{"id":"https://openalex.org/W4312406919","doi":"https://doi.org/10.1109/icpr56361.2022.9956339","title":"Weakly Supervised Object Localization Using Long-Range Semantic Foreground Activation","display_name":"Weakly Supervised Object Localization Using Long-Range Semantic Foreground Activation","publication_year":2022,"publication_date":"2022-08-21","ids":{"openalex":"https://openalex.org/W4312406919","doi":"https://doi.org/10.1109/icpr56361.2022.9956339"},"language":"en","primary_location":{"id":"doi:10.1109/icpr56361.2022.9956339","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr56361.2022.9956339","pdf_url":null,"source":{"id":"https://openalex.org/S4363607731","display_name":"2022 26th International Conference on Pattern Recognition (ICPR)","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":"2022 26th International Conference on Pattern Recognition (ICPR)","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/A5060597056","display_name":"Lianxing Wang","orcid":null},"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":"Lianxing Wang","raw_affiliation_strings":["Nanjing University,Department of Control and Systems Engineering,Nanjing,China","Department of Control and Systems Engineering, Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University,Department of Control and Systems Engineering,Nanjing,China","institution_ids":["https://openalex.org/I881766915"]},{"raw_affiliation_string":"Department of Control and Systems Engineering, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076835782","display_name":"Huaxiong Li","orcid":"https://orcid.org/0000-0003-0395-1525"},"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":"Huaxiong Li","raw_affiliation_strings":["Nanjing University,Department of Control and Systems Engineering,Nanjing,China","Department of Control and Systems Engineering, Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University,Department of Control and Systems Engineering,Nanjing,China","institution_ids":["https://openalex.org/I881766915"]},{"raw_affiliation_string":"Department of Control and Systems Engineering, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5060597056"],"corresponding_institution_ids":["https://openalex.org/I881766915"],"apc_list":null,"apc_paid":null,"fwci":0.06,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.31106516,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"4580","last_page":"4586"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","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/T10036","display_name":"Advanced Neural Network Applications","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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9984999895095825,"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"}},{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9980999827384949,"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/discriminative-model","display_name":"Discriminative model","score":0.8826376795768738},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8107720017433167},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7272091507911682},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5856992602348328},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5484673380851746},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.498276948928833},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.48385679721832275},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.42862576246261597},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.41729050874710083},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3222486972808838}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8826376795768738},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8107720017433167},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7272091507911682},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5856992602348328},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5484673380851746},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.498276948928833},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.48385679721832275},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.42862576246261597},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.41729050874710083},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3222486972808838},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","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/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr56361.2022.9956339","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr56361.2022.9956339","pdf_url":null,"source":{"id":"https://openalex.org/S4363607731","display_name":"2022 26th International Conference on Pattern Recognition (ICPR)","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":"2022 26th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7599999904632568}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1686810756","https://openalex.org/W1783315696","https://openalex.org/W1797268635","https://openalex.org/W1849277567","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2097117768","https://openalex.org/W2117539524","https://openalex.org/W2221898772","https://openalex.org/W2295107390","https://openalex.org/W2600144439","https://openalex.org/W2618530766","https://openalex.org/W2883554151","https://openalex.org/W2950557962","https://openalex.org/W2962851944","https://openalex.org/W2963091558","https://openalex.org/W2963603913","https://openalex.org/W2963749936","https://openalex.org/W2963881378","https://openalex.org/W2964274719","https://openalex.org/W2990371274","https://openalex.org/W3024127982","https://openalex.org/W3030520226","https://openalex.org/W3035318183","https://openalex.org/W3094502228","https://openalex.org/W3107169861","https://openalex.org/W3107331169","https://openalex.org/W3110272085","https://openalex.org/W3142837074","https://openalex.org/W3152635971","https://openalex.org/W3170841864","https://openalex.org/W3170874841","https://openalex.org/W3176774696","https://openalex.org/W4293584584","https://openalex.org/W6631782140","https://openalex.org/W6637373629","https://openalex.org/W6638319203","https://openalex.org/W6639204139","https://openalex.org/W6639824700","https://openalex.org/W6685133223","https://openalex.org/W6737160166","https://openalex.org/W6750227808","https://openalex.org/W6778485988","https://openalex.org/W6784333009","https://openalex.org/W6788135285","https://openalex.org/W6788620109","https://openalex.org/W6790830770"],"related_works":["https://openalex.org/W2180954594","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W2052835778","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2049003611","https://openalex.org/W2127804977","https://openalex.org/W2108418243"],"abstract_inverted_index":{"Weakly":[0],"supervised":[1],"object":[2,12],"localization":[3,64],"(WSOL)":[4],"is":[5,85,98,124],"a":[6,81,93,119],"challenging":[7],"task":[8],"to":[9,41,88,100,106,126,137],"find":[10],"the":[11,27,34,54,73,102,151],"location":[13],"using":[14,20],"only":[15,26],"image-level":[16],"supervision.":[17],"Previous":[18],"works":[19],"CNN":[21],"architectures":[22],"stack":[23],"in":[24,157],"finding":[25,35],"most":[28],"discriminative":[29],"parts.":[30],"Transformer-based":[31],"methods":[32],"expand":[33],"areas":[36],"but":[37],"they":[38],"still":[39],"fail":[40],"take":[42],"full":[43],"advantage":[44],"of":[45,75,153],"attention":[46,70,90,104,133],"information.":[47,91],"To":[48],"address":[49],"this":[50],"problem,":[51],"we":[52],"propose":[53],"Long-range":[55],"Semantic":[56],"Foreground":[57],"Activation":[58],"(LSFA)":[59],"method.":[60],"We":[61],"demonstrate":[62,150],"that":[63],"maps":[65,105,134],"should":[66],"be":[67],"generated":[68],"by":[69,112],"parameters":[71],"under":[72],"guidance":[74],"non-discriminative":[76,128],"foreground":[77,121,129],"features.":[78],"In":[79],"LSFA,":[80],"visual":[82],"transformer":[83],"model":[84],"first":[86],"used":[87],"generate":[89],"Then,":[92],"long-range":[94],"dependency":[95],"activation":[96,122],"module":[97,123],"constructed":[99],"help":[101],"learned":[103,131],"focus":[107],"more":[108],"on":[109,143],"global":[110],"information":[111],"weighting":[113],"them":[114],"with":[115,159],"different":[116],"parameters.":[117],"Finally,":[118],"semantic":[120,140],"built":[125],"use":[127],"regions":[130],"from":[132],"as":[135],"indices":[136],"activate":[138],"token":[139],"areas.":[141],"Experiments":[142],"two":[144],"benchmark":[145],"datasets":[146],"CUB-200-2011":[147],"and":[148],"ILSVRC":[149],"superiority":[152],"our":[154],"LSFA":[155],"method":[156],"comparison":[158],"other":[160],"state-of-the-art":[161],"WSOL":[162],"approaches.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
