{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T18:37:34Z","timestamp":1771958254771,"version":"3.50.1"},"reference-count":27,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,12,4]],"date-time":"2023-12-04T00:00:00Z","timestamp":1701648000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,12,4]],"date-time":"2023-12-04T00:00:00Z","timestamp":1701648000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,12,4]]},"DOI":"10.1109\/robio58561.2023.10354667","type":"proceedings-article","created":{"date-parts":[[2023,12,22]],"date-time":"2023-12-22T19:20:45Z","timestamp":1703272845000},"page":"1-6","source":"Crossref","is-referenced-by-count":2,"title":["SA-GCNN: Spatial Attention Based Graph Convolutional Neural Network for Pedestrian Trajectory Prediction"],"prefix":"10.1109","author":[{"given":"Xuesong","family":"Li","sequence":"first","affiliation":[{"name":"Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences,CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems,Shenzhen,China"}]},{"given":"Qieshi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences,CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems,Shenzhen,China"}]},{"given":"Wanting","family":"Wang","sequence":"additional","affiliation":[{"name":"Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences,CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems,Shenzhen,China"}]},{"given":"Jian","family":"Tang","sequence":"additional","affiliation":[{"name":"Midea Group (Shanghai) Co., Ltd,China"}]},{"given":"Dong","family":"Liu","sequence":"additional","affiliation":[{"name":"Midea Group (Shanghai) Co., Ltd,China"}]},{"given":"Jun","family":"Cheng","sequence":"additional","affiliation":[{"name":"Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences,CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems,Shenzhen,China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01660"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00227"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.110"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr46437.2021.00888"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-11015-4_18"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/IROS47612.2022.9981486"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/IROS51168.2021.9636722"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2018.00196"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01443"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/IROS51168.2021.9636241"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48506.2021.9561480"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01236"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/IROS40897.2019.8967811"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00637"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2021.3056339"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00641"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01654"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP40778.2020.9191332"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.12328"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3176064"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"ref22","article-title":"Scene-LSTM: A model for human trajectory prediction","author":"Manh","year":"2018"},{"key":"ref23","article-title":"Social-BIGAT: Multimodal trajectory forecasting using bicycle-gan and graph attention networks","volume":"32","author":"Kosaraju","year":"2019","journal-title":"Advances in Neural Information Processing Systems (NIPS)"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00683"},{"key":"ref25","article-title":"An empirical evaluation of generic convolutional and recurrent networks for sequence modeling","author":"Bai","year":"2018"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2009.5459260"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-8659.2007.01089.x"}],"event":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","location":"Koh\u00a0Samui, Thailand","start":{"date-parts":[[2023,12,4]]},"end":{"date-parts":[[2023,12,9]]}},"container-title":["2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10354348\/10354529\/10354667.pdf?arnumber=10354667","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T23:12:09Z","timestamp":1705101129000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10354667\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,4]]},"references-count":27,"URL":"https:\/\/doi.org\/10.1109\/robio58561.2023.10354667","relation":{},"subject":[],"published":{"date-parts":[[2023,12,4]]}}}