{"id":"https://openalex.org/W3163490880","doi":"https://doi.org/10.1109/icpr48806.2021.9412692","title":"Text Recognition in Real Scenarios with a Few Labeled Samples","display_name":"Text Recognition in Real Scenarios with a Few Labeled Samples","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3163490880","doi":"https://doi.org/10.1109/icpr48806.2021.9412692","mag":"3163490880"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412692","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412692","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","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/A5056016471","display_name":"Jinghuang Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinghuang Lin","raw_affiliation_strings":["Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011185036","display_name":"Zhanzhan Cheng","orcid":"https://orcid.org/0000-0002-5732-1513"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhanzhan Cheng","raw_affiliation_strings":["Hikvision Research Institute, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hikvision Research Institute, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101399396","display_name":"Fan Bai","orcid":"https://orcid.org/0000-0002-4139-0653"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Bai","raw_affiliation_strings":["Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101448949","display_name":"Yi Niu","orcid":"https://orcid.org/0000-0002-7359-276X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yi Niu","raw_affiliation_strings":["Hikvision Research Institute, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hikvision Research Institute, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085955762","display_name":"Shiliang Pu","orcid":"https://orcid.org/0000-0001-5269-7821"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shiliang Pu","raw_affiliation_strings":["Hikvision Research Institute, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hikvision Research Institute, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017862559","display_name":"Shuigeng Zhou","orcid":"https://orcid.org/0000-0002-1949-2768"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuigeng Zhou","raw_affiliation_strings":["Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2864,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.58383903,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"80","issue":null,"first_page":"370","last_page":"377"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9997000098228455,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9997000098228455,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9776999950408936,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9599999785423279,"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":0.833959698677063},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.697001039981842},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.6827617287635803},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6500102281570435},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6111936569213867},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5884942412376404},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5855703353881836},{"id":"https://openalex.org/keywords/character","display_name":"Character (mathematics)","score":0.544755756855011},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5443553328514099},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5159873962402344},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4963594079017639},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.46458011865615845},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4616625905036926},{"id":"https://openalex.org/keywords/confusion","display_name":"Confusion","score":0.4440404176712036},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.44001874327659607},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.4396136701107025},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43952956795692444},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.43543118238449097},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4309479594230652},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41731879115104675},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.10971328616142273},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07642212510108948}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.833959698677063},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.697001039981842},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6827617287635803},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6500102281570435},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6111936569213867},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5884942412376404},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5855703353881836},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.544755756855011},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5443553328514099},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5159873962402344},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4963594079017639},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.46458011865615845},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4616625905036926},{"id":"https://openalex.org/C2781140086","wikidata":"https://www.wikidata.org/wiki/Q557945","display_name":"Confusion","level":2,"score":0.4440404176712036},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.44001874327659607},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.4396136701107025},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43952956795692444},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.43543118238449097},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4309479594230652},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41731879115104675},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.10971328616142273},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07642212510108948},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C11171543","wikidata":"https://www.wikidata.org/wiki/Q41630","display_name":"Psychoanalysis","level":1,"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/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412692","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412692","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320325413","display_name":"Shanghai