{"id":"https://openalex.org/W4403791439","doi":"https://doi.org/10.1145/3664647.3681450","title":"R <sup>2</sup> SFD: Improving Single Image Reflection Removal using Semantic Feature Dictionary","display_name":"R <sup>2</sup> SFD: Improving Single Image Reflection Removal using Semantic Feature Dictionary","publication_year":2024,"publication_date":"2024-10-26","ids":{"openalex":"https://openalex.org/W4403791439","doi":"https://doi.org/10.1145/3664647.3681450"},"language":"en","primary_location":{"id":"doi:10.1145/3664647.3681450","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3664647.3681450","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3664647.3681450?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3664647.3681450?download=true","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5091938660","display_name":"Green Rosh","orcid":null},"institutions":[{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Green Rosh","raw_affiliation_strings":["Samsung R&amp;D Institute India, Bangalore, Bengaluru, India"],"raw_orcid":"https://orcid.org/0000-0002-1121-6267","affiliations":[{"raw_affiliation_string":"Samsung R&amp;D Institute India, Bangalore, Bengaluru, India","institution_ids":["https://openalex.org/I4210139030"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101661785","display_name":"B H Pawan Prasad","orcid":null},"institutions":[{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Pawan Prasad B H","raw_affiliation_strings":["Samsung R&amp;D Institute India, Bangalore, Bengaluru, India"],"raw_orcid":"https://orcid.org/0000-0002-2328-3125","affiliations":[{"raw_affiliation_string":"Samsung R&amp;D Institute India, Bangalore, Bengaluru, India","institution_ids":["https://openalex.org/I4210139030"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003154827","display_name":"Lokesh R Boregowda","orcid":"https://orcid.org/0009-0004-5966-4220"},"institutions":[{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Lokesh R. Boregowda","raw_affiliation_strings":["Samsung R&amp;D Institute India, Bangalore, Bengaluru, India"],"raw_orcid":"https://orcid.org/0009-0004-5966-4220","affiliations":[{"raw_affiliation_string":"Samsung R&amp;D Institute India, Bangalore, Bengaluru, India","institution_ids":["https://openalex.org/I4210139030"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006862080","display_name":"Kaushik Mitra","orcid":"https://orcid.org/0000-0001-6747-9050"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"education","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Kaushik Mitra","raw_affiliation_strings":["Indian Institute of Technology, Madras, Chennai, India"],"raw_orcid":"https://orcid.org/0000-0001-6747-9050","affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17291484,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"10277","last_page":"10286"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9995999932289124,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9995999932289124,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9975000023841858,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9943000078201294,"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":0.6750181913375854},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6224931478500366},{"id":"https://openalex.org/keywords/reflection","display_name":"Reflection (computer programming)","score":0.5753382444381714},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5175725221633911},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.43007487058639526},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35665562748908997},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.11211463809013367},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.08788987994194031}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6750181913375854},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6224931478500366},{"id":"https://openalex.org/C65682993","wikidata":"https://www.wikidata.org/wiki/Q1056451","display_name":"Reflection (computer programming)","level":2,"score":0.5753382444381714},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5175725221633911},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.43007487058639526},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35665562748908997},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.11211463809013367},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.08788987994194031},{"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:10.1145/3664647.3681450","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3664647.3681450","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3664647.3681450?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3664647.3681450","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3664647.3681450","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3664647.3681450?