{"id":"https://openalex.org/W2982110796","doi":"https://doi.org/10.1145/3343031.3351016","title":"Co-saliency Detection Based on Hierarchical Consistency","display_name":"Co-saliency Detection Based on Hierarchical Consistency","publication_year":2019,"publication_date":"2019-10-15","ids":{"openalex":"https://openalex.org/W2982110796","doi":"https://doi.org/10.1145/3343031.3351016","mag":"2982110796"},"language":"en","primary_location":{"id":"doi:10.1145/3343031.3351016","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3343031.3351016","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th 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/A5100374360","display_name":"Bo Li","orcid":"https://orcid.org/0000-0001-6709-0942"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bo Li","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073588743","display_name":"Zhengxing Sun","orcid":"https://orcid.org/0000-0001-7137-6169"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengxing Sun","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100418247","display_name":"Quan Wang","orcid":"https://orcid.org/0000-0001-6913-8604"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quan Wang","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100340635","display_name":"Qian Li","orcid":"https://orcid.org/0000-0002-9530-4925"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qian Li","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100374360"],"corresponding_institution_ids":["https://openalex.org/I881766915"],"apc_list":null,"apc_paid":null,"fwci":1.4171,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.85686218,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1392","last_page":"1400"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":1.0,"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":1.0,"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":0.9940000176429749,"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":0.9887999892234802,"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/consistency","display_name":"Consistency (knowledge bases)","score":0.8359979391098022},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.7572672367095947},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7381539940834045},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.7215541005134583},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6714451313018799},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.598884105682373},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5412116050720215},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4908083379268646},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4743267893791199},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.4270387291908264},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4269925355911255},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3917217552661896},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3441891670227051},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.20013371109962463}],"concepts":[{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.8359979391098022},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.7572672367095947},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7381539940834045},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7215541005134583},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6714451313018799},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.598884105682373},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5412116050720215},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4908083379268646},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4743267893791199},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.4270387291908264},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4269925355911255},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3917217552661896},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3441891670227051},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.20013371109962463},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3343031.3351016","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3343031.3351016","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1964884769","https://openalex.org/W1969733239","https://openalex.org/W1986811142","https://openalex.org/W1991367009","https://openalex.org/W1992992668","https://openalex.org/W1995443851","https://openalex.org/W2007685793","https://openalex.org/W2037183649","https://openalex.org/W2039313011","https://openalex.org/W2069241582","https://openalex.org/W2074417978","https://openalex.org/W2080142539","https://openalex.org/W2084798549","https://openalex.org/W2087100776","https://openalex.org/W2090518410","https://openalex.org/W2109255472","https://openalex.org/W2112553126","https://openalex.org/W2141303268","https://openalex.org/W2153760331","https://openalex.org/W2161236525","https://openalex.org/W2165232124","https://openalex.org/W2282640221","https://openalex.org/W2342491128","https://openalex.org/W2358876993","https://openalex.org/W2403333215","https://openalex.org/W2415053570","https://openalex.org/W2422471819","https://openalex.org/W2475287302","https://openalex.org/W2605793178","https://openalex.org/W2605929543","https://openalex.org/W2615981376","https://openalex.org/W2773771410","https://openalex.org/W2895136135","https://openalex.org/W2896535068","https://openalex.org/W2951004968","https://openalex.org/W2963223306","https://openalex.org/W2963834057","https://openalex.org/W2963868681"],"related_works":["https://openalex.org/W2159052453","https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2752972570","https://openalex.org/W4297051394","https://openalex.org/W2734887215","https://openalex.org/W2803255133","https://openalex.org/W2909431601","https://openalex.org/W4294770367"],"abstract_inverted_index":{"As":[0],"an":[1],"interesting":[2],"and":[3,12,58,99,149],"emerging":[4],"topic,":[5],"co-saliency":[6,82,155],"detection":[7,83],"aims":[8],"at":[9],"discovering":[10],"common":[11],"salient":[13,121,143,169],"objects":[14,101,122,144,170],"in":[15,69,91,103],"a":[16,31,79,104,110,135,161],"group":[17,94],"of":[18,26,33,43],"related":[19],"images,":[20],"which":[21,65,85],"is":[22],"useful":[23],"to":[24,38,117,139,188],"variety":[25],"visual":[27],"media":[28],"applications.":[29],"Although":[30],"number":[32],"approaches":[34],"have":[35],"been":[36],"proposed":[37],"address":[39],"this":[40],"problem,":[41],"many":[42],"them":[44],"are":[45,157],"designed":[46],"with":[47,166],"the":[48,70,88,92,120,124,129,141,154,167,189],"misleading":[49],"assumption,":[50],"suboptimal":[51],"image":[52,93],"representation,":[53],"or":[54,184],"heavy":[55],"supervision":[56],"cost":[57],"thus":[59],"still":[60],"suffer":[61],"from":[62,123],"certain":[63],"limitations,":[64,76],"reduces":[66],"their":[67],"capability":[68],"real-world":[71],"scenarios.":[72],"To":[73],"alleviate":[74],"these":[75],"we":[77,133],"propose":[78,134],"novel":[80,111],"unsupervised":[81],"method,":[84],"successively":[86],"explores":[87],"hierarchical":[89],"consistency":[90,102,145],"including":[95],"background":[96,125],"consistency,":[97],"high-level":[98,148],"low-level":[100,150],"unified":[105],"framework.":[106],"We":[107],"first":[108],"design":[109],"superpixel-wise":[112],"variational":[113],"autoencoder":[114],"(SVAE)":[115],"network":[116],"precisely":[118],"distinguish":[119],"collection":[126],"based":[127,163],"on":[128,174],"reconstruction":[130],"errors.":[131],"Then,":[132],"two-stage":[136],"clustering":[137],"strategy":[138],"explore":[140],"multi-level":[142,168],"by":[146,159],"using":[147],"features":[151],"separately.":[152],"Finally,":[153],"results":[156],"refined":[158],"applying":[160],"CRF":[162],"refinement":[164],"method":[165,181],"consistency.":[171],"Extensive":[172],"experiments":[173],"three":[175],"widely":[176],"datasets":[177],"show":[178],"that":[179],"our":[180],"achieves":[182],"superior":[183],"competitive":[185],"performance":[186],"compared":[187],"state-of-the-art":[190],"methods.":[191]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}