{"id":"https://openalex.org/W4308236034","doi":"https://doi.org/10.1109/icip46576.2022.9897790","title":"Boosting the Performance of Weakly-Supervised 3d Human Pose Estimators With Pose Prior Regularizers","display_name":"Boosting the Performance of Weakly-Supervised 3d Human Pose Estimators With Pose Prior Regularizers","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4308236034","doi":"https://doi.org/10.1109/icip46576.2022.9897790"},"language":"en","primary_location":{"id":"doi:10.1109/icip46576.2022.9897790","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897790","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","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 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5016841608","display_name":"Lawrence Amadi","orcid":"https://orcid.org/0000-0003-2913-4056"},"institutions":[{"id":"https://openalex.org/I180949307","display_name":"Illinois Institute of Technology","ror":"https://ror.org/037t3ry66","country_code":"US","type":"education","lineage":["https://openalex.org/I180949307"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Lawrence Amadi","raw_affiliation_strings":["Illinois Institute of Technology Computer Science,Visual Computing Lab","Visual Computing Lab, Illinois Institute of Technology Computer Science"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Illinois Institute of Technology Computer Science,Visual Computing Lab","institution_ids":["https://openalex.org/I4210090176"]},{"raw_affiliation_string":"Visual Computing Lab, Illinois Institute of Technology Computer Science","institution_ids":["https://openalex.org/I180949307"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023698748","display_name":"Gady Agam","orcid":null},"institutions":[{"id":"https://openalex.org/I180949307","display_name":"Illinois Institute of Technology","ror":"https://ror.org/037t3ry66","country_code":"US","type":"education","lineage":["https://openalex.org/I180949307"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Gady Agam","raw_affiliation_strings":["Illinois Institute of Technology Computer Science,Visual Computing Lab","Visual Computing Lab, Illinois Institute of Technology Computer Science"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Illinois Institute of Technology Computer Science,Visual Computing Lab","institution_ids":["https://openalex.org/I4210090176"]},{"raw_affiliation_string":"Visual Computing Lab, Illinois Institute of Technology Computer Science","institution_ids":["https://openalex.org/I180949307"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3698,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.67992448,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1791","last_page":"1795"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":1.0,"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":1.0,"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/T11227","display_name":"Diabetic Foot Ulcer Assessment and Management","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2712","display_name":"Endocrinology, Diabetes and Metabolism"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9904999732971191,"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/overfitting","display_name":"Overfitting","score":0.8388332724571228},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7419251203536987},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7333388328552246},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.7309591770172119},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6467195153236389},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5050337910652161},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4998588562011719},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42400062084198},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33968386054039},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1588326096534729},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.15361273288726807},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11538180708885193}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8388332724571228},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7419251203536987},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7333388328552246},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.7309591770172119},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6467195153236389},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5050337910652161},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4998588562011719},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42400062084198},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33968386054039},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1588326096534729},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.15361273288726807},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11538180708885193}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip46576.2022.9897790","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897790","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","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 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1943191679","https://openalex.org/W2101032778","https://openalex.org/W2612706635","https://openalex.org/W2756050327","https://openalex.org/W2795089319","https://openalex.org/W2809890486","https://openalex.org/W2962896489","https://openalex.org/W2963441822","https://openalex.org/W2963475767","https://openalex.org/W2963590054","https://openalex.org/W2970285700","https://openalex.org/W2981660954","https://openalex.org/W2981691949","https://openalex.org/W2984313141","https://openalex.org/W3009246422","https://openalex.org/W3034448411","https://openalex.org/W3034581612","https://openalex.org/W3034884701","https://openalex.org/W3034971010","https://openalex.org/W3107620906","https://openalex.org/W3114358515","https://openalex.org/W3169891778","https://openalex.org/W3174042812","https://openalex.org/W3183950642","https://openalex.org/W3205327953","https://openalex.org/W3205873049"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2393964553","https://openalex.org/W2989932438","https://openalex.org/W4387297750","https://openalex.org/W2186333919","https://openalex.org/W3082059448","https://openalex.org/W4313640622"],"abstract_inverted_index":{"This":[0],"work":[1],"aims":[2],"to":[3,61,100,111],"boost":[4],"the":[5,62,73,85,120],"performance":[6],"of":[7,79,87,127],"3D":[8,23,81,88,131],"human":[9],"pose":[10,33,46,89],"estimators":[11],"trained":[12],"in":[13,68],"a":[14],"weakly-supervised":[15,69],"setting":[16],"where":[17],"there":[18],"are":[19,45,93],"much":[20],"fewer":[21],"annotated":[22,128],"poses":[24],"than":[25],"unlabeled":[26],"video":[27],"data.":[28],"We":[29,106],"formulate":[30],"two":[31],"self-supervised":[32],"prior":[34],"regularizers":[35,92],"(PPR)":[36],"-":[37],"bone":[38,56,74],"proportion":[39],"and":[40,49,76,96,115],"joint":[41,77],"mobility":[42],"constraints":[43],"that":[44,117],"translation,":[47],"scale,":[48],"rotation":[50],"invariant.":[51],"These":[52],"regularizers,":[53],"combined":[54],"with":[55],"symmetry":[57],"loss,":[58],"reduce":[59],"overfitting":[60],"2D":[63],"reprojection":[64],"loss":[65],"commonly":[66],"used":[67],"settings":[70],"by":[71,122,136],"optimizing":[72],"lengths":[75],"rotations":[78],"estimated":[80],"poses.":[82],"Consequently,":[83],"improving":[84,133],"accuracy":[86,135],"estimators.":[90],"The":[91],"network":[94,102,113],"independent":[95],"can":[97],"be":[98],"applied":[99],"any":[101],"architecture":[103],"without":[104],"modifications.":[105],"apply":[107],"our":[108],"proposed":[109],"PPR":[110],"VideoPose3D":[112],"[1]":[114],"show":[116],"it":[118],"decreases":[119],"MPJPE":[121],"24%":[123],"when":[124],"using":[125],"\u22645%":[126],"H36M":[129],"[2]":[130],"data,":[132],"state-of-the-art":[134],"7.9":[137],"mm.":[138]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
