Dual transformer based prediction for lane change intentions and trajectories in mixed traffic environment [J]. IEEE Trans. Intell. Transp. Syst. (2023)","DOI":"10.1109\/TITS.2023.3248842"},{"key":"21_CR3","doi-asserted-by":"crossref","unstructured":"Xu, Z., Yu, Q., Slamu, W., et al.: S-CGRU: an efficient model for pedestrian trajectory prediction [C]. In: International Conference on Neural Information Processing, pp. 244\u2013259. Springer Nature Singapore (2023)","DOI":"10.1007\/978-981-99-8141-0_19"},{"key":"21_CR4","doi-asserted-by":"crossref","unstructured":"Alahi, A., et al.: Social lstm: human trajectory prediction in crowded spaces. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2016)","DOI":"10.1109\/CVPR.2016.110"},{"key":"21_CR5","doi-asserted-by":"crossref","unstructured":"Gupta, A., et al.: Social gan: socially acceptable trajectories with generative adversarial networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2018)","DOI":"10.1109\/CVPR.2018.00240"},{"key":"21_CR6","doi-asserted-by":"crossref","unstructured":"Amirian, J., Hayet, J.-B., Pettr\u00e9, J.: Social ways: learning multi-modal distributions of pedestrian trajectories with gans. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (2019)","DOI":"10.1109\/CVPRW.2019.00359"},{"key":"21_CR7","unstructured":"Yu, C., et al.: Spatio-temporal graph transformer networks for pedestrian trajectory prediction. In: Computer Vision-ECCV 2020: 16th European Conference, Glasgow, UK, Aug 23\u201328, 2020, Proceedings, Part XII 16. Springer International Publishing (2020)"},{"key":"21_CR8","doi-asserted-by":"crossref","unstructured":"Giuliari, F., et al.: Transformer networks for trajectory forecasting. In: 2020 25th International Conference on Pattern Recognition (ICPR). IEEE (2021)","DOI":"10.1109\/ICPR48806.2021.9412190"},{"key":"21_CR9","doi-asserted-by":"crossref","unstructured":"Mohamed, A., et al.: Social-stgcnn: a social spatio-temporal graph convolutional neural network for human trajectory prediction. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2020)","DOI":"10.1109\/CVPR42600.2020.01443"},{"key":"21_CR10","doi-asserted-by":"crossref","unstructured":"Lv, K., Yuan, L.: SKGACN: social knowledge-guided graph attention convolutional network for human trajectory prediction. IEEE Trans. Instrum. Meas. (2023)","DOI":"10.1109\/TIM.2023.3283544"},{"key":"21_CR11","unstructured":"Salzmann, T., et al.: Trajectron++: dynamically-feasible trajectory forecasting with heterogeneous data. In: Computer Vision-ECCV 2020: 16th European Conference, Glasgow, UK, Aug 23\u201328, 2020, Proceedings, Part XVIII 16. Springer International Publishing (2020)"},{"key":"21_CR12","doi-asserted-by":"crossref","unstructured":"Xu, P., Hayet, J.-B., Karamouzas, I.: Socialvae: human trajectory prediction using timewise latents. In: European Conference on Computer Vision. Springer Nature Switzerland, Cham (2022)","DOI":"10.1007\/978-3-031-19772-7_30"},{"key":"21_CR13","doi-asserted-by":"crossref","unstructured":"Xu, B., et al.: Social-cvae: pedestrian trajectory prediction using conditional variational auto-encoder. In: International Conference on Neural Information Processing. Springer Nature Singapore (2023)","DOI":"10.1007\/978-981-99-8132-8_36"},{"key":"21_CR14","unstructured":"Becker, S., et al.: An evaluation of trajectory prediction approaches and notes on the trajnet benchmark. arXiv preprint arXiv:1805.07663 (2018)"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-8505-6_21","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,6]],"date-time":"2024-11-06T22:06:33Z","timestamp":1730930793000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-8505-6_21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,7]]},"ISBN":["9789819785049","9789819785056"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-8505-6_21","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,7]]},"assertion":[{"value":"7 November 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chinese Conference on Pattern Recognition and Computer Vision  (PRCV)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Urumqi","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","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":"18 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccprcv2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2024.prcv.cn\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}