{"id":"https://openalex.org/W4224920173","doi":"https://doi.org/10.1109/icassp43922.2022.9746998","title":"Binary Dense Predictors for Human Pose Estimation Based on Dynamic Thresholds and Filtering","display_name":"Binary Dense Predictors for Human Pose Estimation Based on Dynamic Thresholds and Filtering","publication_year":2022,"publication_date":"2022-04-27","ids":{"openalex":"https://openalex.org/W4224920173","doi":"https://doi.org/10.1109/icassp43922.2022.9746998"},"language":"en","primary_location":{"id":"doi:10.1109/icassp43922.2022.9746998","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9746998","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5063636157","display_name":"Xingrun Xing","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingrun Xing","raw_affiliation_strings":["Beihang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045163085","display_name":"Yalong Jiang","orcid":"https://orcid.org/0000-0001-7224-6067"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yalong Jiang","raw_affiliation_strings":["Beihang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015525872","display_name":"Baochang Zhang","orcid":"https://orcid.org/0000-0001-7396-6218"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baochang Zhang","raw_affiliation_strings":["Beihang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024501453","display_name":"Wenrui Ding","orcid":"https://orcid.org/0000-0001-5490-4724"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenrui Ding","raw_affiliation_strings":["Beihang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028491176","display_name":"Yangguang Li","orcid":"https://orcid.org/0000-0002-9696-8192"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yangguang Li","raw_affiliation_strings":["SenseTime Group"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SenseTime Group","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101914194","display_name":"Hongguang Li","orcid":"https://orcid.org/0000-0002-9386-8137"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongguang Li","raw_affiliation_strings":["Beihang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091061106","display_name":"Huan Peng","orcid":"https://orcid.org/0000-0001-6799-946X"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huan Peng","raw_affiliation_strings":["Huazhong University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":null,"first_page":"1705","last_page":"1709"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9970999956130981,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9968000054359436,"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/computer-science","display_name":"Computer science","score":0.8039887547492981},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7991055250167847},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7737021446228027},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.7328786849975586},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6778804063796997},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.5890911221504211},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.562278151512146},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5553040504455566},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5458659529685974},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12226137518882751}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8039887547492981},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7991055250167847},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7737021446228027},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.7328786849975586},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6778804063796997},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5890911221504211},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.562278151512146},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5553040504455566},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5458659529685974},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12226137518882751},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp43922.2022.9746998","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9746998","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W2080873731","https://openalex.org/W2300242332","https://openalex.org/W2307770531","https://openalex.org/W2319920447","https://openalex.org/W2578797046","https://openalex.org/W2887447938","https://openalex.org/W2916798096","https://openalex.org/W2951392520","https://openalex.org/W2952819818","https://openalex.org/W2962730651","https://openalex.org/W2963402313","https://openalex.org/W2964062189","https://openalex.org/W3018278400","https://openalex.org/W3034742259","https://openalex.org/W3034750257","https://openalex.org/W3035232708","https://openalex.org/W3088524643","https://openalex.org/W3102288316","https://openalex.org/W3104151879","https://openalex.org/W3119697406","https://openalex.org/W3175730059","https://openalex.org/W3176892444","https://openalex.org/W3177491619","https://openalex.org/W6639102338","https://openalex.org/W6698200048","https://openalex.org/W6700264148","https://openalex.org/W6730410022","https://openalex.org/W6735463952","https://openalex.org/W6750378959","https://openalex.org/W6760224987","https://openalex.org/W6783467810","https://openalex.org/W6788473708"],"related_works":["https://openalex.org/W1542224353","https://openalex.org/W1661087619","https://openalex.org/W2378211422","https://openalex.org/W2116854923","https://openalex.org/W2750730210","https://openalex.org/W2236974868","https://openalex.org/W4312766348","https://openalex.org/W2952127465","https://openalex.org/W2028276520","https://openalex.org/W2164628286"],"abstract_inverted_index":{"Binary":[0],"neural":[1],"networks":[2],"(BNNs)":[3],"contribute":[4],"a":[5,41,73,80,121],"lot":[6],"to":[7,50,65,89,108,119],"the":[8,33,52,87,99,109,112,130,133,142],"efficiency":[9],"of":[10,35],"image":[11],"classification":[12],"models.":[13,60],"However,":[14],"in":[15,25,72,86,98],"dense":[16],"predication":[17],"tasks":[18],"such":[19],"as":[20],"human":[21,76],"pose":[22,77],"estimation,":[23],"predictions":[24],"different":[26,122],"locations":[27],"are":[28,117],"coupled":[29],"and":[30,45,57,68,138],"rely":[31],"on":[32,141],"extraction":[34],"features":[36],"across":[37],"entire":[38],"images.":[39],"As":[40],"result,":[42],"more":[43],"robust":[44],"adaptive":[46],"binarization":[47,71,92,103,123],"is":[48,84],"required":[49],"bridge":[51],"performance":[53],"gap":[54],"between":[55],"binarized":[56],"full":[58],"precision":[59],"We":[61],"propose":[62],"two":[63],"approaches":[64],"conduct":[66],"image-aware":[67],"pixel-aware":[69],"dynamic":[70,82],"model":[74],"for":[75,94,104,125,146],"estimation.":[78],"Firstly,":[79],"simplified":[81],"thresholding":[83],"leveraged":[85],"backbone":[88],"determine":[90,120],"unique":[91],"thresholds":[93],"each":[95,105,126],"image.":[96],"Secondly,":[97],"decoder,":[100],"we":[101],"decouple":[102],"pixel":[106],"according":[107],"activations":[110],"surrounding":[111],"pixel.":[113,127],"Dynamic":[114],"filtering":[115],"modules":[116],"proposed":[118,134],"strategy":[124],"Compared":[128],"with":[129],"strong":[131],"baselines,":[132],"framework":[135],"improves":[136],"5.2%":[137],"3.6%":[139],"mAP":[140],"COCO":[143],"test-dev":[144],"benchmark":[145],"ResNet-18/34":[147],"architectures":[148],"respectively.":[149]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}