{"id":"https://openalex.org/W3120386773","doi":"https://doi.org/10.1109/ijcb48548.2020.9304904","title":"All-in-one \u201cHairNet\u201d: A Deep Neural Model for Joint Hair Segmentation and Characterization","display_name":"All-in-one \u201cHairNet\u201d: A Deep Neural Model for Joint Hair Segmentation and Characterization","publication_year":2020,"publication_date":"2020-09-28","ids":{"openalex":"https://openalex.org/W3120386773","doi":"https://doi.org/10.1109/ijcb48548.2020.9304904","mag":"3120386773"},"language":"en","primary_location":{"id":"doi:10.1109/ijcb48548.2020.9304904","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcb48548.2020.9304904","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Joint Conference on Biometrics (IJCB)","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/A5099785516","display_name":"Diana Laura Borza","orcid":"https://orcid.org/0000-0002-0276-7243"},"institutions":[{"id":"https://openalex.org/I3125347698","display_name":"Babe\u0219-Bolyai University","ror":"https://ror.org/02rmd1t30","country_code":"RO","type":"education","lineage":["https://openalex.org/I3125347698"]}],"countries":["RO"],"is_corresponding":true,"raw_author_name":"Diana Borza","raw_affiliation_strings":["Babe\u015f Boylai University, Cluj-Napoca, Romania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Babe\u015f Boylai University, Cluj-Napoca, Romania","institution_ids":["https://openalex.org/I3125347698"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057743682","display_name":"Ehsan Yaghoubi","orcid":"https://orcid.org/0000-0003-3639-266X"},"institutions":[{"id":"https://openalex.org/I161321875","display_name":"University of Beira Interior","ror":"https://ror.org/03nf36p02","country_code":"PT","type":"education","lineage":["https://openalex.org/I161321875"]},{"id":"https://openalex.org/I4210120471","display_name":"Instituto de Telecomunica\u00e7\u00f5es","ror":"https://ror.org/02ht4fk33","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I4210120471"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Ehsan Yaghoubi","raw_affiliation_strings":["Instituto de Telecomunica\u00e7\u00f5es, University of Beira Interior, Covilha, Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Instituto de Telecomunica\u00e7\u00f5es, University of Beira Interior, Covilha, Portugal","institution_ids":["https://openalex.org/I161321875","https://openalex.org/I4210120471"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002088416","display_name":"Jo\u00e3o C. Neves","orcid":"https://orcid.org/0000-0003-0139-2213"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Joao Neves","raw_affiliation_strings":["TomiWorld, Viseu, Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TomiWorld, Viseu, Portugal","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090305015","display_name":"Hugo Proen\u00e7a","orcid":"https://orcid.org/0000-0003-2551-8570"},"institutions":[{"id":"https://openalex.org/I161321875","display_name":"University of Beira Interior","ror":"https://ror.org/03nf36p02","country_code":"PT","type":"education","lineage":["https://openalex.org/I161321875"]},{"id":"https://openalex.org/I4210120471","display_name":"Instituto de Telecomunica\u00e7\u00f5es","ror":"https://ror.org/02ht4fk33","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I4210120471"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Hugo Proenca","raw_affiliation_strings":["Instituto de Telecomunica\u00e7\u00f5es, University of Beira Interior, Covilha, Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Instituto de Telecomunica\u00e7\u00f5es, University of Beira Interior, Covilha, Portugal","institution_ids":["https://openalex.org/I161321875","https://openalex.org/I4210120471"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5099785516"],"corresponding_institution_ids":["https://openalex.org/I3125347698"],"apc_list":null,"apc_paid":null,"fwci":0.0981,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.43994171,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"37","issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9854000210762024,"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/T11448","display_name":"Face recognition and analysis","score":0.9854000210762024,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9739999771118164,"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":0.972100019454956,"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/segmentation","display_name":"Segmentation","score":0.7911965847015381},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7722266912460327},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7377274036407471},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6775308847427368},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6572073698043823},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5249022245407104},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.49127572774887085},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45850899815559387},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.44882211089134216},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.4394336938858032},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.4275713264942169},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.42746812105178833},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.360684335231781}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7911965847015381},