{"id":"https://openalex.org/W4301146083","doi":"https://doi.org/10.1109/tmm.2022.3198314","title":"SRRNet: A Semantic Representation Refinement Network for Image Segmentation","display_name":"SRRNet: A Semantic Representation Refinement Network for Image Segmentation","publication_year":2022,"publication_date":"2022-08-11","ids":{"openalex":"https://openalex.org/W4301146083","doi":"https://doi.org/10.1109/tmm.2022.3198314"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2022.3198314","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2022.3198314","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-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/A5001257681","display_name":"Xiaofeng Ding","orcid":"https://orcid.org/0000-0003-1261-5195"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaofeng Ding","raw_affiliation_strings":["Department of Mathematics, School of Science, Shanghai University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, School of Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059443966","display_name":"Tieyong Zeng","orcid":"https://orcid.org/0000-0002-0688-202X"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Tieyong Zeng","raw_affiliation_strings":["Department of Mathematics, Chinese University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Chinese University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039176528","display_name":"Jian Tang","orcid":"https://orcid.org/0000-0003-4418-0114"},"institutions":[{"id":"https://openalex.org/I4210093653","display_name":"Midea Group (China)","ror":"https://ror.org/006fm2278","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210093653"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Tang","raw_affiliation_strings":["Midea Group, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Midea Group, Shanghai, China","institution_ids":["https://openalex.org/I4210093653"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079044416","display_name":"Zhengping Che","orcid":"https://orcid.org/0000-0001-6818-1125"},"institutions":[{"id":"https://openalex.org/I4210093653","display_name":"Midea Group (China)","ror":"https://ror.org/006fm2278","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210093653"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengping Che","raw_affiliation_strings":["Midea Group, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Midea Group, Shanghai, China","institution_ids":["https://openalex.org/I4210093653"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033203506","display_name":"Yaxin Peng","orcid":"https://orcid.org/0000-0002-2983-555X"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaxin Peng","raw_affiliation_strings":["Department of Mathematics, School of Science, Shanghai University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, School of Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5001257681"],"corresponding_institution_ids":["https://openalex.org/I113940042"],"apc_list":null,"apc_paid":null,"fwci":0.8151,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.73277727,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"25","issue":null,"first_page":"5720","last_page":"5732"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","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/T10036","display_name":"Advanced Neural Network Applications","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/T11714","display_name":"Multimodal Machine Learning Applications","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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.8085116147994995},{"id":"https://openalex.org/keywords/semantic-computing","display_name":"Semantic computing","score":0.6195166707038879},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5849522948265076},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.5724267959594727},{"id":"https://openalex.org/keywords/semantic-gap","display_name":"Semantic gap","score":0.5357071161270142},{"id":"https://openalex.org/keywords/semantic-compression","display_name":"Semantic compression","score":0.4756338596343994},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.47529637813568115},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46714848279953003},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.46616464853286743},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4660647213459015},{"id":"https://openalex.org/keywords/semantic-search","display_name":"Semantic