Municipal Commission of Economy and Informatization","ror":"https://ror.org/04166ws88"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":72,"referenced_works":["https://openalex.org/W6908809","https://openalex.org/W1491389626","https://openalex.org/W1522301498","https://openalex.org/W1607307044","https://openalex.org/W1882958252","https://openalex.org/W1916279783","https://openalex.org/W1922126009","https://openalex.org/W1978729128","https://openalex.org/W1998042868","https://openalex.org/W2008806374","https://openalex.org/W2130942839","https://openalex.org/W2133564696","https://openalex.org/W2140132917","https://openalex.org/W2144554289","https://openalex.org/W2194187530","https://openalex.org/W2294053032","https://openalex.org/W2593768305","https://openalex.org/W2598581049","https://openalex.org/W2750938222","https://openalex.org/W2756073160","https://openalex.org/W2767699072","https://openalex.org/W2795619303","https://openalex.org/W2810028092","https://openalex.org/W2810983211","https://openalex.org/W2875814315","https://openalex.org/W2885722640","https://openalex.org/W2893918048","https://openalex.org/W2894730515","https://openalex.org/W2904785373","https://openalex.org/W2905589284","https://openalex.org/W2909425146","https://openalex.org/W2951939904","https://openalex.org/W2959965583","https://openalex.org/W2962790387","https://openalex.org/W2962793481","https://openalex.org/W2962808524","https://openalex.org/W2963233928","https://openalex.org/W2963299454","https://openalex.org/W2963327605","https://openalex.org/W2963500702","https://openalex.org/W2963517393","https://openalex.org/W2963526661","https://openalex.org/W2963712589","https://openalex.org/W2963784072","https://openalex.org/W2963826681","https://openalex.org/W2964121744","https://openalex.org/W2964308564","https://openalex.org/W2965066169","https://openalex.org/W2970910956","https://openalex.org/W2979371747","https://openalex.org/W2987563462","https://openalex.org/W3005436539","https://openalex.org/W3106271744","https://openalex.org/W6600284362","https://openalex.org/W6631190155","https://openalex.org/W6636382570","https://openalex.org/W6639480849","https://openalex.org/W6640226783","https://openalex.org/W6649973027","https://openalex.org/W6679434410","https://openalex.org/W6679436768","https://openalex.org/W6720691552","https://openalex.org/W6735204497","https://openalex.org/W6744307767","https://openalex.org/W6745620410","https://openalex.org/W6746282794","https://openalex.org/W6752143097","https://openalex.org/W6752486419","https://openalex.org/W6754568377","https://openalex.org/W6754924631","https://openalex.org/W6757884528","https://openalex.org/W6767937744"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W2899666933","https://openalex.org/W4289294429","https://openalex.org/W2949100517","https://openalex.org/W2147093486"],"abstract_inverted_index":{"Scene":[0],"text":[1,34],"recognition":[2,60],"(STR)":[3],"is":[4,62,115],"still":[5],"a":[6,25,29,78,101,109,160],"hot":[7],"research":[8],"topic":[9],"in":[10,53,166],"computer":[11],"vision":[12],"field":[13],"due":[14],"to":[15,36,86,188],"its":[16],"various":[17,173],"applications.":[18],"Existing":[19],"works":[20],"mainly":[21],"focus":[22],"on":[23,172],"learning":[24,119],"general":[26],"model":[27],"with":[28,124,135,158],"huge":[30],"number":[31,162],"of":[32,163],"synthetic":[33,92,97],"images":[35],"recognize":[37],"unconstrained":[38],"scene":[39],"texts,":[40],"and":[41,100,128,149,184],"have":[42],"achieved":[43],"substantial":[44],"progress.":[45],"However,":[46],"these":[47],"methods":[48],"are":[49,68],"not":[50],"quite":[51],"applicable":[52],"many":[54,96],"real-world":[55],"scenarios":[56],"where":[57],"1)":[58],"high":[59],"accuracy":[61],"required,":[63],"while":[64],"2)":[65],"labeled":[66,98,112,164],"samples":[67,165],"lacked.":[69],"To":[70],"tackle":[71],"this":[72,75],"challenging":[73],"problem,":[74],"paper":[76],"proposes":[77],"few-shot":[79],"adversarial":[80,136],"sequence":[81,88],"domain":[82,94,104,148],"adaptation":[83,89,157],"(FASDA)":[84],"approach":[85,139],"build":[87],"between":[90,145],"the":[91,130,142,146,150,155,167,181,189],"source":[93,147],"(with":[95,105],"samples)":[99],"specific":[102],"target":[103,151,168],"only":[106],"some":[107],"or":[108],"few":[110],"real":[111],"samples).":[113],"This":[114],"done":[116],"by":[117],"simultaneously":[118],"each":[120],"character's":[121],"feature":[122],"representation":[123],"an":[125],"attention":[126],"mechanism":[127],"establishing":[129],"corresponding":[131],"character-level":[132,143],"latent":[133],"subspace":[134],"learning.":[137],"Our":[138],"can":[140],"maximize":[141],"confusion":[144],"domain,":[152],"thus":[153],"achieves":[154],"sequence-level":[156],"even":[159],"small":[161],"domain.":[169],"Extensive":[170],"experiments":[171],"datasets":[174],"show":[175],"that":[176],"our":[177],"method":[178],"significantly":[179],"outperforms":[180],"finetuning":[182],"scheme,":[183],"obtains":[185],"comparable":[186],"performance":[187],"state-of-the-art":[190],"STR":[191],"methods.":[192]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
