{"id":"https://openalex.org/W4415003081","doi":"https://doi.org/10.1109/tmc.2025.3619573","title":"MPNet: Multi-Stage Progressive Convolutional Neural Networks for Trajectory Prediction","display_name":"MPNet: Multi-Stage Progressive Convolutional Neural Networks for Trajectory Prediction","publication_year":2025,"publication_date":"2025-10-09","ids":{"openalex":"https://openalex.org/W4415003081","doi":"https://doi.org/10.1109/tmc.2025.3619573"},"language":"en","primary_location":{"id":"doi:10.1109/tmc.2025.3619573","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmc.2025.3619573","pdf_url":null,"source":{"id":"https://openalex.org/S69141925","display_name":"IEEE Transactions on Mobile Computing","issn_l":"1536-1233","issn":["1536-1233","1558-0660","2161-9875"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Mobile Computing","raw_type":"journal-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/A5053317950","display_name":"Huihui Pan","orcid":"https://orcid.org/0000-0002-8931-1774"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Huihui Pan","raw_affiliation_strings":["Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074191109","display_name":"Changzhi Yang","orcid":"https://orcid.org/0000-0002-3908-1309"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changzhi Yang","raw_affiliation_strings":["Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jue Wang","orcid":"https://orcid.org/0009-0003-8461-8827"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jue Wang","raw_affiliation_strings":["Ningbo Institute of Intelligent Equipment Technology Company Ltd., Ningbo, China"],"affiliations":[{"raw_affiliation_string":"Ningbo Institute of Intelligent Equipment Technology Company Ltd., Ningbo, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077953778","display_name":"Yuanduo Hong","orcid":"https://orcid.org/0000-0002-8684-6765"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanduo Hong","raw_affiliation_strings":["Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5053317950"],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.29867717,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"25","issue":"3","first_page":"3905","last_page":"3919"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9952999949455261,"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":0.9430000185966492,"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":0.8483999967575073},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5953999757766724},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.5913000106811523},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4941999912261963},{"id":"https://openalex.org/keywords/displacement","display_name":"Displacement (psychology)","score":0.48080000281333923},{"id":"https://openalex.org/keywords/drone","display_name":"Drone","score":0.4562000036239624},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.3515999913215637},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.3476000130176544}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.8483999967575073},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8453999757766724},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5953999757766724},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.5913000106811523},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5285999774932861},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4941999912261963},{"id":"https://openalex.org/C107551265","wikidata":"https://www.wikidata.org/wiki/Q1458245","display_name":"Displacement (psychology)","level":2,"score":0.48080000281333923},{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.4562000036239624},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.3515999913215637},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.3476000130176544},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3336000144481659},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3181000053882599},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3172000050544739},{"id":"https://openalex.org/C167085575","wikidata":"https://www.wikidata.org/wiki/Q6803654","display_name":"Mean squared prediction error","level":2,"score":0.31029999256134033},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3082999885082245},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.28540000319480896},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.27320000529289246},{"id":"https://openalex.org/C2776505523","wikidata":"https://www.wikidata.org/wiki/Q4785468","display_name":"Plan (archaeology)","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2619999945163727},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.25450000166893005}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmc.2025.3619573","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmc.2025.3619573","pdf_url":null,"source":{"id":"https://openalex.org/S69141925","display_name":"IEEE Transactions on Mobile Computing","issn_l":"1536-1233","issn":["1536-1233","1558-0660","2161-9875"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Mobile Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1053508716","display_name":null,"funder_award_id":"YQ2024F008","funder_id":"https://openalex.org/F4320323085","funder_display_name":"Natural