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403791439.pdf","grobid_xml":"https://content.openalex.org/works/W4403791439.grobid-xml"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W1543446142","https://openalex.org/W1901560254","https://openalex.org/W1980212291","https://openalex.org/W1988700013","https://openalex.org/W2107530646","https://openalex.org/W2166313476","https://openalex.org/W2185175083","https://openalex.org/W2518628096","https://openalex.org/W2608451532","https://openalex.org/W2737517983","https://openalex.org/W2752768279","https://openalex.org/W2777427113","https://openalex.org/W2789530606","https://openalex.org/W2798966709","https://openalex.org/W2807571777","https://openalex.org/W2894734721","https://openalex.org/W2914947442","https://openalex.org/W2919046835","https://openalex.org/W2954740582","https://openalex.org/W2955193736","https://openalex.org/W2963676366","https://openalex.org/W2964309429","https://openalex.org/W2967060301","https://openalex.org/W2982389402","https://openalex.org/W2983840324","https://openalex.org/W2987324461","https://openalex.org/W2999905431","https://openalex.org/W3034647178","https://openalex.org/W3035209350","https://openalex.org/W3035304527","https://openalex.org/W3035736826","https://openalex.org/W3107538983","https://openalex.org/W3110073279","https://openalex.org/W3136036486","https://openalex.org/W3173090543","https://openalex.org/W3173435145","https://openalex.org/W3179253672","https://openalex.org/W3180940425","https://openalex.org/W3186096677","https://openalex.org/W3191948448","https://openalex.org/W3193639341","https://openalex.org/W3197042136","https://openalex.org/W3204666771","https://openalex.org/W3207120935","https://openalex.org/W4200589107","https://openalex.org/W4214485187","https://openalex.org/W4234552385","https://openalex.org/W4241529584","https://openalex.org/W4292737915","https://openalex.org/W4319301044","https://openalex.org/W4390576621"],"related_works":["https://openalex.org/W2371168111","https://openalex.org/W2494809169","https://openalex.org/W3147584709","https://openalex.org/W1576035430","https://openalex.org/W2390392971","https://openalex.org/W3040437776","https://openalex.org/W2977677679","https://openalex.org/W2033914206","https://openalex.org/W2042327336","https://openalex.org/W4389713859"],"abstract_inverted_index":{"Single":[0],"image":[1,28,96,138,194,223],"reflection":[2,21,29,62,97,179,203,224],"removal":[3,30,98,225],"is":[4,11,52,71,81,114],"a":[5,88,100,107,117,184,198],"severely":[6],"ill-posed":[7],"problem":[8],"and":[9,19,135,166,213],"it":[10],"very":[12],"hard":[13],"to":[14,33,128,142,171,216],"separate":[15],"the":[16,25,35,46,57,75,129,136,155,164,168,173,217,220,240],"desirable":[17],"transmission":[18,36],"undesirable":[20],"layers.":[22],"Most":[23],"of":[24,59,61,109,131,192,197,200,219],"existing":[26],"single":[27,95,222],"methods":[31,226],"try":[32],"recover":[34],"layer":[37],"by":[38],"exploiting":[39],"cues":[40],"that":[41,124],"are":[42,139],"extracted":[43],"only":[44],"from":[45,106,154],"given":[47],"input":[48,137,157],"image.":[49],"However,":[50],"there":[51],"abundant":[53],"unutilized":[54],"information":[55,70],"in":[56,163],"form":[58],"millions":[60],"free":[63],"images":[64],"available":[65],"publicly.":[66],"Even":[67],"though":[68],"this":[69,84],"easily":[72],"available,":[73],"utilizing":[74],"same":[76],"for":[77,93,160],"effectively":[78],"removing":[79],"reflections":[80],"non-trivial.":[82],"In":[83],"paper,":[85],"we":[86,181],"propose":[87],"novel":[89,118,144],"method,":[90],"termed":[91,146],"R^2SFD,":[92],"improving":[94],"using":[99,116],"Semantic":[101],"Feature":[102,121],"Dictionary":[103],"(SFD)":[104],"constructed":[105,115],"database":[108],"reflection-free":[110],"images.":[111],"The":[112,133,205],"SFD":[113,134],"Reflection":[119,187],"Aware":[120],"Extractor":[122],"(RAFENet)":[123],"extracts":[125,151],"features":[126,153,162],"invariant":[127],"presence":[130],"reflections.":[132],"then":[140],"passed":[141],"another":[143],"network":[145,149],"SFDNet.":[147],"This":[148],"first":[150],"RAFENet":[152],"reflection-corrupted":[156],"image,":[158],"searches":[159],"similar":[161],"SFD,":[165],"transfers":[167],"semantic":[169],"content":[170],"generate":[172],"final":[174],"output.":[175],"To":[176],"further":[177],"improve":[178],"removal,":[180],"also":[182],"introduce":[183],"Large":[185],"Scale":[186],"Removal":[188],"(LSRR)":[189],"dataset":[190,241],"consisting":[191],"2650":[193],"pairs":[195],"comprising":[196],"variety":[199],"real":[201,228],"world":[202],"scenarios.":[204],"proposed":[206],"method":[207],"achieves":[208],"superior":[209],"results":[210],"both":[211],"qualitatively":[212],"quantitatively":[214],"compared":[215],"state":[218],"art":[221],"on":[227],"public":[229],"datasets":[230],"as":[231,233],"well":[232],"our":[234],"LSRR":[235],"dataset.":[236],"We":[237],"will":[238],"release":[239],"at":[242],"https://github.com/ee19d005/r2sfd.":[243]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
