{"id":"https://openalex.org/W3115741467","doi":"https://doi.org/10.1145/3393822.3432314","title":"Deep Image Compositing","display_name":"Deep Image Compositing","publication_year":2020,"publication_date":"2020-11-06","ids":{"openalex":"https://openalex.org/W3115741467","doi":"https://doi.org/10.1145/3393822.3432314","mag":"3115741467"},"language":"en","primary_location":{"id":"doi:10.1145/3393822.3432314","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3393822.3432314","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 European Symposium on Software Engineering","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2103.15446","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Shivangi Aneja","orcid":null},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Shivangi Aneja","raw_affiliation_strings":["Technical University of Munich, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"last","author":{"id":null,"display_name":"Soham Mazumder","orcid":null},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Soham Mazumder","raw_affiliation_strings":["Technical University of Munich, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I62916508"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17316244,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"101","last_page":"104"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9962000250816345,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/compositing","display_name":"Compositing","score":0.8407999873161316},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6205000281333923},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.613099992275238},{"id":"https://openalex.org/keywords/image-editing","display_name":"Image editing","score":0.5026000142097473},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4952999949455261},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.4544000029563904},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.40610000491142273},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4025000035762787},{"id":"https://openalex.org/keywords/hue","display_name":"Hue","score":0.4023999869823456}],"concepts":[{"id":"https://openalex.org/C129315195","wikidata":"https://www.wikidata.org/wiki/Q1121886","display_name":"Compositing","level":3,"score":0.8407999873161316},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7576000094413757},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7509999871253967},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6290000081062317},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6205000281333923},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.613099992275238},{"id":"https://openalex.org/C2776674983","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image editing","level":3,"score":0.5026000142097473},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4952999949455261},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.4544000029563904},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.40610000491142273},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4025000035762787},{"id":"https://openalex.org/C126537357","wikidata":"https://www.wikidata.org/wiki/Q372948","display_name":"Hue","level":2,"score":0.4023999869823456},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.36320000886917114},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.33869999647140503},{"id":"https://openalex.org/C11727466","wikidata":"https://www.wikidata.org/wiki/Q1628157","display_name":"Inpainting","level":3,"score":0.3319999873638153},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.32829999923706055},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.31929999589920044},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.3100999891757965},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.28929999470710754},{"id":"https://openalex.org/C79106606","wikidata":"https://www.wikidata.org/wiki/Q735197","display_name":"Afterimage","level":3,"score":0.27900001406669617},{"id":"https://openalex.org/C62725073","wikidata":"https://www.wikidata.org/wiki/Q1771663","display_name":"Image histogram","level":5,"score":0.2777999937534332},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.275299996137619},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.2612999975681305},{"id":"https://openalex.org/C78087231","wikidata":"https://www.wikidata.org/wiki/Q5156759","display_name":"Composite image filter","level":3,"score":0.258899986743927},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2558000087738037},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2538999915122986}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3393822.3432314","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3393822.3432314","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 European Symposium on Software Engineering","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2103.15446","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2103.15446","pdf_url":"https://arxiv.org/pdf/2103.15446","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2103.15446","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2103.15446","pdf_url":"https://arxiv.org/pdf/2103.15446","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1964884769","https://openalex.org/W2190424233","https://openalex.org/W2326925005","https://openalex.org/W2331128040","https://openalex.org/W2962737447","https://openalex.org/W2963073614","https://openalex.org/W2963835354","https://openalex.org/W6637568146","https://openalex.org/W6687483927"],"related_works":[],"abstract_inverted_index":{"In":[0,91],"image":[1,12,34,37,83,151,170,198,208],"editing,":[2],"the":[3,14,20,23,27,63,79,119,129,135,141,150,157,161,169,181,188,213,219],"most":[4],"common":[5],"task":[6,31,81,196],"is":[7,32,39,137,187,202],"pasting":[8],"objects":[9],"from":[10],"one":[11],"to":[13,60,76,96,98,128,139,155],"other":[15],"and":[16,48,131,146,152,165,215],"then":[17],"eventually":[18],"adjusting":[19],"manifestation":[21],"of":[22,52,82,125,144,149,168,183,197],"foreground":[24,145,158],"object":[25,159],"with":[26,121,160],"background":[28,147],"object.":[29],"This":[30],"called":[33],"compositing.":[35,199,209],"But":[36],"compositing":[38,84],"a":[40,49,122],"challenging":[41],"problem":[42,100],"which":[43],"requires":[44],"professional":[45],"editing":[46],"skills":[47],"considerable":[50],"amount":[51],"time.":[53],"Not":[54],"only":[55],"these":[56],"professionals":[57],"are":[58,73,111],"expensive":[59,75],"hire,":[61],"but":[62],"tools":[64],"(like":[65],"Adobe":[66],"Photoshop)":[67],"used":[68],"for":[69,86,194,207,223],"doing":[70],"such":[71],"tasks":[72],"also":[74,153,217],"purchase":[77],"making":[78,102],"overall":[80],"difficult":[85],"people":[87],"without":[88],"this":[89,92,99,178,186,228],"skillset.":[90],"work":[93,190],"we":[94,110,211],"aim":[95],"cater":[97],"by":[101],"composite":[103],"images":[104,130],"look":[105],"realistic.":[106],"To":[107,180],"achieve":[108],"this,":[109],"using":[112],"Generative":[113],"Adversarial":[114],"Networks":[115],"(GANS).":[116],"By":[117],"training":[118],"network":[120],"diverse":[123],"range":[124],"filters":[126],"applied":[127],"special":[132],"loss":[133],"functions,":[134],"model":[136],"able":[138],"decode":[140],"color":[142],"histogram":[143],"part":[148],"learns":[154],"blend":[156],"background.":[162],"The":[163],"hue":[164],"saturation":[166],"values":[167],"plays":[171],"an":[172],"important":[173],"role":[174],"as":[175],"discussed":[176],"in":[177],"paper.":[179],"best":[182],"our":[184,232],"knowledge,":[185],"first":[189],"that":[191,195,231],"uses":[192],"GANs":[193],"Currently,":[200],"there":[201],"no":[203],"benchmark":[204],"dataset":[205,214,220,229],"available":[206,222],"So":[210],"created":[212],"will":[216],"make":[218],"publicly":[221],"benchmarking.":[224],"Experimental":[225],"results":[226],"on":[227],"show":[230],"method":[233],"outperforms":[234],"all":[235],"current":[236],"state-of-the-art":[237],"methods.":[238]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2021-01-05T00:00:00"}
