{"id":"https://openalex.org/W2991653934","doi":"https://doi.org/10.1109/iccv.2019.00637","title":"STGAT: Modeling Spatial-Temporal Interactions for Human Trajectory Prediction","display_name":"STGAT: Modeling Spatial-Temporal Interactions for Human Trajectory Prediction","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2991653934","doi":"https://doi.org/10.1109/iccv.2019.00637","mag":"2991653934"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2019.00637","doi":"https://doi.org/10.1109/iccv.2019.00637","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2019.00637","pdf_url":null,"source":{"id":"https://openalex.org/S4363607764","display_name":"IEEE/CVF International Conference on Computer Vision (ICCV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Yingfan Huang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingfan Huang","raw_affiliation_strings":["Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Beijing, China","University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Beijing, China","institution_ids":["https://openalex.org/I4210090176"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028142499","display_name":"Huikun Bi","orcid":"https://orcid.org/0000-0002-0690-4663","observed_orcids":["https://orcid.org/0000-0002-0690-4663"]},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huikun Bi","raw_affiliation_strings":["Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Beijing, China","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100449625","display_name":"Zhaoxin Li","orcid":"https://orcid.org/0000-0002-8299-1076","observed_orcids":["https://orcid.org/0000-0002-8299-1076","https://orcid.org/0009-0004-5253-516X"]},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoxin Li","raw_affiliation_strings":["Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Beijing, China","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001141015","display_name":"Tianlu Mao","orcid":"https://orcid.org/0000-0003-2537-9873","observed_orcids":["https://orcid.org/0000-0003-2537-9873"]},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianlu Mao","raw_affiliation_strings":["Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Beijing, China","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100613098","display_name":"Zhaoqi Wang","orcid":"https://orcid.org/0000-0003-0894-8165","observed_orcids":["https://orcid.org/0000-0003-0894-8165","https://orcid.org/0009-0004-0987-0093"]},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoqi Wang","raw_affiliation_strings":["Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Beijing, China","institution_ids":["https://openalex.org/I4210090176"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":107.5887,"has_fulltext":false,"cited_by_count":691,"citation_normalized_percentile":{"value":0.9992272,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"6271","last_page":"6280"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.7383000254631042,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.7383000254631042,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.2093999981880188,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.011900000274181366,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/human-trajectory-prediction","display_name":"human trajectory prediction","score":0.9860000014305115},{"id":"https://openalex.org/keywords/pedestrian-movement","display_name":"pedestrian movement","score":0.5299999713897705},{"id":"https://openalex.org/keywords/spatial-temporal-interaction","display_name":"spatial-temporal interaction","score":0.8069999814033508},{"id":"https://openalex.org/keywords/graph-attention-networks","display_name":"graph attention networks","score":0.9070000052452087},{"id":"https://openalex.org/keywords/lstm-temporal-modeling","display_name":"LSTM temporal modeling","score":0.5799999833106995},{"id":"https://openalex.org/keywords/crowded-scenes","display_name":"crowded scenes","score":0.4959999918937683},{"id":"https://openalex.org/keywords/collision-avoidance","display_name":"collision avoidance","score":0.6779999732971191},{"id":"https://openalex.org/keywords/sequence-to-sequence-models","display_name":"sequence-to-sequence