{"id":"https://openalex.org/W7125928341","doi":"https://doi.org/10.1109/smc58881.2025.11342993","title":"SlimPose: Lightweight Multi-Person Pose Estimation via Multi-Scale Structural Feature Fusion and Selective Attention","display_name":"SlimPose: Lightweight Multi-Person Pose Estimation via Multi-Scale Structural Feature Fusion and Selective Attention","publication_year":2025,"publication_date":"2025-10-05","ids":{"openalex":"https://openalex.org/W7125928341","doi":"https://doi.org/10.1109/smc58881.2025.11342993"},"language":null,"primary_location":{"id":"doi:10.1109/smc58881.2025.11342993","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11342993","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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":null,"display_name":"Yandong Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yandong Liu","raw_affiliation_strings":["Central China Normal University,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Central China Normal University,Wuhan,China","institution_ids":["https://openalex.org/I40963666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124104127","display_name":"Jiangnan Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangnan Liu","raw_affiliation_strings":["Central China Normal University,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Central China Normal University,Wuhan,China","institution_ids":["https://openalex.org/I40963666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105786559","display_name":"X. Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Peng","raw_affiliation_strings":["Central China Normal University,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Central China Normal University,Wuhan,China","institution_ids":["https://openalex.org/I40963666"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124130214","display_name":"Shengnan Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengnan Hu","raw_affiliation_strings":["Central China Normal University,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Central China Normal University,Wuhan,China","institution_ids":["https://openalex.org/I40963666"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I40963666"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.61572281,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3084","last_page":"3089"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9783999919891357,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9783999919891357,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.003000000026077032,"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"}},{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.002400000113993883,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/pose","display_name":"Pose","score":0.7620999813079834},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5848000049591064},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.513700008392334},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4453999996185303},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4401000142097473},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.435699999332428},{"id":"https://openalex.org/keywords/computational-model","display_name":"Computational model","score":0.423799991607666},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3977999985218048},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.38109999895095825}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7692000269889832},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7639999985694885},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.7620999813079834},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6477000117301941},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5848000049591064},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.513700008392334},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4453999996185303},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4401000142097473},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.435699999332428},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.423799991607666},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3977999985218048},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.38109999895095825},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.36160001158714294},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.35350000858306885},{"id":"https://openalex.org/C160086991","wikidata":"https://www.wikidata.org/wiki/Q5939193","display_name":"Human visual system model","level":3,"score":0.3091000020503998},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.299699991941452},{"id":"https://openalex.org/C2986089797","wikidata":"https://www.wikidata.org/wiki/Q6501338","display_name":"Visual attention","level":3,"score":0.299699991941452},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2953000068664551},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.2858000099658966},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.2847999930381775},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C2989146674","wikidata":"https://www.wikidata.org/wiki/Q4818236","display_name":"Selective attention","level":3,"score":0.2754000127315521},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.2621999979019165},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.2565000057220459},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2563999891281128},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.2526000142097473},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.25060001015663147}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc58881.2025.11342993","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11342993","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W2559085405","https://openalex.org/W2916798096","https://openalex.org/W2962820842","https://openalex.org/W2962954622","https://openalex.org/W2963125010","https://openalex.org/W2963150697","https://openalex.org/W2963265461","https://openalex.org/W2964105113","https://openalex.org/W3034399482","https://openalex.org/W3108572544","https://openalex.org/W3138516171","https://openalex.org/W3171398643","https://openalex.org/W3172013121","https://openalex.org/W3176892444","https://openalex.org/W4226334005","https://openalex.org/W4229073080","https://openalex.org/W4280489393","https://openalex.org/W4312443924","https://openalex.org/W4379985979","https://openalex.org/W4384202713","https://openalex.org/W4393990792"],"related_works":[],"abstract_inverted_index":{"As":[0],"a":[1,42,73,97],"foundational":[2],"technology":[3],"for":[4],"human-centered":[5],"visual":[6],"understanding,":[7],"pose":[8,45],"estimation":[9,46],"has":[10],"broad":[11],"applications":[12],"in":[13,113,139],"human-computer":[14],"interaction,":[15],"behavior":[16],"recognition,":[17],"and":[18,123,142],"video":[19],"surveillance.":[20],"However,":[21],"existing":[22],"methods":[23],"often":[24],"incur":[25],"high":[26],"computational":[27,92,116],"costs,":[28],"limiting":[29],"their":[30],"deployment":[31],"on":[32,120],"resource-constrained":[33],"edge":[34],"devices.":[35],"In":[36],"this":[37],"paper,":[38],"we":[39,95],"propose":[40],"SlimPose,":[41],"lightweight":[43,134],"multi-person":[44],"framework":[47],"that":[48,80,101,127],"enhances":[49,102],"the":[50,68,103,121],"model\u2019s":[51,104],"ability":[52,105],"to":[53,106],"perceive":[54],"human":[55,69,83],"poses":[56],"across":[57],"scales":[58],"by":[59],"integrating":[60],"multi-scale":[61],"features":[62],"with":[63,110],"directional":[64],"structural":[65],"cues":[66],"of":[67],"body.":[70],"We":[71],"introduce":[72],"compact":[74],"Selective":[75],"Attentional":[76],"Feature":[77],"Gating":[78],"module":[79],"adaptively":[81],"emphasizes":[82],"regions":[84],"while":[85],"suppressing":[86],"background":[87],"features,":[88],"thereby":[89],"reducing":[90],"unnecessary":[91],"overhead.":[93],"Additionally,":[94],"design":[96],"Deconvolutional":[98],"Shift-Channel":[99],"Mixer":[100],"infer":[107],"occluded":[108],"keypoints":[109],"minimal":[111],"increase":[112],"parameters":[114],"or":[115],"cost.":[117],"Extensive":[118],"experiments":[119],"COCO":[122],"CrowdPose":[124],"datasets":[125],"demonstrate":[126],"our":[128],"approach":[129],"achieves":[130],"state-of-the-art":[131],"accuracy":[132],"among":[133],"bottom-up":[135],"methods,":[136],"particularly":[137],"excelling":[138],"crowded":[140],"scenes":[141],"under":[143],"resource-limited":[144],"conditions.":[145]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2026-01-29T00:00:00"}