{"id":"https://openalex.org/W4304091571","doi":"https://doi.org/10.1145/3503161.3548214","title":"Marior: Margin Removal and Iterative Content Rectification for Document Dewarping in the Wild","display_name":"Marior: Margin Removal and Iterative Content Rectification for Document Dewarping in the Wild","publication_year":2022,"publication_date":"2022-10-10","ids":{"openalex":"https://openalex.org/W4304091571","doi":"https://doi.org/10.1145/3503161.3548214"},"language":"en","primary_location":{"id":"doi:10.1145/3503161.3548214","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503161.3548214","pdf_url":null,"source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","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":"Proceedings of the 30th ACM International Conference on Multimedia","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/A5100414877","display_name":"Jiaxin Zhang","orcid":"https://orcid.org/0000-0003-2144-9053"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiaxin Zhang","raw_affiliation_strings":["South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071461852","display_name":"Canjie Luo","orcid":"https://orcid.org/0000-0002-1089-7611"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Canjie Luo","raw_affiliation_strings":["South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080674767","display_name":"Lianwen Jin","orcid":"https://orcid.org/0000-0002-5456-0957"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianwen Jin","raw_affiliation_strings":["South China University of Technology & Peng Cheng Laboratory, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"South China University of Technology & Peng Cheng Laboratory, Guangzhou, China","institution_ids":["https://openalex.org/I4210136793","https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114859120","display_name":"Fengjun Guo","orcid":"https://orcid.org/0000-0003-1984-3027"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fengjun Guo","raw_affiliation_strings":["IntSig Information Co. Ltd, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"IntSig Information Co. Ltd, Shanghai, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114858729","display_name":"Kai Ding","orcid":"https://orcid.org/0000-0002-9371-0751"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kai Ding","raw_affiliation_strings":["IntSig Information Co. Ltd, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"IntSig Information Co. Ltd, Shanghai, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100414877"],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":1.3793,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.87430486,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2805","last_page":"2815"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.995199978351593,"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":0.995199978351593,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9904000163078308,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9897000193595886,"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/margin","display_name":"Margin (machine learning)","score":0.8427942991256714},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7816133499145508},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.7332375645637512},{"id":"https://openalex.org/keywords/readability","display_name":"Readability","score":0.6050779819488525},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5671669840812683},{"id":"https://openalex.org/keywords/rectification","display_name":"Rectification","score":0.4754980504512787},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.4744221568107605},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.47301769256591797},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.434237539768219},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4338029623031616},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.15934115648269653},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11962944269180298}],"concepts":[{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.8427942991256714},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7816133499145508},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7332375645637512},{"id":"https://openalex.org/C2778143727","wikidata":"https://www.wikidata.org/wiki/Q1820650","display_name":"Readability","level":2,"score":0.6050779819488525},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5671669840812683},{"id":"https://openalex.org/C50942859","wikidata":"https://www.wikidata.org/wiki/Q4967193","display_name":"Rectification","level":3,"score":0.4754980504512787},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.4744221568107605},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.47301769256591797},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.434237539768219},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