{"id":"https://openalex.org/W7123453563","doi":"https://doi.org/10.1109/mmsp64401.2025.11324183","title":"HyperDiff: Hypergraph Guided Diffusion Model for 3D Human Pose Estimation","display_name":"HyperDiff: Hypergraph Guided Diffusion Model for 3D Human Pose Estimation","publication_year":2025,"publication_date":"2025-09-21","ids":{"openalex":"https://openalex.org/W7123453563","doi":"https://doi.org/10.1109/mmsp64401.2025.11324183"},"language":null,"primary_location":{"id":"doi:10.1109/mmsp64401.2025.11324183","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmsp64401.2025.11324183","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Workshop on Multimedia Signal Processing (MMSP)","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/A5122965346","display_name":"Bing Han","orcid":null},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bing Han","raw_affiliation_strings":["Nanjing University of Aeronautics and Astronautics,Nanjing,China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Aeronautics and Astronautics,Nanjing,China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087505633","display_name":"Yuhua Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhua Huang","raw_affiliation_strings":["Nanjing University of Aeronautics and Astronautics,Nanjing,China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Aeronautics and Astronautics,Nanjing,China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019391901","display_name":"Pan Gao","orcid":"https://orcid.org/0000-0002-4492-5430"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pan Gao","raw_affiliation_strings":["Nanjing University of Aeronautics and Astronautics,Nanjing,China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Aeronautics and Astronautics,Nanjing,China","institution_ids":["https://openalex.org/I9842412"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5122965346"],"corresponding_institution_ids":["https://openalex.org/I9842412"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.68927401,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"72","last_page":"77"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9682000279426575,"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":0.9682000279426575,"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/T12290","display_name":"Human Motion and Animation","score":0.013899999670684338,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.00279999990016222,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.8206999897956848},{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.6743999719619751},{"id":"https://openalex.org/keywords/articulated-body-pose-estimation","display_name":"Articulated body pose estimation","score":0.666700005531311},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.6395000219345093},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.57669997215271},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.49239999055862427},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.43549999594688416},{"id":"https://openalex.org/keywords/skeleton","display_name":"Skeleton (computer programming)","score":0.3968999981880188}],"concepts":[{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.8206999897956848},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.6743999719619751},{"id":"https://openalex.org/C22100474","wikidata":"https://www.wikidata.org/wiki/Q4800952","display_name":"Articulated body pose estimation","level":4,"score":0.666700005531311},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6657000184059143},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6563000082969666},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.6395000219345093},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.57669997215271},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5037000179290771},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.49239999055862427},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.43549999594688416},{"id":"https://openalex.org/C18969341","wikidata":"https://www.wikidata.org/wiki/Q1169129","display_name":"Skeleton (computer programming)","level":2,"score":0.3968999981880188},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3833000063896179},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.3434000015258789},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.31450000405311584},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.31189998984336853},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.31040000915527344},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.3001999855041504},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.2962999939918518},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.29280000925064087},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.29269999265670776},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2881999909877777},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.26840001344680786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mmsp64401.2025.11324183","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmsp64401.2025.11324183","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Workshop on Multimedia Signal Processing (MMSP)","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":38,"referenced_works":["https://openalex.org/W2101032778","https://openalex.org/W2307770531","https://openalex.org/W2612706635","https://openalex.org/W2892880750","https://openalex.org/W2916798096","https://openalex.org/W2948058585","https://openalex.org/W2963076818","https://openalex.org/W2964221239","https://openalex.org/W2964304707","https://openalex.org/W2987087879","https://openalex.org/W3034217102","https://openalex.org/W3035367723","https://openalex.org/W3037859578","https://openalex.org/W3085990079","https://openalex.org/W3136525061","https://openalex.org/W3173811519","https://openalex.org/W3175246890","https://openalex.org/W3175788243","https://openalex.org/W3178872387","https://openalex.org/W3202716970","https://openalex.org/W3205327953","https://openalex.org/W4280639678","https://openalex.org/W4283377921","https://openalex.org/W4312249545","https://openalex.org/W4313068951","https://openalex.org/W4323545075","https://openalex.org/W4382457852","https://openalex.org/W4383890459","https://openalex.org/W4386075813","https://openalex.org/W4386076485","https://openalex.org/W4390873166","https://openalex.org/W4390874574","https://openalex.org/W4393156217","https://openalex.org/W4393158891","https://openalex.org/W4401853819","https://openalex.org/W4402703028","https://openalex.org/W4402715909","https://openalex.org/W4411245088"],"related_works":[],"abstract_inverted_index":{"Monocular":[0],"3D":[1,51],"human":[2],"pose":[3,40,52],"estimation":[4,53],"(HPE)":[5],"often":[6],"encounters":[7],"challenges":[8],"such":[9],"as":[10,77],"depth":[11,70],"ambiguity":[12,71],"and":[13,72,111,114,125],"occlusion":[14],"during":[15],"the":[16,37,92,109],"2D-to-3D":[17],"lifting":[18],"process.":[19],"Additionally,":[20],"traditional":[21],"methods":[22],"may":[23],"overlook":[24],"multi-scale":[25],"skeleton":[26,30],"features":[27],"when":[28],"utilizing":[29],"structure":[31],"information,":[32],"which":[33,56],"can":[34,115],"negatively":[35],"impact":[36],"accuracy":[38],"of":[39],"estimation.":[41],"To":[42],"address":[43],"these":[44],"challenges,":[45],"this":[46],"paper":[47],"introduces":[48],"a":[49,78],"novel":[50],"method,":[54],"HyperDiff,":[55],"integrates":[57],"diffusion":[58,63],"models":[59],"with":[60],"HyperGCN.":[61],"The":[62],"model":[64,85],"effectively":[65],"captures":[66],"data":[67],"uncertainty,":[68],"alleviating":[69],"occlusion.":[73],"Meanwhile,":[74],"HyperGCN,":[75],"serving":[76],"denoiser,":[79],"employs":[80],"multi-granularity":[81],"structures":[82],"to":[83,118,122],"accurately":[84],"high-order":[86],"correlations":[87],"between":[88],"joints.":[89],"This":[90],"improves":[91],"model\u2019s":[93],"denoising":[94],"capability":[95],"especially":[96],"for":[97],"complex":[98],"poses.":[99],"Experimental":[100],"results":[101],"demonstrate":[102],"that":[103],"HyperDiff":[104],"achieves":[105],"state-of-the-art":[106],"performance":[107,124],"on":[108],"Human3.6M":[110],"MPI-INF-3DHP":[112],"datasets":[113],"flexibly":[116],"adapt":[117],"varying":[119],"computational":[120],"resources":[121],"balance":[123],"efficiency.":[126],"Code":[127],"is":[128],"released":[129],"at":[130],"https://github.com/IHENL/HyperDiff":[131]},"counts_by_year":[],"updated_date":"2026-01-14T23:44:37.837170","created_date":"2026-01-14T00:00:00"}
