{"id":"https://openalex.org/W4312757076","doi":"https://doi.org/10.1109/icpr56361.2022.9956526","title":"Average Activation Network for Weakly Supervised Semantic Segmentation","display_name":"Average Activation Network for Weakly Supervised Semantic Segmentation","publication_year":2022,"publication_date":"2022-08-21","ids":{"openalex":"https://openalex.org/W4312757076","doi":"https://doi.org/10.1109/icpr56361.2022.9956526"},"language":"en","primary_location":{"id":"doi:10.1109/icpr56361.2022.9956526","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr56361.2022.9956526","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/A5064755127","display_name":"Zhenkun Fan","orcid":"https://orcid.org/0000-0001-9382-5068"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhenkun Fan","raw_affiliation_strings":["AnMai Technology (Ningbo) Co., Ltd"],"affiliations":[{"raw_affiliation_string":"AnMai Technology (Ningbo) Co., Ltd","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015182080","display_name":"Xin Sun","orcid":"https://orcid.org/0000-0003-1870-9037"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Xin Sun","raw_affiliation_strings":["Technical University of Munich,Department of Aerospace and Geodesy,Germany","Department of Aerospace and Geodesy, Technical University of Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Technical University of Munich,Department of Aerospace and Geodesy,Germany","institution_ids":["https://openalex.org/I62916508"]},{"raw_affiliation_string":"Department of Aerospace and Geodesy, Technical University of Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029633264","display_name":"Junyu Dong","orcid":"https://orcid.org/0000-0001-7012-2087"},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junyu Dong","raw_affiliation_strings":["Ocean University of China,Department of Computer Science and Technology,Qingdao,China,266100"],"affiliations":[{"raw_affiliation_string":"Ocean University of China,Department of Computer Science and Technology,Qingdao,China,266100","institution_ids":["https://openalex.org/I59028903"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5064755127"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15350064,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"24","issue":null,"first_page":"657","last_page":"662"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9994000196456909,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9968000054359436,"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/segmentation","display_name":"Segmentation","score":0.7604910135269165},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7107100486755371},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6809407472610474},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6761829853057861},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.6691708564758301},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5665450692176819},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.529585063457489},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.5057258605957031},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.46707087755203247},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.431648313999176},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.41341841220855713},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32723337411880493},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.32029497623443604}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7604910135269165},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7107100486755371},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6809407472610474},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6761829853057861},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.6691708564758301},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5665450692176819},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.529585063457489},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.5057258605957031},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.46707087755203247},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.431648313999176},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.41341841220855713},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32723337411880493},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.32029497623443604},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr56361.2022.9956526","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr56361.2022.9956526","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":[{"display_name":"Reduced inequalities","score":0.7599999904632568,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324174","display_name":"Natural Science Foundation of Shandong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W2031489346","https://openalex.org/W2133515615","https://openalex.org/W2161236525","https://openalex.org/W2221898772","https://openalex.org/W2295107390","https://openalex.org/W2306289963","https://openalex.org/W2600144439","https://openalex.org/W2630837129","https://openalex.org/W2798376494","https://openalex.org/W2798715809","https://openalex.org/W2799124825","https://openalex.org/W2952793010","https://openalex.org/W2962758679","https://openalex.org/W2962867364","https://openalex.org/W2963977581","https://openalex.org/W2964274719","https://openalex.org/W2980189057","https://openalex.org/W2991662170","https://openalex.org/W2997851315","https://openalex.org/W3034373787","https://openalex.org/W3034930876","https://openalex.org/W3166286626","https://openalex.org/W3169761117","https://openalex.org/W4289367614","https://openalex.org/W6739696289","https://openalex.org/W6755402806"],"related_works":["https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W1482209366","https://openalex.org/W2110523656","https://openalex.org/W2521627374","https://openalex.org/W2981954115"],"abstract_inverted_index":{"Most":[0],"current":[1],"image-level":[2],"weakly":[3,21,67],"supervised":[4,22],"semantic":[5,23,125],"segmentation":[6,24,126],"(WSSS)":[7],"methods":[8],"are":[9],"based":[10],"on":[11,36,84,133],"class":[12],"activation":[13,57,73,87],"map":[14],"(CAM).":[15],"However,":[16],"the":[17,27,31,37,42,45,49,63,71,76,81,85,90,93,105,108,121,134,141],"main":[18],"limitation":[19],"of":[20,41,62,75,89,107,143],"is":[25],"that":[26],"CAMs":[28,61],"generated":[29],"by":[30,78],"WSSS":[32],"network":[33,58,100],"always":[34],"focus":[35],"most":[38],"discriminative":[39],"parts":[40],"object,":[43],"limiting":[44],"CAM":[46,77,91,115],"to":[47,59,104,119,139],"capture":[48],"holistic":[50,64],"object.":[51,109],"So":[52],"we":[53,112],"propose":[54,113],"an":[55],"average":[56],"generate":[60],"object":[65],"with":[66],"supervision.":[68],"We":[69,130],"restrain":[70],"highest":[72],"regions":[74],"continuously":[79],"splitting":[80],"training":[82,94],"image":[83],"maximum":[86],"point":[88],"during":[92],"process.":[95],"In":[96,110],"this":[97],"way,":[98],"our":[99,144],"pays":[101],"more":[102],"attention":[103],"whole":[106],"addition,":[111],"a":[114],"similarity":[116],"loss":[117],"function":[118],"narrow":[120],"gap":[122],"between":[123],"fully-supervised":[124],"(FSSS)":[127],"and":[128],"WSSS.":[129],"conducted":[131],"experiments":[132],"PASCAL":[135],"VOC":[136],"2012":[137],"dataset":[138],"validate":[140],"effectiveness":[142],"method.":[145]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}