Science Foundation of Heilongjiang Province"},{"id":"https://openalex.org/G2180299318","display_name":null,"funder_award_id":"U23A20323","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6156751147","display_name":null,"funder_award_id":"62573153","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323085","display_name":"Natural Science Foundation of Heilongjiang Province","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2020209171","https://openalex.org/W2095339628","https://openalex.org/W2167052694","https://openalex.org/W2168921961","https://openalex.org/W2171935043","https://openalex.org/W2245440101","https://openalex.org/W2424778531","https://openalex.org/W2476548250","https://openalex.org/W2490270993","https://openalex.org/W2519586580","https://openalex.org/W2532516272","https://openalex.org/W2752782242","https://openalex.org/W2895598217","https://openalex.org/W2962687116","https://openalex.org/W2963001155","https://openalex.org/W2963853051","https://openalex.org/W2965217508","https://openalex.org/W2982745079","https://openalex.org/W2991653934","https://openalex.org/W3003906095","https://openalex.org/W3024186890","https://openalex.org/W3035096461","https://openalex.org/W3035692480","https://openalex.org/W3042505632","https://openalex.org/W3055613329","https://openalex.org/W3097237405","https://openalex.org/W3108908812","https://openalex.org/W3116651890","https://openalex.org/W3118240751","https://openalex.org/W3120437934","https://openalex.org/W3139491754","https://openalex.org/W3170697543","https://openalex.org/W4210457203","https://openalex.org/W4211165876","https://openalex.org/W4214593147","https://openalex.org/W4231697575","https://openalex.org/W4292794796","https://openalex.org/W4312599226","https://openalex.org/W4312688875","https://openalex.org/W4312898211","https://openalex.org/W4367663493","https://openalex.org/W4385245566","https://openalex.org/W4385413695","https://openalex.org/W4389609824","https://openalex.org/W4391097085","https://openalex.org/W4399563381","https://openalex.org/W4400644807","https://openalex.org/W4402716194","https://openalex.org/W4402754122","https://openalex.org/W4406457520","https://openalex.org/W4410608942","https://openalex.org/W4410949491","https://openalex.org/W4414173953"],"related_works":[],"abstract_inverted_index":{"Trajectory":[0],"prediction":[1,41,73],"is":[2,15],"a":[3,16,46,62,85,116,123,130,147],"continuing":[4],"concern":[5],"within":[6],"autonomous":[7],"vehicles.":[8],"Psychological":[9],"research":[10],"shows":[11],"that":[12,69,164],"pedestrian":[13],"traveling":[14],"cyclic":[17],"alternation.":[18],"Pedestrians":[19],"constantly":[20],"interact":[21],"with":[22,84,219],"their":[23],"surroundings,":[24],"including":[25],"social":[26],"agents":[27],"and":[28,31,103,129,174,184,193,213],"physical":[29],"environments,":[30],"plan":[32],"paths":[33],"to":[34,52,106,134,152,159],"achieve":[35,107],"goals.":[36],"Nevertheless,":[37],"most":[38],"existing":[39],"trajectory":[40,72,108,155],"methods":[42],"are":[43,91],"based":[44,92],"on":[45,93,115,181,188,195],"single-stage":[47],"design,":[48],"which":[49,98],"runs":[50],"counter":[51],"traffic":[53],"psychology":[54],"principles.":[55],"In":[56],"this":[57],"work,":[58],"we":[59,99,145],"present":[60],"MPNet,":[61],"novel":[63,117],"multi-stage":[64],"progressive":[65],"convolutional":[66],"neural":[67],"network":[68],"decomposes":[70],"complicated":[71],"into":[74],"multiple":[75],"manageable":[76],"components,":[77],"where":[78],"lightweight":[79],"sub-networks":[80,90,113],"handle":[81],"each":[82,143],"stage":[83],"divide-and-conquer":[86],"methodology.":[87],"Specifically,":[88],"our":[89,206],"the":[94,182,189,196],"encoder-decoder":[95],"architecture,":[96],"in":[97],"capture":[100],"interactive":[101],"information":[102,137],"estimate":[104],"goals":[105],"prediction.":[109],"The":[110],"communication":[111],"among":[112],"depends":[114],"cross-stage":[118],"fusion":[119,132],"design.":[120],"We":[121],"introduce":[122],"feedback":[124],"channel":[125],"mutual":[126],"attention":[127],"mechanism":[128],"cross-sub-network":[131],"unit":[133],"enable":[135],"efficient":[136],"sharing":[138],"across":[139],"different":[140],"stages.":[141],"At":[142],"stage,":[144],"develop":[146],"symmetric":[148],"gated":[149],"supervision":[150],"module":[151],"supervise":[153],"future":[154],"generation":[156],"from":[157],"coarse":[158],"fine.":[160],"Extensive":[161],"experiments":[162],"demonstrate":[163],"MPNet":[165],"achieves":[166],"state-of-the-art":[167],"performance,":[168],"reducing":[169],"Average":[170],"Displacement":[171,176],"Error":[172,177],"(ADE)":[173],"Final":[175],"(FDE)":[178],"by":[179,211,216],"5.6%/7.4%":[180],"ETH":[183],"UCY":[185],"Datasets,":[186],"7.5%/7.7%":[187],"Stanford":[190],"Drone":[191,198],"Dataset,":[192,199],"7.1%/22.5%":[194],"Intersection":[197],"while":[200],"maintaining":[201],"comparable":[202],"computational":[203],"complexity.":[204],"Additionally,":[205],"MPNet-Tiny":[207],"variant":[208],"reduces":[209],"parameters":[210],"90.5%":[212],"inference":[214],"time":[215],"1.83":[217],"seconds":[218],"competitive":[220],"accuracy.":[221]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
