{"id":"https://openalex.org/W7135094800","doi":"https://doi.org/10.1109/access.2026.3673396","title":"HCA-YOLOv8: A Pedestrian Detection Model That Integrates Multi-Source Context-Aware Mechanisms","display_name":"HCA-YOLOv8: A Pedestrian Detection Model That Integrates Multi-Source Context-Aware Mechanisms","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7135094800","doi":"https://doi.org/10.1109/access.2026.3673396"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3673396","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3673396","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3673396","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Song Yang","orcid":"https://orcid.org/0000-0002-9875-7356"},"institutions":[{"id":"https://openalex.org/I156292868","display_name":"Dalian University of Foreign Languages","ror":"https://ror.org/008a8z393","country_code":"CN","type":"education","lineage":["https://openalex.org/I156292868"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Song Yang","raw_affiliation_strings":["School of Software, Dalian University of Foreign Languages, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0002-9875-7356","affiliations":[{"raw_affiliation_string":"School of Software, Dalian University of Foreign Languages, Dalian, China","institution_ids":["https://openalex.org/I156292868"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128836662","display_name":"Jiayao Xing","orcid":null},"institutions":[{"id":"https://openalex.org/I156292868","display_name":"Dalian University of Foreign Languages","ror":"https://ror.org/008a8z393","country_code":"CN","type":"education","lineage":["https://openalex.org/I156292868"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiayao Xing","raw_affiliation_strings":["School of Software, Dalian University of Foreign Languages, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software, Dalian University of Foreign Languages, Dalian, China","institution_ids":["https://openalex.org/I156292868"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128918940","display_name":"Zhaoxia Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I156292868","display_name":"Dalian University of Foreign Languages","ror":"https://ror.org/008a8z393","country_code":"CN","type":"education","lineage":["https://openalex.org/I156292868"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoxia Liu","raw_affiliation_strings":["School of Software, Dalian University of Foreign Languages, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software, Dalian University of Foreign Languages, Dalian, China","institution_ids":["https://openalex.org/I156292868"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021719082","display_name":"Xuchen Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I156292868","display_name":"Dalian University of Foreign Languages","ror":"https://ror.org/008a8z393","country_code":"CN","type":"education","lineage":["https://openalex.org/I156292868"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuchen Zheng","raw_affiliation_strings":["School of Software, Dalian University of Foreign Languages, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software, Dalian University of Foreign Languages, Dalian, China","institution_ids":["https://openalex.org/I156292868"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I156292868"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24664336,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"48487","last_page":"48503"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.26330000162124634,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.26330000162124634,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.12479999661445618,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.09279999881982803,"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/pedestrian","display_name":"Pedestrian","score":0.5447999835014343},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.5231999754905701},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.38029998540878296},{"id":"https://openalex.org/keywords/radar-tracker","display_name":"Radar tracker","score":0.319599986076355},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.2818000018596649}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7574999928474426},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.5447999835014343},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.5231999754905701},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5153999924659729},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48899999260902405},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.38029998540878296},{"id":"https://openalex.org/C32283439","wikidata":"https://www.wikidata.org/wiki/Q1407014","display_name":"Radar