search","score":0.46545296907424927},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4487343430519104},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.41998082399368286},{"id":"https://openalex.org/keywords/semantic-technology","display_name":"Semantic technology","score":0.3636631965637207},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.34734901785850525},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.195072740316391},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.16331061720848083},{"id":"https://openalex.org/keywords/semantic-web","display_name":"Semantic Web","score":0.06841570138931274}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8085116147994995},{"id":"https://openalex.org/C511149849","wikidata":"https://www.wikidata.org/wiki/Q7449051","display_name":"Semantic computing","level":3,"score":0.6195166707038879},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5849522948265076},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.5724267959594727},{"id":"https://openalex.org/C86034646","wikidata":"https://www.wikidata.org/wiki/Q474311","display_name":"Semantic gap","level":4,"score":0.5357071161270142},{"id":"https://openalex.org/C202708506","wikidata":"https://www.wikidata.org/wiki/Q7449050","display_name":"Semantic compression","level":5,"score":0.4756338596343994},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.47529637813568115},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46714848279953003},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.46616464853286743},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4660647213459015},{"id":"https://openalex.org/C166423231","wikidata":"https://www.wikidata.org/wiki/Q1891170","display_name":"Semantic search","level":3,"score":0.46545296907424927},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4487343430519104},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.41998082399368286},{"id":"https://openalex.org/C6881194","wikidata":"https://www.wikidata.org/wiki/Q7449091","display_name":"Semantic technology","level":4,"score":0.3636631965637207},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.34734901785850525},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.195072740316391},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.16331061720848083},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.06841570138931274},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2022.3198314","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2022.3198314","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1113331884","display_name":null,"funder_award_id":"20XD1421700","funder_id":"https://openalex.org/F4320335796","funder_display_name":"Program of Shanghai Academic Research Leader"},{"id":"https://openalex.org/G5221450027","display_name":null,"funder_award_id":"11771276","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5563675220","display_name":null,"funder_award_id":"20SG40","funder_id":"https://openalex.org/F4320321881","funder_display_name":"Shanghai Municipal Education Commission"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321659","display_name":"Shanghai Education Development Foundation","ror":"https://ror.org/02kq92y46"},{"id":"https://openalex.org/F4320321881","display_name":"Shanghai Municipal Education Commission","ror":"https://ror.org/05tewj457"},{"id":"https://openalex.org/F4320335796","display_name":"Program of Shanghai Academic Research Leader","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":93,"referenced_works":["https://openalex.org/W1601741105","https://openalex.org/W1686810756","https://openalex.org/W1745334888","https://openalex.org/W1867429401","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2031489346","https://openalex.org/W2044593983","https://openalex.org/W2074398519","https://openalex.org/W2124592697","https://openalex.org/W2125215748","https://openalex.org/W2144794286","https://openalex.org/W2150066425","https://openalex.org/W2161236525","https://openalex.org/W2168894214","https://openalex.org/W2194775991","https://openalex.org/W2340897893","https://openalex.org/W2412782625","https://openalex.org/W2473131906","https://openalex.org/W2560023338","https://openalex.org/W2563705555","https://openalex.org/W2739253758","https://openalex.org/W2752782242","https://openalex.org/W2776638780","https://openalex.org/W2798791840","https://openalex.org/W2799166040","https://openalex.org/W2799213142","https://openalex.org/W2886934227","https://openalex.org/W2895340641","https://openalex.org/W2903642350","https://openalex.org/W2943351376","https://openalex.org/W2948080074","https://openalex.org/W2952793010","https://openalex.org/W2955058313","https://