{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T07:00:23Z","timestamp":1743145223717,"version":"3.40.3"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031112164"},{"type":"electronic","value":"9783031112171"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-11217-1_16","type":"book-chapter","created":{"date-parts":[[2022,7,15]],"date-time":"2022-07-15T21:02:35Z","timestamp":1657918955000},"page":"214-228","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Astral: An Autoencoder-Based Model for\u00a0Pedestrian Trajectory Prediction of\u00a0Variable-Length"],"prefix":"10.1007","author":[{"given":"Yupeng","family":"Diao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiteng","family":"Su","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ximu","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xu","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuncheng","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Han","family":"Su","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,7,16]]},"reference":[{"key":"16_CR1","doi-asserted-by":"crossref","unstructured":"Alahi, A., Goel, K., Ramanathan, V., Robicquet, A., Fei-Fei, L., Savarese, S.: Social LSTM: human trajectory prediction in crowded spaces. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 961\u2013971 (2016)","DOI":"10.1109\/CVPR.2016.110"},{"key":"16_CR2","doi-asserted-by":"crossref","unstructured":"Antonini, G., Bierlaire, M., Weber, M.: Discrete Choice Models of Pedestrian Walking Behavior. Transp. Res. Part B Methodol. 40, 667\u2013687 (2006)","DOI":"10.1016\/j.trb.2005.09.006"},{"key":"16_CR3","unstructured":"Bahdanau, D., Cho, K., Bengio, Y.: Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473 (2014)"},{"key":"16_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"422","DOI":"10.1007\/978-3-030-73194-6_29","volume-title":"Database Systems for Advanced Applications","author":"X Chen","year":"2021","unstructured":"Chen, X., et al.: SCSG attention: a self-centered star graph with attention for pedestrian trajectory prediction. In: Jensen, C.S., et al. (eds.) DASFAA 2021. LNCS, vol. 12681, pp. 422\u2013438. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-73194-6_29"},{"key":"16_CR5","doi-asserted-by":"publisher","unstructured":"Ferrer, G., Garrell, A., Sanfeliu, A.: Robot companion: a social-force based approach with human awareness-navigation in crowded environments. In: 2013 IEEE\/RSJ International Conference on Intelligent Robots and Systems, pp. 1688\u20131694 (2013). https:\/\/doi.org\/10.1109\/IROS.2013.6696576","DOI":"10.1109\/IROS.2013.6696576"},{"key":"16_CR6","doi-asserted-by":"crossref","unstructured":"Gupta, A., Johnson, J., Fei-Fei, L., Savarese, S., Alahi, A.: Social GAN: socially acceptable trajectories with generative adversarial networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2255\u20132264 (2018)","DOI":"10.1109\/CVPR.2018.00240"},{"key":"16_CR7","unstructured":"Haddad, S., Wu, M., Wei, H., Lam, S.K.: Situation-aware pedestrian trajectory prediction with spatio-temporal attention model. arXiv preprint arXiv:1902.05437 (2019)"},{"issue":"1","key":"16_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1287\/trsc.1040.0108","volume":"39","author":"D Helbing","year":"2005","unstructured":"Helbing, D., Buzna, L., Johansson, A., Werner, T.: Self-organized pedestrian crowd dynamics: experiments, simulations, and design solutions. Transpo. Sci. 39(1), 1\u201324 (2005)","journal-title":"Transpo. Sci."},{"issue":"5","key":"16_CR9","doi-asserted-by":"publisher","first-page":"4282","DOI":"10.1103\/PhysRevE.51.4282","volume":"51","author":"D Helbing","year":"1995","unstructured":"Helbing, D., Molnar, P.: Social force model for pedestrian dynamics. Phys. Rev. E 51(5), 4282 (1995)","journal-title":"Phys. Rev. E"},{"issue":"8","key":"16_CR10","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural computation 9(8), 1735\u20131780 (1997)","journal-title":"Neural computation"},{"key":"16_CR11","doi-asserted-by":"crossref","unstructured":"Leal-Taix\u00e9, L., Fenzi, M., Kuznetsova, A., Rosenhahn, B., Savarese, S.: Learning an image-based motion context for multiple people tracking. