{"id":"https://openalex.org/W3016061641","doi":"https://doi.org/10.1109/icassp40776.2020.9054508","title":"Position Constraint Loss For Fashion Landmark Estimation","display_name":"Position Constraint Loss For Fashion Landmark Estimation","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3016061641","doi":"https://doi.org/10.1109/icassp40776.2020.9054508","mag":"3016061641"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9054508","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054508","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5101566068","display_name":"Hong Liu","orcid":"https://orcid.org/0000-0002-7320-0260"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hong Liu","raw_affiliation_strings":["Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066016872","display_name":"Meijia Song","orcid":"https://orcid.org/0009-0000-9438-3716"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meijia Song","raw_affiliation_strings":["Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032675026","display_name":"Wei Shi","orcid":"https://orcid.org/0000-0002-3129-0296"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Shi","raw_affiliation_strings":["Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100445616","display_name":"Xia Li","orcid":"https://orcid.org/0000-0003-2284-1700"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xia Li","raw_affiliation_strings":["Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101566068"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.0977,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.36727835,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1868","last_page":"1872"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9980999827384949,"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":0.9980999827384949,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9905999898910522,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11448","display_name":"Face recognition and analysis","score":0.9905999898910522,"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/landmark","display_name":"Landmark","score":0.9706554412841797},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7183376550674438},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5837677121162415},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5635513067245483},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.535993218421936},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.530174732208252},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5111754536628723},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.4845258593559265},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4556286036968231},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4402422308921814},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.41309696435928345},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3277010917663574},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.21027812361717224},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15892016887664795}],"concepts":[{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.9706554412841797},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7183376550674438},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5837677121162415},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5635513067245483},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.535993218421936},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.530174732208252},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5111754536628723},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4845258593559265},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4556286036968231},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4402422308921814},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41309696435928345},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3277010917663574},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.21027812361717224},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15892016887664795},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9054508","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054508","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":36,"referenced_works":["https://openalex.org/W123584468","https://openalex.org/W181871703","https://openalex.org/W602397586","https://openalex.org/W1606177037","https://openalex.org/W1949942966","https://openalex.org/W1994769389","https://openalex.org/W2038147967","https://openalex.org/W2136391815","https://openalex.org/W2170881581","https://openalex.org/W2200092826","https://openalex.org/W2221507685","https://openalex.org/W2330154883","https://openalex.org/W2410358280","https://openalex.org/W2471768434","https://openalex.org/W2511502099","https://openalex.org/W2559085405","https://openalex.org/W2565639579","https://openalex.org/W2614562328","https://openalex.org/W2743772526","https://openalex.org/W2748310231","https://openalex.org/W2798734012","https://openalex.org/W2811481004","https://openalex.org/W2835003784","https://openalex.org/W2897195437","https://openalex.org/W2954388973","https://openalex.org/W2963402313","https://openalex.org/W2963516811","https://openalex.org/W2963598138","https://openalex.org/W2964211610","https://openalex.org/W2967819436","https://openalex.org/W3098379913","https://openalex.org/W6605026522","https://openalex.org/W6680285999","https://openalex.org/W6743682248","https://openalex.org/W6752751980","https://openalex.org/W6758606004"],"related_works":["https://openalex.org/W2056853153","https://openalex.org/W2057559274","https://openalex.org/W2026924879","https://openalex.org/W2005087563","https://openalex.org/W2378111931","https://openalex.org/W2052388267","https://openalex.org/W2950647290","https://openalex.org/W1968481813","https://openalex.org/W2620829895","https://openalex.org/W2356918560"],"abstract_inverted_index":{"Fashion":[0],"landmark":[1,28,49,66,95],"estimation":[2,29],"aims":[3],"at":[4],"locating":[5],"functional":[6],"key":[7],"points":[8],"of":[9,56,108,126,152],"clothes,":[10],"which":[11],"has":[12],"wide":[13],"potential":[14],"applications":[15],"in":[16,110],"electronic":[17],"commerce.":[18],"However,":[19],"due":[20],"to":[21,46,67,78,128],"the":[22,53,111,116,123,150],"occlusion":[23],"and":[24,32,72,81,141],"weak":[25],"outline":[26],"information,":[27],"occurs":[30],"outliers":[31],"duplicate":[33],"detection":[34],"problems.":[35],"To":[36],"alleviate":[37],"these":[38],"issues,":[39],"we":[40,121],"propose":[41],"Position":[42],"Constraint":[43],"Loss":[44],"(PCLoss)":[45],"constrain":[47],"error":[48],"locations":[50],"by":[51,100,155],"utilizing":[52],"position":[54,106,131],"relationship":[55],"landmarks.":[57,134],"Specifically,":[58],"PCLoss":[59,104],"adds":[60],"a":[61,156],"regularization":[62],"term":[63],"for":[64],"each":[65],"regularize":[68],"their":[69],"relative":[70],"positions,":[71],"it":[73],"can":[74,147],"be":[75],"easily":[76],"applied":[77],"both":[79],"regression":[80],"heatmap":[82],"based":[83],"methods":[84,146],"without":[85,114],"extra":[86],"computation":[87],"during":[88],"inference.":[89],"Unlike":[90],"existing":[91],"approaches":[92],"that":[93,144],"propagate":[94],"information":[96],"between":[97,133],"feature":[98],"layers":[99],"specific":[101],"network":[102,117],"structures,":[103],"introduces":[105],"relations":[107],"landmarks":[109],"label":[112],"space":[113],"modifying":[115],"structure.":[118],"In":[119],"addition,":[120],"leverage":[122],"skeleton-like":[124],"relation":[125],"clothing":[127],"further":[129],"strengthen":[130],"constraints":[132],"Extensive":[135],"experimental":[136],"results":[137],"on":[138],"DeepFashion,":[139],"FLD":[140],"FashionAI":[142],"demonstrate":[143],"our":[145],"effectively":[148],"increase":[149],"performance":[151],"mainstream":[153],"frameworks":[154],"large":[157],"margin.":[158]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}