4338029623031616},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.15934115648269653},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11962944269180298},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3503161.3548214","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503161.3548214","pdf_url":null,"source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","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":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1647671624","https://openalex.org/W2022289190","https://openalex.org/W2027238116","https://openalex.org/W2031746509","https://openalex.org/W2033628967","https://openalex.org/W2047643928","https://openalex.org/W2066204611","https://openalex.org/W2090518410","https://openalex.org/W2098270921","https://openalex.org/W2112626863","https://openalex.org/W2115263911","https://openalex.org/W2121498135","https://openalex.org/W2121931423","https://openalex.org/W2130987542","https://openalex.org/W2159374825","https://openalex.org/W2161175365","https://openalex.org/W2166767194","https://openalex.org/W2170265032","https://openalex.org/W2412396436","https://openalex.org/W2786749633","https://openalex.org/W2798905980","https://openalex.org/W2964309882","https://openalex.org/W2973841807","https://openalex.org/W2984850203","https://openalex.org/W2985998306","https://openalex.org/W2998508940","https://openalex.org/W3047176958","https://openalex.org/W3049081235","https://openalex.org/W3082022228","https://openalex.org/W3094927345","https://openalex.org/W3162001439","https://openalex.org/W3207713347","https://openalex.org/W4285529970"],"related_works":["https://openalex.org/W1964661231","https://openalex.org/W4254960163","https://openalex.org/W3110264473","https://openalex.org/W2999103397","https://openalex.org/W2370831213","https://openalex.org/W4315704968","https://openalex.org/W4285478380","https://openalex.org/W2100255360","https://openalex.org/W2032810564","https://openalex.org/W2107506952"],"abstract_inverted_index":{"Camera-captured":[0],"document":[1,39,52,104],"images":[2,53,80,105],"usually":[3],"suffer":[4],"from":[5],"perspective":[6],"and":[7,23,99,122,137,155],"geometric":[8],"deformations.":[9],"It":[10],"is":[11,83,95],"of":[12,27,91,167,199,208],"great":[13],"value":[14],"to":[15,63,68,131,171,191],"rectify":[16],"them":[17],"when":[18,72],"considering":[19],"poor":[20],"visual":[21],"aesthetics":[22],"the":[24,36,89,107,134,146,164,168,173,183,197,205],"deteriorated":[25],"performance":[26,207],"OCR":[28],"systems.":[29],"Recent":[30],"learning-based":[31],"methods":[32],"intensively":[33],"focus":[34],"on":[35,211],"accurately":[37],"cropped":[38],"image.":[40],"However,":[41],"this":[42,64,111],"might":[43],"not":[44],"be":[45],"sufficient":[46],"for":[47,102,220],"overcoming":[48],"practical":[49],"challenges,":[50],"including":[51],"either":[54],"with":[55],"large":[56,75],"marginal":[57,76],"regions":[58],"or":[59],"without":[60,81],"margins.":[61],"Due":[62],"impracticality,":[65],"users":[66],"struggle":[67],"crop":[69],"documents":[70],"precisely":[71],"they":[73],"encounter":[74],"regions.":[77],"Simultaneously,":[78],"dewarping":[79,135],"margins":[82],"still":[84,96],"an":[85],"insurmountable":[86],"problem.":[87],"To":[88,109],"best":[90],"our":[92,209],"knowledge,":[93],"there":[94],"no":[97],"complete":[98],"effective":[100],"pipeline":[101,147],"rectifying":[103],"in":[106,139],"wild.":[108],"address":[110],"issue,":[112],"we":[113,144,162,181],"propose":[114],"a":[115,128,140,177],"novel":[116],"approach":[117],"called":[118],"Marior":[119,126],"(Margin":[120],"Removal":[121],"Iterative":[123],"Content":[124],"Rectification).":[125],"follows":[127],"progressive":[129],"strategy":[130],"iteratively":[132],"improve":[133],"quality":[136],"readability":[138],"coarse-to-fine":[141],"manner.":[142],"Specifically,":[143],"divide":[145],"into":[148],"two":[149],"modules:":[150],"margin":[151],"removal":[152],"module":[153,159],"(MRM)":[154],"iterative":[156],"content":[157],"rectification":[158],"(ICRM).":[160],"First,":[161],"predict":[163],"segmentation":[165],"mask":[166],"input":[169],"image":[170,184],"remove":[172],"margin,":[174],"thereby":[175],"obtaining":[176],"preliminary":[178],"result.":[179],"Then":[180],"refine":[182],"further":[185,221],"by":[186],"producing":[187],"dense":[188],"displacement":[189],"flows":[190],"achieve":[192],"content-aware":[193],"rectification.":[194],"We":[195],"determine":[196],"number":[198],"refinement":[200],"iterations":[201],"adaptively.":[202],"Experiments":[203],"demonstrate":[204],"state-of-the-art":[206],"method":[210],"public":[212],"benchmarks.":[213],"The":[214],"resources":[215],"are":[216],"available":[217],"at":[218],"https://github.com/ZZZHANG-jx/Marior":[219],"comparison.":[222]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}