{"id":"https://openalex.org/W4306317336","doi":"https://doi.org/10.1145/3511808.3557455","title":"Social Graph Transformer Networks for Pedestrian Trajectory Prediction in Complex Social Scenarios","display_name":"Social Graph Transformer Networks for Pedestrian Trajectory Prediction in Complex Social Scenarios","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4306317336","doi":"https://doi.org/10.1145/3511808.3557455"},"language":"en","primary_location":{"id":"doi:10.1145/3511808.3557455","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557455","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},"type":"article","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":"https://openalex.org/A5100463079","display_name":"Yao Liu","orcid":"https://orcid.org/0000-0002-5271-0536"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Yao Liu","raw_affiliation_strings":["The University of New South Wales, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"The University of New South Wales, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052731721","display_name":"Lina Yao","orcid":"https://orcid.org/0000-0002-4149-839X"},"institutions":[{"id":"https://openalex.org/I1292875679","display_name":"Commonwealth Scientific and Industrial Research Organisation","ror":"https://ror.org/03qn8fb07","country_code":"AU","type":"funder","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4387156119"]},{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Lina Yao","raw_affiliation_strings":["CSIRO, The University of New South Wales, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"CSIRO, The University of New South Wales, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I31746571","https://openalex.org/I1292875679"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072317258","display_name":"Binghao Li","orcid":"https://orcid.org/0000-0001-8565-7287"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Binghao Li","raw_affiliation_strings":["The University of New South Wales, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"The University of New South Wales, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076107706","display_name":"Xianzhi Wang","orcid":"https://orcid.org/0000-0001-9582-3445"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Xianzhi Wang","raw_affiliation_strings":["The University of Technology Sydney, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"The University of Technology Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015779172","display_name":"Claude Sammut","orcid":"https://orcid.org/0000-0001-8873-5228"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Claude Sammut","raw_affiliation_strings":["The University of New South Wales, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"The University of New South Wales, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I31746571"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100463079"],"corresponding_institution_ids":["https://openalex.org/I31746571"],"apc_list":null,"apc_paid":null,"fwci":3.4358,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.9516129,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1339","last_page":"1349"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9998000264167786,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10370","display_name":"Traffic and Road Safety","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/computer-science","display_name":"Computer science","score":0.6658099889755249},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5869420766830444},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.5551130771636963},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4612973630428314},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.45902830362319946},{"id":"https://openalex.org/keywords/adjacency-matrix","display_name":"Adjacency matrix","score":0.44732919335365295},{"id":"https://openalex.org/keywords/adjacency-list","display_name":"Adjacency list","score":0.4462182819843292},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4362087547779083},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.35209038853645325},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.338120698928833},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32597970962524414},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.28520238399505615},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.152815580368042}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6658099889755249},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5869420766830444},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.5551130771636963},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4612973630428314},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.45902830362319946},{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.44732919335365295},{"id":"https://openalex.org/C110484373","wikidata":"https://www.wikidata.org/wiki/Q264398","display_name":"Adjacency list","level":2,"score":0.4462182819843292},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4362087547779083},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.35209038853645325},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.338120698928833},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32597970962524414},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28520238399505615},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.152815580368042},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3511808.3557455","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557455","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.4300000071525574,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1969839198","https://openalex.org/W2020209171","https://openalex.org/W2064675550","https://openalex.org/W2102605133","https://openalex.org/W2124609748","https://openalex.org/W2167052694","https://openalex.org/W2424778531","https://openalex.org/W2532516272","https://openalex.org/W2607296803","https://openalex.org/W2766836212","https://openalex.org/W2890001928","https://openalex.org/W2897079037","https://openalex.org/W2897688003","https://openalex.org/W2962687116","https://openalex.org/W2963001155","https://openalex.org/W2963076818","https://openalex.org/W2963353290","https://openalex.org/W2963945905","https://openalex.org/W2964136016","https://openalex.org/W2977619045","https://openalex.org/W2983205879","https://openalex.org/W2984200242","https://openalex.org/W2985871763","https://openalex.org/W2989851631","https://openalex.org/W3033920763","https://openalex.org/W3036244893","https://openalex.org/W3100327819","https://openalex.org/W3106257603","https://openalex.org/W3132535424","https://openalex.org/W3160050461","https://openalex.org/W3169575318","https://openalex.org/W3175646471","https://openalex.org/W4226225296"],"related_works":["https://openalex.org/W4213150077","https://openalex.org/W2369410163","https://openalex.org/W2982430984","https://openalex.org/W2059018062","https://openalex.org/W4206178588","https://openalex.org/W1991172810","https://openalex.org/W125803343","https://openalex.org/W2564285047","https://openalex.org/W4280593160","https://openalex.org/W2000173816"],"abstract_inverted_index":{"Pedestrian":[0],"trajectory":[1,90],"prediction":[2,49],"is":[3,140],"essential":[4],"for":[5,17,34,47,88],"many":[6],"modern":[7],"applications,":[8],"such":[9],"as":[10],"abnormal":[11],"motion":[12],"analysis":[13],"and":[14,32,59,74,86,112,131],"collision":[15],"avoidance":[16],"improved":[18],"traffic":[19],"safety.":[20],"Previous":[21],"studies":[22],"still":[23],"face":[24],"challenges":[25],"in":[26,134],"embracing":[27],"high":[28,36],"social":[29],"interaction,":[30],"dynamics,":[31],"multi-modality":[33],"achieving":[35],"accuracy":[37],"with":[38],"long-time":[39,89],"predictions.":[40,91],"We":[41],"propose":[42],"Social":[43],"Graph":[44,56],"Transformer":[45,60,87],"Networks":[46],"multi-modal":[48],"of":[50,98,110],"pedestrian":[51],"trajectories,":[52],"where":[53],"we":[54,78,94],"combine":[55],"Convolutional":[57],"Network":[58,61],"by":[62],"generating":[63],"stable":[64],"resolution":[65],"pseudo-images":[66],"from":[67],"Spatio-temporal":[68,84],"graphs":[69],"through":[70,142],"a":[71],"designed":[72],"stacking":[73],"interception":[75],"method.":[76],"Specifically,":[77],"adopt":[79],"adjacency":[80],"matrices":[81],"to":[82,103,113],"obtain":[83],"features":[85],"As":[92],"such,":[93],"retrain":[95],"the":[96,101,127],"advantages":[97],"both,":[99],"i.e.,":[100],"ability":[102],"aggregate":[104],"information":[105],"over":[106],"an":[107],"arbitrary":[108],"number":[109],"neighbors":[111],"conduct":[114],"complex":[115],"time-dependent":[116],"data":[117],"processing.":[118],"Our":[119],"experimental":[120],"results":[121],"show":[122],"that":[123],"our":[124],"model":[125],"reduces":[126],"final":[128],"displacement":[129],"error":[130],"achieves":[132],"state-of-the-art":[133],"multiple":[135],"metrics.":[136],"The":[137],"module's":[138],"effectiveness":[139],"demonstrated":[141],"ablation":[143],"experiments.":[144]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":2}],"updated_date":"2026-04-11T08:14:18.477133","created_date":"2025-10-10T00:00:00"}