openalex.org/W2955813853","https://openalex.org/W2963091558","https://openalex.org/W2963108253","https://openalex.org/W2963563573","https://openalex.org/W2963727650","https://openalex.org/W2963881378","https://openalex.org/W2964309882","https://openalex.org/W2965391153","https://openalex.org/W2981689412","https://openalex.org/W2981899103","https://openalex.org/W2982805640","https://openalex.org/W2985276900","https://openalex.org/W2985459778","https://openalex.org/W2989684653","https://openalex.org/W2990775046","https://openalex.org/W2991062542","https://openalex.org/W2999725795","https://openalex.org/W3001433222","https://openalex.org/W3009337785","https://openalex.org/W3016889634","https://openalex.org/W3034502973","https://openalex.org/W3034681889","https://openalex.org/W3034815155","https://openalex.org/W3035339581","https://openalex.org/W3035526186","https://openalex.org/W3035531015","https://openalex.org/W3041273049","https://openalex.org/W3047385447","https://openalex.org/W3097762837","https://openalex.org/W3107634219","https://openalex.org/W3108139472","https://openalex.org/W3108450508","https://openalex.org/W3108591672","https://openalex.org/W3109301572","https://openalex.org/W3115781494","https://openalex.org/W3118882604","https://openalex.org/W3122412340","https://openalex.org/W3165745140","https://openalex.org/W3170410460","https://openalex.org/W3170841864","https://openalex.org/W3199130398","https://openalex.org/W3204874447","https://openalex.org/W3210786719","https://openalex.org/W3211490618","https://openalex.org/W3211512919","https://openalex.org/W3213165621","https://openalex.org/W4214554179","https://openalex.org/W4214893857","https://openalex.org/W4220989862","https://openalex.org/W4226342918","https://openalex.org/W4385245566","https://openalex.org/W6637373629","https://openalex.org/W6639824700","https://openalex.org/W6684665197","https://openalex.org/W6739901393","https://openalex.org/W6748481559","https://openalex.org/W6797399245","https://openalex.org/W6798837711","https://openalex.org/W6803632499"],"related_works":["https://openalex.org/W3134365128","https://openalex.org/W2365852568","https://openalex.org/W1589762743","https://openalex.org/W2363443447","https://openalex.org/W2382028126","https://openalex.org/W2133831373","https://openalex.org/W2174630793","https://openalex.org/W2156467700","https://openalex.org/W3183710995","https://openalex.org/W1497307167"],"abstract_inverted_index":{"Semantic":[0],"context":[1,106],"has":[2],"raised":[3],"concerns":[4],"in":[5,95],"semantic":[6,26,46,53,57,69,85,105,111,138,154],"segmentation.":[7],"In":[8],"most":[9],"cases,":[10],"it":[11,22,99,114,131],"is":[12],"applied":[13],"to":[14,23,135],"guide":[15],"feature":[16,32],"learning.":[17],"Instead,":[18],"this":[19],"paper":[20],"applies":[21],"extract":[24],"the":[25,30,68,73,77,81,91,101,116,126,146,153,158,162,172,180],"representation,":[27],"which":[28,50],"records":[29],"global":[31,109,123],"information":[33],"of":[34,52,90,104,118,125,161],"each":[35],"category":[36],"with":[37,84],"a":[38,44,137],"memory":[39,74],"tensor.":[40],"Specifically,":[41],"we":[42],"propose":[43],"novel":[45],"representation":[47,70,102,139],"(SR)":[48],"module,":[49],"consists":[51],"embedding":[54],"(SE)":[55],"and":[56,76,129,156,175,185],"attention":[58],"(SA)":[59],"blocks.":[60],"The":[61,87],"SE":[62],"block":[63,79],"adaptively":[64],"embeds":[65],"features":[66,83,120,124],"into":[67],"by":[71,107,121,143],"calculating":[72],"similarity,":[75],"SA":[78],"aggregates":[80],"embedded":[82],"attention.":[86],"main":[88],"advantages":[89],"SR":[92,147],"module":[93,148],"lie":[94],"three":[96],"aspects:":[97],"i)":[98],"enhances":[100],"ability":[103],"employing":[108],"(cross-image)":[110],"information;":[112],"ii)":[113],"improves":[115,171],"consistency":[117],"intraclass":[119],"aggregating":[122],"same":[127],"categories;":[128],"iii)":[130],"can":[132],"be":[133],"extended":[134],"build":[136],"refinement":[140],"network":[141],"(SRRNet)":[142],"iteratively":[144],"applying":[145],"across":[149],"multiple":[150],"scales,":[151],"shrinking":[152],"gap":[155],"enhancing":[157],"structural":[159],"reasoning":[160],"model.":[163],"Extensive":[164],"experiments":[165],"demonstrate":[166],"that":[167],"our":[168],"method":[169],"significantly":[170],"segmentation":[173],"results":[174],"achieves":[176],"superior":[177],"performance":[178],"on":[179],"PASCAL":[181,186],"VOC":[182],"2012,":[183],"Cityscapes,":[184],"Context":[187],"datasets.":[188]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}