{"id":"https://openalex.org/W4224919779","doi":"https://doi.org/10.1109/icassp43922.2022.9746218","title":"Adaptive Intra-Group Aggregation for Co-Saliency Detection","display_name":"Adaptive Intra-Group Aggregation for Co-Saliency Detection","publication_year":2022,"publication_date":"2022-04-27","ids":{"openalex":"https://openalex.org/W4224919779","doi":"https://doi.org/10.1109/icassp43922.2022.9746218"},"language":"en","primary_location":{"id":"doi:10.1109/icassp43922.2022.9746218","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9746218","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5058986919","display_name":"Guangyu Ren","orcid":null},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Guangyu Ren","raw_affiliation_strings":["Imperial College London,United Kingdom","Imperial College London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Imperial College London,United Kingdom","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"Imperial College London, United Kingdom","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084139877","display_name":"Tianhong Dai","orcid":"https://orcid.org/0000-0001-8904-1551"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Tianhong Dai","raw_affiliation_strings":["Imperial College London,United Kingdom","Imperial College London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Imperial College London,United Kingdom","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"Imperial College London, United Kingdom","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028031376","display_name":"Tania Stathaki","orcid":null},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Tania Stathaki","raw_affiliation_strings":["Imperial College London,United Kingdom","Imperial College London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Imperial College London,United Kingdom","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"Imperial College London, United Kingdom","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5058986919"],"corresponding_institution_ids":["https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":0.3598,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.65963211,"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":"2520","last_page":"2524"},"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":0.9962999820709229,"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":0.9872000217437744,"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":0.7923662066459656},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.7236948013305664},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.721092700958252},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.7053786516189575},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6397277116775513},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.6140046119689941},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.6100955605506897},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5701843500137329},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5607765316963196},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5585266351699829},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.48049771785736084},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.45671477913856506},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42802000045776367},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4233909845352173},{"id":"https://openalex.org/keywords/group","display_name":"Group (periodic table)","score":0.42258214950561523}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7923662066459656},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.7236948013305664},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.721092700958252},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.7053786516189575},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6397277116775513},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.6140046119689941},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.6100955605506897},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5701843500137329},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5607765316963196},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5585266351699829},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.48049771785736084},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.45671477913856506},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42802000045776367},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4233909845352173},{"id":"https://openalex.org/C2781311116","wikidata":"https://www.wikidata.org/wiki/Q83306","display_name":"Group (periodic table)","level":2,"score":0.42258214950561523},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp43922.2022.9746218","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9746218","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7599999904632568,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1992992668","https://openalex.org/W2104915577","https://openalex.org/W2314707829","https://openalex.org/W2342491128","https://openalex.org/W2565639579","https://openalex.org/W2615981376","https://openalex.org/W2737677090","https://openalex.org/W2740667773","https://openalex.org/W2954275231","https://openalex.org/W2961348656","https://openalex.org/W2963834057","https://openalex.org/W2964429685","https://openalex.org/W2972640707","https://openalex.org/W2987701848","https://openalex.org/W2990844506","https://openalex.org/W2990984982","https://openalex.org/W2991366018","https://openalex.org/W2998116433","https://openalex.org/W3005827406","https://openalex.org/W3017280272","https://openalex.org/W3034499925","https://openalex.org/W3035666869","https://openalex.org/W3096289386","https://openalex.org/W3211037481","https://openalex.org/W3212325595","https://openalex.org/W6637373629","https://openalex.org/W6675944149","https://openalex.org/W6738422528","https://openalex.org/W6767856356","https://openalex.org/W6776169750"],"related_works":["https://openalex.org/W2363993642","https://openalex.org/W2134990190","https://openalex.org/W2978744676","https://openalex.org/W2382607599","https://openalex.org/W2728071886","https://openalex.org/W4287995534","https://openalex.org/W2998168123","https://openalex.org/W4281760909","https://openalex.org/W2546942002","https://openalex.org/W2970216048"],"abstract_inverted_index":{"Co-salient":[0],"object":[1],"detection":[2],"(CoSOD)":[3],"together":[4],"with":[5],"the":[6,21,56,80,83,94,101,107],"rapid":[7],"development":[8],"of":[9,86],"deep":[10],"learning":[11],"has":[12],"led":[13],"to":[14,54,78],"substantial":[15],"progress":[16],"in":[17,68],"recent":[18],"years.":[19],"However,":[20],"feature":[22,26,30],"aggregation":[23,46],"between":[24,59],"group":[25,60],"representation":[27,31],"and":[28,61,64,89,113],"individual":[29],"is":[32,76],"still":[33],"a":[34,42,51],"challenging":[35],"issue.":[36],"In":[37],"this":[38],"work,":[39],"we":[40],"propose":[41],"novel":[43,73],"adaptive":[44,70],"intra-group":[45],"(AIGA)":[47],"method,":[48],"which":[49],"provides":[50],"new":[52],"perspective":[53],"investigate":[55],"interaction":[57],"relationship":[58],"single-image":[62],"features":[63,67],"aggregate":[65],"these":[66],"an":[69],"way.":[71],"A":[72],"scale-aware":[74],"loss":[75],"proposed":[77,102],"help":[79],"model":[81],"capture":[82],"scale":[84],"prior":[85],"different":[87],"groups":[88,92],"discriminatively":[90],"process":[91],"during":[93],"training":[95],"phase.":[96],"Extensive":[97],"experiments":[98],"demonstrate":[99],"that":[100],"method":[103],"can":[104],"effectively":[105],"improve":[106],"performance":[108],"without":[109],"increasing":[110],"extra":[111],"parameters":[112],"achieve":[114],"better":[115],"accuracy":[116],"on":[117],"three":[118],"prevalent":[119],"benchmarks.":[120]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
