{"id":"https://openalex.org/W3090023449","doi":"https://doi.org/10.1109/icip40778.2020.9191107","title":"A Simple Yet Effective Pipeline For Radial Distortion Correction","display_name":"A Simple Yet Effective Pipeline For Radial Distortion Correction","publication_year":2020,"publication_date":"2020-09-30","ids":{"openalex":"https://openalex.org/W3090023449","doi":"https://doi.org/10.1109/icip40778.2020.9191107","mag":"3090023449"},"language":"en","primary_location":{"id":"doi:10.1109/icip40778.2020.9191107","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191107","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","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/A5101661485","display_name":"He Zhao","orcid":"https://orcid.org/0000-0002-2471-9680"},"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":"He Zhao","raw_affiliation_strings":["Key Lab of Machine Perception (MOE), Peking University"],"affiliations":[{"raw_affiliation_string":"Key Lab of Machine Perception (MOE), Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031204537","display_name":"Yongjie Shi","orcid":"https://orcid.org/0000-0002-7524-1146"},"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":"Yongjie Shi","raw_affiliation_strings":["Key Lab of Machine Perception (MOE), Peking University"],"affiliations":[{"raw_affiliation_string":"Key Lab of Machine Perception (MOE), Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100784734","display_name":"Xin Tong","orcid":"https://orcid.org/0000-0001-8788-2453"},"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":"Xin Tong","raw_affiliation_strings":["Key Lab of Machine Perception (MOE), Peking University"],"affiliations":[{"raw_affiliation_string":"Key Lab of Machine Perception (MOE), Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015981200","display_name":"Xianghua Ying","orcid":"https://orcid.org/0000-0002-9785-0727"},"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":"Xianghua Ying","raw_affiliation_strings":["Key Lab of Machine Perception (MOE), Peking University"],"affiliations":[{"raw_affiliation_string":"Key Lab of Machine Perception (MOE), Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017031914","display_name":"Hongbin Zha","orcid":"https://orcid.org/0000-0001-5860-4673"},"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":"Hongbin Zha","raw_affiliation_strings":["Key Lab of Machine Perception (MOE), Peking University"],"affiliations":[{"raw_affiliation_string":"Key Lab of Machine Perception (MOE), Peking University","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101661485"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.4885,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.66175976,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"878","last_page":"882"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10638","display_name":"Optical measurement and interference techniques","score":0.9998000264167786,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9998000264167786,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T11338","display_name":"Advancements in Photolithography Techniques","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.7506272196769714},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6991426944732666},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6839019060134888},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6132752299308777},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.48389849066734314},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46098029613494873},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4531328082084656},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.4259512424468994},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.09643802046775818}],"concepts":[{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.7506272196769714},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6991426944732666},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6839019060134888},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6132752299308777},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.48389849066734314},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46098029613494873},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4531328082084656},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.4259512424468994},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.09643802046775818},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip40778.2020.9191107","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191107","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","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":31,"referenced_works":["https://openalex.org/W36923225","https://openalex.org/W603908379","https://openalex.org/W1522301498","https://openalex.org/W1557102613","https://openalex.org/W1910129379","https://openalex.org/W1969332260","https://openalex.org/W1992989752","https://openalex.org/W2021581587","https://openalex.org/W2033819227","https://openalex.org/W2075544016","https://openalex.org/W2097648992","https://openalex.org/W2103569660","https://openalex.org/W2108598243","https://openalex.org/W2150141892","https://openalex.org/W2194775991","https://openalex.org/W2562637781","https://openalex.org/W2592756114","https://openalex.org/W2737258237","https://openalex.org/W2796773185","https://openalex.org/W2891665375","https://openalex.org/W2902878200","https://openalex.org/W2959131783","https://openalex.org/W2964121744","https://openalex.org/W2970971581","https://openalex.org/W2979543786","https://openalex.org/W4295312788","https://openalex.org/W6618372016","https://openalex.org/W6631190155","https://openalex.org/W6730551332","https://openalex.org/W6734937843","https://openalex.org/W6766978945"],"related_works":["https://openalex.org/W1585007175","https://openalex.org/W2382521049","https://openalex.org/W2144385241","https://openalex.org/W2165950148","https://openalex.org/W4253593777","https://openalex.org/W2951497643","https://openalex.org/W4300101996","https://openalex.org/W2142393343","https://openalex.org/W2977327189","https://openalex.org/W2353456014"],"abstract_inverted_index":{"Eliminating":[0],"the":[1,88,94,100,106],"radial":[2,27],"lens":[3],"distortion":[4,28,89],"of":[5,114],"an":[6,70,80],"image":[7,81],"is":[8],"a":[9,21,47,75],"crucial":[10],"preprocessing":[11],"step":[12],"for":[13,26],"many":[14],"computer":[15],"vision":[16],"applications.":[17],"This":[18],"paper":[19],"explores":[20],"simple":[22],"yet":[23],"effective":[24],"pipeline":[25],"correction.":[29],"Different":[30],"from":[31],"existing":[32],"state-of-the-art":[33,95],"methods":[34],"that":[35],"design":[36,55],"complex":[37],"network":[38,49],"structure":[39],"and":[40,61,79,108,122],"concatenate":[41],"multi-branch":[42],"features.":[43],"Our":[44],"model":[45,98],"uses":[46],"single":[48],"without":[50],"any":[51],"additional":[52],"supervision.":[53],"We":[54],"two":[56],"differentiable":[57],"layers":[58],"to":[59,86],"synthesize":[60],"rectify":[62],"distorted":[63,110],"images":[64,111],"efficiently.":[65],"Based":[66],"on":[67,104],"these":[68],"layers,":[69],"online":[71],"data":[72,121],"synthesis":[73],"strategy,":[74],"sampling":[76],"grid":[77],"loss,":[78],"reprojection":[82],"loss":[83],"are":[84],"proposed":[85],"improve":[87],"correction":[90],"accuracy.":[91],"Compared":[92],"with":[93,112],"methods,":[96],"our":[97],"achieves":[99],"best":[101],"rectification":[102],"quality":[103],"both":[105],"synthetic":[107],"real":[109],"dozens":[113],"times":[115],"faster":[116],"inference":[117],"speed.":[118],"The":[119],"training":[120],"codes":[123],"will":[124],"be":[125],"released.":[126],"<sup":[127,130],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[128,131],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sup>":[129,132],"https://github.com/MccreeZhao/RDCPipeline":[133]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}