models","score":0.7360000014305115}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7894682884216309},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.7141358852386475},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6161015629768372},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.5868914127349854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5446443557739258},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5255407691001892},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5206636190414429},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.47138863801956177},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41319847106933594},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.27872225642204285},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.10110053420066833},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccv.2019.00637","doi":"https://doi.org/10.1109/iccv.2019.00637","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2019.00637","pdf_url":null,"source":{"id":"https://openalex.org/S4363607764","display_name":"IEEE/CVF International Conference on Computer Vision (ICCV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5142999887466431,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W116550656","https://openalex.org/W1514535095","https://openalex.org/W1586532344","https://openalex.org/W1947481528","https://openalex.org/W1968362113","https://openalex.org/W1970206276","https://openalex.org/W2102113734","https://openalex.org/W2109389234","https://openalex.org/W2116341502","https://openalex.org/W2125095437","https://openalex.org/W2130942839","https://openalex.org/W2133564696","https://openalex.org/W2134944993","https://openalex.org/W2139501017","https://openalex.org/W2145508099","https://openalex.org/W2146183743","https://openalex.org/W2149021215","https://openalex.org/W2157331557","https://openalex.org/W2164489414","https://openalex.org/W2167052694","https://openalex.org/W2244807774","https://openalex.org/W2293527364","https://openalex.org/W2418081708","https://openalex.org/W2418222507","https://openalex.org/W2424778531","https://openalex.org/W2518708963","https://openalex.org/W2519586580","https://openalex.org/W2525778437","https://openalex.org/W2532516272","https://openalex.org/W2576001372","https://openalex.org/W2579024533","https://openalex.org/W2593239008","https://openalex.org/W2607296803","https://openalex.org/W2740185481","https://openalex.org/W2750499125","https://openalex.org/W2766453196","https://openalex.org/W2766836212","https://openalex.org/W2794787653","https://openalex.org/W2798708518","https://openalex.org/W2799059904","https://openalex.org/W2963076818","https://openalex.org/W2963377215","https://openalex.org/W2963465695","https://openalex.org/W2964308564","https://openalex.org/W3152893301"],"related_works":["https://openalex.org/W3104041523","https://openalex.org/W4390444532","https://openalex.org/W3215707486","https://openalex.org/W3190542798","https://openalex.org/W4399533667","https://openalex.org/W4205855488","https://openalex.org/W7124456626","https://openalex.org/W4402149033","https://openalex.org/W4390204040","https://openalex.org/W3136999308"],"abstract_inverted_index":{"Human":[0],"trajectory":[1],"prediction":[2],"is":[3],"challenging":[4],"and":[5,13,20,36,126,128],"critical":[6],"in":[7,29,59],"various":[8],"applications":[9],"(e.g.,":[10],"autonomous":[11],"vehicles":[12],"social":[14],"robots).":[15],"Because":[16],"of":[17,22,45,53,82,107],"the":[18,23,26,46,50,85,90,104],"continuity":[19],"foresight":[21],"pedestrian":[24],"movements,":[25],"moving":[27],"pedestrians":[28,57],"crowded":[30],"spaces":[31],"will":[32],"consider":[33],"both":[34],"spatial":[35,86],"temporal":[37,51,105],"interactions":[38,54,87],"to":[39,78,102],"avoid":[40],"future":[41,80],"collisions.":[42],"However,":[43],"most":[44],"existing":[47],"methods":[48],"ignore":[49],"correlations":[52,106],"with":[55,111],"other":[56],"involved":[58],"a":[60,67,75],"scene.":[61],"In":[62],"this":[63],"work,":[64],"we":[65,97],"propose":[66],"Spatial-Temporal":[68],"Graph":[69],"Attention":[70],"network":[71],"(STGAT),":[72],"based":[73],"on":[74,119],"sequence-to-sequence":[76],"architecture":[77],"predict":[79],"trajectories":[81,133],"pedestrians.":[83,135],"Besides":[84],"captured":[88],"by":[89],"graph":[91],"attention":[92],"mechanism":[93],"at":[94],"each":[95],"time-step,":[96],"adopt":[98],"an":[99],"extra":[100],"LSTM":[101],"encode":[103],"interactions.":[108],"Through":[109],"comparisons":[110],"state-of-the-art":[112],"methods,":[113],"our":[114],"model":[115],"achieves":[116],"superior":[117],"performance":[118],"two":[120],"publicly":[121],"available":[122],"crowd":[123],"datasets":[124],"(ETH":[125],"UCY)":[127],"produces":[129],"more":[130],"\"socially\"":[131],"plausible":[132],"for":[134]},"counts_by_year":[{"year":2026,"cited_by_count":63},{"year":2025,"cited_by_count":135},{"year":2024,"cited_by_count":122},{"year":2023,"cited_by_count":125},{"year":2022,"cited_by_count":111},{"year":2021,"cited_by_count":100},{"year":2020,"cited_by_count":35}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2019-12-05T00:00:00"}