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7722266912460327},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7377274036407471},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6775308847427368},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6572073698043823},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5249022245407104},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.49127572774887085},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45850899815559387},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.44882211089134216},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.4394336938858032},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.4275713264942169},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.42746812105178833},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.360684335231781},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcb48548.2020.9304904","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcb48548.2020.9304904","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Joint Conference on Biometrics (IJCB)","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":43,"referenced_works":["https://openalex.org/W62762741","https://openalex.org/W204064097","https://openalex.org/W1495267108","https://openalex.org/W1522301498","https://openalex.org/W1536680647","https://openalex.org/W1782590233","https://openalex.org/W1834627138","https://openalex.org/W1861492603","https://openalex.org/W1923115158","https://openalex.org/W1966572524","https://openalex.org/W1973168410","https://openalex.org/W2025306521","https://openalex.org/W2045134316","https://openalex.org/W2063566441","https://openalex.org/W2082498363","https://openalex.org/W2109255472","https://openalex.org/W2132050322","https://openalex.org/W2158844819","https://openalex.org/W2159246913","https://openalex.org/W2165991346","https://openalex.org/W2539528817","https://openalex.org/W2548780814","https://openalex.org/W2566619501","https://openalex.org/W2593879108","https://openalex.org/W2605339450","https://openalex.org/W2612445135","https://openalex.org/W2737986725","https://openalex.org/W2893299052","https://openalex.org/W2913340405","https://openalex.org/W2921525902","https://openalex.org/W2964121744","https://openalex.org/W2964166015","https://openalex.org/W3106250896","https://openalex.org/W3112122518","https://openalex.org/W3191734347","https://openalex.org/W4294643831","https://openalex.org/W4297775537","https://openalex.org/W6631190155","https://openalex.org/W6639102338","https://openalex.org/W6737664043","https://openalex.org/W6745560452","https://openalex.org/W6785652829","https://openalex.org/W6786923439"],"related_works":["https://openalex.org/W2517104666","https://openalex.org/W2005437358","https://openalex.org/W1669643531","https://openalex.org/W2008656436","https://openalex.org/W2134924024","https://openalex.org/W2023558673","https://openalex.org/W2110230079","https://openalex.org/W1982826852","https://openalex.org/W2613186388","https://openalex.org/W2546942002"],"abstract_inverted_index":{"The":[0],"hair":[1,46,52,163,174],"appearance":[2,22],"is":[3,23,113,118,156],"among":[4],"the":[5,20,45,51,67,81,85,97,101,108,115,121,132,136,143,152,160,169,179,185],"most":[6],"valuable":[7],"soft":[8],"biometric":[9],"traits":[10],"when":[11],"performing":[12,188],"human":[13],"recognition":[14],"at-a-distance.":[15],"Even":[16],"in":[17,193],"degraded":[18],"data,":[19,154],"hair's":[21],"instinctively":[24],"used":[25,119],"by":[26,120],"humans":[27],"to":[28,79,124,135,145,178],"distinguish":[29],"between":[30],"individuals.":[31],"In":[32,104],"this":[33],"paper":[34],"we":[35],"propose":[36],"a":[37,105,173,194],"multi-task":[38],"deep":[39],"neural":[40,72],"model":[41,112],"capable":[42],"of":[43,69,110,151,162,187,191],"segmenting":[44],"region,":[47],"while":[48],"also":[49],"inferring":[50],"color,":[53],"shape":[54],"and":[55,83],"style,":[56],"all":[57],"from":[58,148],"in-the-wild":[59],"images.":[60],"Our":[61,165],"main":[62,183],"contributions":[63],"are":[64],"two-fold:":[65],"1)":[66],"design":[68],"an":[70,92],"all-in-one":[71],"network,":[73],"based":[74],"on":[75],"depthwise":[76],"separable":[77],"convolutions":[78],"extract":[80],"features;":[82],"2)":[84],"use":[86],"convolutional":[87],"feature":[88],"masking":[89],"layer":[90],"as":[91,182],"attention":[93],"mechanism":[94],"that":[95,114,168],"enforces":[96],"analysis":[98,192],"only":[99,131],"within":[100],"`hair'":[102],"regions.":[103,164],"conceptual":[106],"perspective,":[107],"strength":[109],"our":[111],"segmentation":[116,175],"mask":[117],"other":[122],"tasks":[123],"perceive":[125],"-":[126,130],"at":[127],"feature-map":[128],"level":[129],"regions":[133],"relevant":[134],"attribute":[137],"characterization":[138],"task.":[139],"This":[140],"paradigm":[141],"allows":[142],"network":[144],"analyze":[146],"features":[147],"nonrectangular":[149],"areas":[150],"input":[153],"which":[155],"particularly":[157],"important,":[158],"considering":[159],"irregularity":[161],"experiments":[166],"showed":[167],"proposed":[170],"approach":[171],"reaches":[172],"performance":[176],"comparable":[177],"state-of-the-art,":[180],"having":[181],"advantage":[184],"fact":[186],"multiple":[189],"levels":[190],"single-shot":[195],"paradigm.":[196]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-03T08:25:01.440150","created_date":"2025-10-10T00:00:00"}
