{"id":"https://openalex.org/W2899812241","doi":"https://doi.org/10.1109/tip.2018.2879408","title":"Deep Visual Saliency on Stereoscopic Images","display_name":"Deep Visual Saliency on Stereoscopic Images","publication_year":2018,"publication_date":"2018-11-06","ids":{"openalex":"https://openalex.org/W2899812241","doi":"https://doi.org/10.1109/tip.2018.2879408","mag":"2899812241","pmid":"https://pubmed.ncbi.nlm.nih.gov/30403631"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2018.2879408","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2018.2879408","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5100616331","display_name":"Duc Chien Nguyen","orcid":"https://orcid.org/0000-0001-7759-1134"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Anh-Duc Nguyen","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102916130","display_name":"Jongyoo Kim","orcid":"https://orcid.org/0000-0002-2435-9195"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jongyoo Kim","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037805423","display_name":"Heeseok Oh","orcid":"https://orcid.org/0000-0002-0920-7281"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Heeseok Oh","raw_affiliation_strings":["Electronics and Telecommunications Research Institute, Daejeon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronics and Telecommunications Research Institute, Daejeon, South Korea","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080643325","display_name":"Haksub Kim","orcid":"https://orcid.org/0000-0002-8780-9747"},"institutions":[{"id":"https://openalex.org/I58716616","display_name":"Korea Institute of Science and Technology","ror":"https://ror.org/05kzfa883","country_code":"KR","type":"facility","lineage":["https://openalex.org/I27494661","https://openalex.org/I2801339556","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098","https://openalex.org/I4387152098","https://openalex.org/I58716616"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Haksub Kim","raw_affiliation_strings":["Korea Institute of Science and Technology, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea Institute of Science and Technology, Seoul, South Korea","institution_ids":["https://openalex.org/I58716616"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100403129","display_name":"Weisi Lin","orcid":"https://orcid.org/0000-0001-9866-1947"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Weisi Lin","raw_affiliation_strings":["School of Computer Science and Engineering, Nanyang Technological University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100320181","display_name":"Sanghoon Lee","orcid":"https://orcid.org/0000-0001-9895-5347"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sanghoon Lee","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-9895-5347","affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.6961,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.88858187,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"28","issue":"4","first_page":"1939","last_page":"1953"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9998999834060669,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9998999834060669,"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/T11165","display_name":"Image and Video Quality Assessment","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/T10427","display_name":"Visual perception and processing mechanisms","score":0.9914000034332275,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8508312702178955},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7800706028938293},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6427007913589478},{"id":"https://openalex.org/keywords/kadir\u2013brady-saliency-detector","display_name":"Kadir\u2013Brady saliency detector","score":0.6348674297332764},{"id":"https://openalex.org/keywords/stereoscopy","display_name":"Stereoscopy","score":0.627651035785675},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.607097327709198},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.5670761466026306},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5635137557983398},{"id":"https://openalex.org/keywords/human-visual-system-model","display_name":"Human visual system model","score":0.5463845729827881},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.53407222032547},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5288599133491516},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4839351773262024},{"id":"https://openalex.org/keywords/luminance","display_name":"Luminance","score":0.47602134943008423},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.4637826681137085},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4235672354698181},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.25566366314888}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8508312702178955},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7800706028938293},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6427007913589478},{"id":"https://openalex.org/C202227193","wikidata":"https://www.wikidata.org/wiki/Q6345568","display_name":"Kadir\u2013Brady saliency detector","level":4,"score":0.6348674297332764},{"id":"https://openalex.org/C126057942","wikidata":"https://www.wikidata.org/wiki/Q35158","display_name":"Stereoscopy","level":2,"score":0.627651035785675},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.607097327709198},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.5670761466026306},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5635137557983398},{"id":"https://openalex.org/C160086991","wikidata":"https://www.wikidata.org/wiki/Q5939193","display_name":"Human visual system model","level":3,"score":0.5463845729827881},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.53407222032547},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5288599133491516},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4839351773262024},{"id":"https://openalex.org/C73313986","wikidata":"https://www.wikidata.org/wiki/Q355386","display_name":"Luminance","level":2,"score":0.47602134943008423},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.4637826681137085},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4235672354698181},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.25566366314888},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tip.2018.2879408","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2018.2879408","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:30403631","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30403631","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null},{"id":"pmh:oai:dr.ntu.edu.sg:10356/142326","is_oa":false,"landing_page_url":"https://hdl.handle.net/10356/142326","pdf_url":null,"source":{"id":"https://openalex.org/S4306402609","display_name":"DR-NTU (Nanyang Technological University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I172675005","host_organization_name":"Nanyang Technological University","host_organization_lineage":["https://openalex.org/I172675005"],"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":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.75,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G7491344312","display_name":null,"funder_award_id":"SRFC-IT1702-08","funder_id":"https://openalex.org/F4320332195","funder_display_name":"Samsung"}],"funders":[{"id":"https://openalex.org/F4320332195","display_name":"Samsung","ror":"https://ror.org/04w3jy968"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W6908809","https://openalex.org/W73612554","https://openalex.org/W358561913","https://openalex.org/W1497443722","https://openalex.org/W1510835000","https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1544789217","https://openalex.org/W1686810756","https://openalex.org/W1836465849","https://openalex.org/W1910776219","https://openalex.org/W1936373248","https://openalex.org/W1978741881","https://openalex.org/W1981076008","https://openalex.org/W1981228217","https://openalex.org/W1996095832","https://openalex.org/W1997137149","https://openalex.org/W2000946514","https://openalex.org/W2001992771","https://openalex.org/W2022508996","https://openalex.org/W2033941867","https://openalex.org/W2033959528","https://openalex.org/W2054802006","https://openalex.org/W2073812468","https://openalex.org/W2095705004","https://openalex.org/W2096391334","https://openalex.org/W2102388230","https://openalex.org/W2102605133","https://openalex.org/W2122256465","https://openalex.org/W2128272608","https://openalex.org/W2135957164","https://openalex.org/W2146103513","https://openalex.org/W2156127467","https://openalex.org/W2156387975","https://openalex.org/W2170379149","https://openalex.org/W2170632605","https://openalex.org/W2183871738","https://openalex.org/W2206823058","https://openalex.org/W2288514685","https://openalex.org/W2313356319","https://openalex.org/W2472782738","https://openalex.org/W2529173830","https://openalex.org/W2558906385","https://openalex.org/W2566149141","https://openalex.org/W2583180462","https://openalex.org/W2767836774","https://openalex.org/W2807793257","https://openalex.org/W2888880110","https://openalex.org/W2891156870","https://openalex.org/W2949117887","https://openalex.org/W2963749936","https://openalex.org/W2963828885","https://openalex.org/W2964114039","https://openalex.org/W2964121744","https://openalex.org/W3101840568","https://openalex.org/W6602978295","https://openalex.org/W6612112361","https://openalex.org/W6629803754","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6674330103","https://openalex.org/W6680437723","https://openalex.org/W6682889407","https://openalex.org/W6752289546","https://openalex.org/W6754774487","https://openalex.org/W7008807371"],"related_works":["https://openalex.org/W1990245967","https://openalex.org/W2054177013","https://openalex.org/W4383506493","https://openalex.org/W1994772959","https://openalex.org/W2427340667","https://openalex.org/W3006845356","https://openalex.org/W2359818963","https://openalex.org/W2619578085","https://openalex.org/W2902949665","https://openalex.org/W2187196007"],"abstract_inverted_index":{"Visual":[0,77],"saliency":[1,55,87,97,157,161,170,194,222],"on":[2,56],"stereoscopic":[3],"3D":[4],"(S3D)":[5],"images":[6,58],"has":[7],"been":[8],"shown":[9],"to":[10,39,80,133,138,153,198,216],"be":[11],"heavily":[12],"influenced":[13,99],"by":[14,100],"image":[15,25,28,122],"quality.":[16],"Hence,":[17],"this":[18,67],"dependency":[19],"is":[20,35,98],"an":[21],"important":[22],"factor":[23],"in":[24,45,52,90,127,220],"quality":[26],"prediction,":[27],"restoration":[29],"and":[30,85,105,124,156,165,178],"discomfort":[31],"reduction,":[32],"but":[33],"it":[34,143],"still":[36],"very":[37],"difficult":[38],"predict":[40],"such":[41],"a":[42,71,82,109,151,176,179],"nonlinear":[43],"relation":[44],"images.":[46,65],"In":[47,66],"addition,":[48],"most":[49],"algorithms":[50],"specialized":[51],"detecting":[53],"visual":[54,96,135,169],"pristine":[57],"may":[59],"unsurprisingly":[60],"fail":[61],"when":[62],"facing":[63],"distorted":[64],"paper,":[68],"we":[69,114,163],"investigate":[70],"deep":[72,131,217],"learning":[73,132],"scheme":[74],"named":[75],"Deep":[76],"Saliency":[78],"(DeepVS)":[79],"achieve":[81],"more":[83],"accurate":[84],"reliable":[86],"predictor":[88],"even":[89],"the":[91,128,147,167,192,208,211],"presence":[92],"of":[93,112,130],"distortions.":[94],"Since":[95],"low-level":[101,117,148],"features":[102,118,149,213],"(contrast,":[103],"luminance":[104],"depth":[106],"information)":[107],"from":[108,120,187],"psychophysical":[110],"point":[111],"view,":[113],"propose":[115],"seven":[116],"derived":[119],"S3D":[121,221],"pairs":[123],"utilize":[125],"them":[126],"context":[129],"detect":[134],"attention":[136],"adaptively":[137],"human":[139,168,203],"perception.":[140],"During":[141],"analysis,":[142],"turns":[144],"out":[145],"that":[146,191],"play":[150],"role":[152],"extract":[154],"distortion":[155],"information.":[158],"To":[159],"construct":[160],"predictors,":[162],"weight":[164],"model":[166],"through":[171],"two":[172],"different":[173],"network":[174],"architectures,":[175],"regression":[177],"fully":[180],"convolutional":[181],"neural":[182,218],"networks":[183,219],"(CNNs).":[184],"Our":[185],"results":[186],"thorough":[188],"experiments":[189],"confirm":[190],"predicted":[193],"maps":[195],"are":[196],"up":[197],"70":[199],"%":[200],"correlated":[201],"with":[202],"gaze":[204],"patterns,":[205],"which":[206],"emphasize":[207],"need":[209],"for":[210],"hand-crafted":[212],"as":[214],"input":[215],"detection.":[223]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":5}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}