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3542\u20133549 (2014)","DOI":"10.1109\/CVPR.2014.453"},{"key":"16_CR12","doi-asserted-by":"publisher","unstructured":"Miao, Y., Gowayyed, M., Metze, F.: EESEN: End-to-end speech recognition using deep RNN models and WFST-based decoding. In: 2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU), pp. 167\u2013174 (2015). https:\/\/doi.org\/10.1109\/ASRU.2015.7404790","DOI":"10.1109\/ASRU.2015.7404790"},{"key":"16_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"452","DOI":"10.1007\/978-3-642-15549-9_33","volume-title":"Computer Vision \u2013 ECCV 2010","author":"S Pellegrini","year":"2010","unstructured":"Pellegrini, S., Ess, A., Van Gool, L.: Improving data association by joint modeling of pedestrian trajectories and groupings. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010. LNCS, vol. 6311, pp. 452\u2013465. Springer, Heidelberg (2010). https:\/\/doi.org\/10.1007\/978-3-642-15549-9_33"},{"issue":"AVEC14","key":"16_CR14","doi-asserted-by":"publisher","first-page":"53","DOI":"10.20485\/jsaeijae.7.AVEC14_53","volume":"7","author":"P Raksincharoensak","year":"2016","unstructured":"Raksincharoensak, P., Hasegawa, T., Nagai, M.: Motion planning and control of autonomous driving intelligence system based on risk potential optimization framework. Int. J. Autom. Eng. 7(AVEC14), 53\u201360 (2016)","journal-title":"Int. J. Autom. Eng."},{"key":"16_CR15","doi-asserted-by":"crossref","unstructured":"Sadeghian, A., Kosaraju, V., Sadeghian, A., Hirose, N., Rezatofighi, H., Savarese, S.: Sophie: an attentive GAN for predicting paths compliant to social and physical constraints. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1349\u20131358 (2019)","DOI":"10.1109\/CVPR.2019.00144"},{"key":"16_CR16","doi-asserted-by":"publisher","unstructured":"Shang, L., Lu, Z., Li, H.: Neural responding machine for short-text conversation. In: Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pp. 1577\u20131586. Association for Computational Linguistics, Beijing, China, July 2015. https:\/\/doi.org\/10.3115\/v1\/P15-1152, https:\/\/aclanthology.org\/P15-1152","DOI":"10.3115\/v1\/P15-1152"},{"key":"16_CR17","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1613\/jair.1.12007","volume":"69","author":"F Stahlberg","year":"2020","unstructured":"Stahlberg, F.: Neural machine translation: a review. J. Artif. Intell. Res. 69, 343\u2013418 (2020)","journal-title":"J. Artif. Intell. Res."},{"key":"16_CR18","unstructured":"Sutskever, I., Vinyals, O., Le, Q.V.: Sequence to sequence learning with neural networks. In: Advances in neural information processing systems, pp. 3104\u20133112 (2014)"},{"issue":"3","key":"16_CR19","doi-asserted-by":"publisher","first-page":"1160","DOI":"10.1145\/1141911.1142008","volume":"25","author":"A Treuille","year":"2006","unstructured":"Treuille, A., Cooper, S., Popovi\u0107, Z.: Continuum crowds. ACM Trans. Graph. 25(3), 1160\u20131168 (2006)","journal-title":"ACM Trans. Graph."},{"key":"16_CR20","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, pp. 5998\u20136008 (2017)"},{"key":"16_CR21","doi-asserted-by":"publisher","unstructured":"Xiong, W., Wu, L., Alleva, F., Droppo, J., Huang, X., Stolcke, A.: The microsoft 2017 conversational speech recognition system. In: 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 5934\u20135938 (2018). https:\/\/doi.org\/10.1109\/ICASSP.2018.8461870","DOI":"10.1109\/ICASSP.2018.8461870"}],"container-title":["Lecture Notes in Computer Science","Database Systems for Advanced Applications. DASFAA 2022 International Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-11217-1_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T16:11:21Z","timestamp":1710259881000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-11217-1_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031112164","9783031112171"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-11217-1_16","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"16 July 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DASFAA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Database Systems for Advanced Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 April 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 April 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dasfaa2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.dasfaa2022.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"543","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"72","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"76","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"13% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"6","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Conference was originally planned to take place in Hyberabad, India. 24 other papers are included in the volume.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}