{"id":"https://openalex.org/W4313037544","doi":"https://doi.org/10.1109/icarm54641.2022.9959497","title":"Self-paced Learning for Pedestrian Trajectory Prediction","display_name":"Self-paced Learning for Pedestrian Trajectory Prediction","publication_year":2022,"publication_date":"2022-07-09","ids":{"openalex":"https://openalex.org/W4313037544","doi":"https://doi.org/10.1109/icarm54641.2022.9959497"},"language":"en","primary_location":{"id":"doi:10.1109/icarm54641.2022.9959497","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarm54641.2022.9959497","pdf_url":null,"source":{"id":"https://openalex.org/S4363608069","display_name":"2022 International Conference on Advanced Robotics and Mechatronics (ICARM)","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":"2022 International Conference on Advanced Robotics and Mechatronics (ICARM)","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/A5082689644","display_name":"Ya Wu","orcid":"https://orcid.org/0000-0002-5376-4448"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ya Wu","raw_affiliation_strings":["Tongji University,School of Automotive Studies,Shanghai,China,200092"],"affiliations":[{"raw_affiliation_string":"Tongji University,School of Automotive Studies,Shanghai,China,200092","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100365130","display_name":"Bin Li","orcid":"https://orcid.org/0000-0001-8752-084X"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Li","raw_affiliation_strings":["Tongji University,School of Automotive Studies,Shanghai,China,200092"],"affiliations":[{"raw_affiliation_string":"Tongji University,School of Automotive Studies,Shanghai,China,200092","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100786637","display_name":"Ruiqi Zhang","orcid":"https://orcid.org/0000-0002-4729-8313"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruiqi Zhang","raw_affiliation_strings":["Tongji University,School of Automotive Studies,Shanghai,China,200092"],"affiliations":[{"raw_affiliation_string":"Tongji University,School of Automotive Studies,Shanghai,China,200092","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100323037","display_name":"Guang Chen","orcid":"https://orcid.org/0000-0002-7416-592X"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guang Chen","raw_affiliation_strings":["Tongji University,School of Automotive Studies,Shanghai,China,200092"],"affiliations":[{"raw_affiliation_string":"Tongji University,School of Automotive Studies,Shanghai,China,200092","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100450024","display_name":"Zhijun Li","orcid":"https://orcid.org/0000-0002-3909-488X"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhijun Li","raw_affiliation_strings":["University of Science and Technology of China,Department of Automation,China","Department of Automation, University of Science and Technology of China, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China,Department of Automation,China","institution_ids":["https://openalex.org/I126520041"]},{"raw_affiliation_string":"Department of Automation, University of Science and Technology of China, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021887616","display_name":"Zhengfa Liu","orcid":"https://orcid.org/0000-0003-3544-5694"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengfa Liu","raw_affiliation_strings":["Tongji University,School of Automotive Studies,Shanghai,China,200092"],"affiliations":[{"raw_affiliation_string":"Tongji University,School of Automotive Studies,Shanghai,China,200092","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5082689644"],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":0.2163,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.40727509,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"781","last_page":"786"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9994999766349792,"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":0.9994999766349792,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9976000189781189,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.9027572274208069},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.8854567408561707},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7894824743270874},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.686186671257019},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6241239309310913},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.616861879825592},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5145930051803589},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.41269588470458984},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.28959473967552185},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08677986264228821}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.9027572274208069},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.8854567408561707},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7894824743270874},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.686186671257019},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6241239309310913},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.616861879825592},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5145930051803589},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.41269588470458984},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28959473967552185},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08677986264228821},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"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/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icarm54641.2022.9959497","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarm54641.2022.9959497","pdf_url":null,"source":{"id":"https://openalex.org/S4363608069","display_name":"2022 International Conference on Advanced Robotics and Mechatronics (ICARM)","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":"2022 International Conference on Advanced Robotics and Mechatronics (ICARM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.550000011920929,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322449","display_name":"Tongji University","ror":"https://ror.org/03rc6as71"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1964590153","https://openalex.org/W2132984949","https://openalex.org/W2167052694","https://openalex.org/W2256388387","https://openalex.org/W2296073425","https://openalex.org/W2424778531","https://openalex.org/W2607296803","https://openalex.org/W2801667201","https://openalex.org/W2808064329","https://openalex.org/W2887842788","https://openalex.org/W2904549000","https://openalex.org/W2963001155","https://openalex.org/W2963697717","https://openalex.org/W2991653934","https://openalex.org/W3017247368","https://openalex.org/W3034722190","https://openalex.org/W3039515597","https://openalex.org/W3157891728","https://openalex.org/W3204079132","https://openalex.org/W4288287716","https://openalex.org/W4298018319","https://openalex.org/W6679390333","https://openalex.org/W6736021936","https://openalex.org/W6765361892"],"related_works":["https://openalex.org/W2392100589","https://openalex.org/W2512789322","https://openalex.org/W2101960027","https://openalex.org/W2197846993","https://openalex.org/W49697837","https://openalex.org/W2586575957","https://openalex.org/W3122828758","https://openalex.org/W2170799233","https://openalex.org/W2972620127","https://openalex.org/W2981141433"],"abstract_inverted_index":{"Pedestrian":[0],"trajectory":[1,58,80,94],"prediction":[2,59,95],"is":[3],"a":[4,7,50],"task":[5],"where":[6],"model":[8,106],"predicts":[9],"future":[10],"trajectories":[11],"of":[12,31,44,67,73],"the":[13,29,34,42,65,71,99],"target":[14],"agent":[15],"from":[16],"historical":[17],"clues":[18],"and":[19,69,97],"environment":[20],"clues.":[21],"However,":[22],"earlier":[23],"works":[24],"do":[25],"not":[26],"distinguish":[27],"between":[28],"level":[30],"difficulty":[32],"in":[33,90],"samples,":[35],"which":[36],"considers":[37],"all":[38],"samples":[39,68],"simultaneously.":[40],"For":[41],"purpose":[43],"solving":[45],"this":[46],"problem,":[47],"we":[48],"propose":[49],"novel":[51],"self-paced":[52],"based":[53],"learning":[54],"paradigm":[55],"for":[56,101],"pedestrian":[57,79],"tasks":[60],"that":[61],"can":[62,86],"simultaneously":[63],"measure":[64],"easiness":[66],"determine":[70],"order":[72],"samples.":[74],"Through":[75],"experiments":[76],"on":[77],"public":[78],"forecasting":[81],"benchmarks,":[82],"our":[83],"model-agnostic":[84],"approach":[85],"easily":[87],"be":[88],"used":[89],"combination":[91],"with":[92],"other":[93],"baselines,":[96],"improve":[98],"performance":[100],"different":[102],"baselines":[103],"without":[104],"increasing":[105],"complexity.":[107]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}