tracker","level":3,"score":0.319599986076355},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2818000018596649},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2370000034570694},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.23440000414848328}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3673396","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3673396","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:864f84c3652a426aa6849d82f2637af8","is_oa":true,"landing_page_url":"https://doaj.org/article/864f84c3652a426aa6849d82f2637af8","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 14, Pp 48487-48503 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3673396","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3673396","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"complex":[1,285],"and":[2,15,23,67,102,141,144,180,204,225,233,255,260,269,278],"dynamic":[3],"scenes,":[4],"pedestrian":[5,32,73,282],"detection":[6,21,33,213,283],"faces":[7],"significant":[8],"challenges,":[9],"including":[10,199],"large-scale":[11],"variations,":[12,133],"severe":[13],"occlusion,":[14],"strong":[16],"background":[17],"interference.":[18],"To":[19,79],"enhance":[20,81],"robustness":[22],"contextual":[24,117,290],"perception":[25,118],"capability,":[26],"this":[27,106],"paper":[28],"proposes":[29],"an":[30,49,276],"improved":[31],"framework":[34,112,121],"named":[35],"HCA-YOLOv8,":[36],"which":[37,166],"introduces":[38],"a":[39,84,108,159,293],"unified":[40,160,294],"holistic":[41],"context-aware":[42],"modeling":[43,88,186,239],"mechanism":[44,54,89],"within":[45,292],"the":[46,57,170,174,231,242,248,258,272],"YOLOv8":[47,175],"architecture.First,":[48],"efficient":[50],"channel":[51,65,96],"context":[52,87,110,127,146,185,238],"awareness":[53],"based":[55],"on":[56,195,257],"ECA":[58],"attention":[59,295],"is":[60,91,113,167],"adopted":[61],"to":[62,72,93,115],"capture":[63],"local":[64],"dependencies":[66],"strengthen":[68],"semantic":[69,97,152],"responses":[70],"related":[71],"structures":[74],"while":[75,187,264],"maintaining":[76,188,265],"computational":[77,270],"efficiency.":[78],"further":[80,229],"feature":[82],"representation,":[83],"channel\u2013space\u2013direction":[85],"collaborative":[86],"(CSD-Attention)":[90],"designed":[92],"jointly":[94],"model":[95,191],"dependencies,":[98],"spatial":[99],"saliency":[100],"distribution,":[101],"directional":[103],"structural":[104],"information.On":[105],"basis,":[107],"multi-source":[109,184],"enhancement":[111,135],"constructed":[114],"expand":[116],"capability.":[119],"This":[120],"integrates":[122],"three":[123],"complementary":[124,234],"modules:":[125],"multi-scale":[126],"fusion":[128],"(MSCF)":[129],"for":[130,138,149,281],"handling":[131],"scale":[132,245],"edge":[134],"module":[136],"(EEM)":[137],"strengthening":[139],"boundary":[140],"contour":[142],"information,":[143],"global":[145],"block":[147],"(GCB)":[148],"capturing":[150],"image-level":[151],"relationships.":[153],"These":[154],"modules":[155],"are":[156],"integrated":[157],"into":[158,169],"Holistic":[161],"Contextual":[162],"Attention":[163],"(HCA)":[164],"block,":[165],"embedded":[168],"BottleneckCSP":[171],"structure":[172],"of":[173,236],"backbone":[176],"through":[177],"residual":[178],"connections":[179],"LayerScale,":[181],"enabling":[182],"effective":[183,277],"nearly":[189],"unchanged":[190],"parameters.Extensive":[192],"experiments":[193],"conducted":[194],"five":[196],"public":[197],"datasets,":[198,262],"ICCV,":[200],"MOT17,":[201],"WiderPerson,":[202],"CrowdHuman,":[203],"KITTI,":[205],"demonstrate":[206],"that":[207],"HCA-YOLOv8":[208,274],"consistently":[209],"outperforms":[210],"several":[211],"mainstream":[212],"models":[214],"across":[215],"multiple":[216],"evaluation":[217],"metrics":[218],"such":[219],"as":[220,246],"Precision,":[221],"Recall,":[222],"F1-score,":[223],"mAP@0.5,":[224],"mAP@0.5:0.95.":[226],"Ablation":[227],"studies":[228],"verify":[230],"effectiveness":[232],"contributions":[235],"each":[237],"component.":[240],"With":[241],"same":[243],"parameter":[244],"YOLOv8s,":[247],"proposed":[249,273],"method":[250],"improves":[251],"mAP@0.5":[252],"by":[253,287],"12.89%":[254],"8.29%":[256],"CrowdHuman":[259],"KITTI":[261],"respectively,":[263],"stable":[266],"training":[267],"performance":[268],"efficiency.Overall,":[271],"provides":[275],"reliable":[279],"solution":[280],"in":[284],"scenes":[286],"integrating":[288],"multi-dimensional":[289],"information":[291],"framework.":[296]},"counts_by_year":[],"updated_date":"2026-04-03T16:38:21.277918","created_date":"2026-03-13T00:00:00"}