{"id":"https://openalex.org/W2970089170","doi":"https://doi.org/10.1109/icip.2019.8803672","title":"Classifier Refinement for Weakly Supervised Object Detection with Class-Specific Activation Map","display_name":"Classifier Refinement for Weakly Supervised Object Detection with Class-Specific Activation Map","publication_year":2019,"publication_date":"2019-08-26","ids":{"openalex":"https://openalex.org/W2970089170","doi":"https://doi.org/10.1109/icip.2019.8803672","mag":"2970089170"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2019.8803672","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803672","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5058776553","display_name":"Peilun Du","orcid":"https://orcid.org/0000-0001-9005-4448"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peilun Du","raw_affiliation_strings":["Beijing University of Posts and Telecomm., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecomm., Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100454596","display_name":"Haitao Zhang","orcid":"https://orcid.org/0000-0002-9131-3517"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haitao Zhang","raw_affiliation_strings":["Beijing University of Posts and Telecomm., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecomm., Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100710713","display_name":"Huad\u00f3ng Ma","orcid":"https://orcid.org/0000-0002-7199-5047"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huadong Ma","raw_affiliation_strings":["Beijing University of Posts and Telecomm., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecomm., Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.366,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.65478849,"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":"3367","last_page":"3371"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9995999932289124,"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":0.9993000030517578,"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":0.7594109773635864},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7386714816093445},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7238721251487732},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.6882210969924927},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.6831600666046143},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.680508017539978},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.6673426628112793},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6087182760238647},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5598823428153992},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.4649340808391571},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32882362604141235}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7594109773635864},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7386714816093445},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7238721251487732},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.6882210969924927},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.6831600666046143},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.680508017539978},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.6673426628112793},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6087182760238647},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5598823428153992},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.4649340808391571},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32882362604141235},{"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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2019.8803672","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803672","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","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":31,"referenced_works":["https://openalex.org/W7746136","https://openalex.org/W318792885","https://openalex.org/W1903029394","https://openalex.org/W1934621328","https://openalex.org/W2031489346","https://openalex.org/W2061629163","https://openalex.org/W2088049833","https://openalex.org/W2106841609","https://openalex.org/W2109255472","https://openalex.org/W2133324800","https://openalex.org/W2163605009","https://openalex.org/W2179352600","https://openalex.org/W2220111505","https://openalex.org/W2295107390","https://openalex.org/W2496066288","https://openalex.org/W2519284461","https://openalex.org/W2559348937","https://openalex.org/W2604260814","https://openalex.org/W2813911573","https://openalex.org/W2884195989","https://openalex.org/W2895236117","https://openalex.org/W2962858109","https://openalex.org/W2963603913","https://openalex.org/W6600313631","https://openalex.org/W6611089629","https://openalex.org/W6675803743","https://openalex.org/W6676338569","https://openalex.org/W6684191040","https://openalex.org/W6726508743","https://openalex.org/W6752404337","https://openalex.org/W6753280777"],"related_works":["https://openalex.org/W4237171675","https://openalex.org/W3036286480","https://openalex.org/W4287027631","https://openalex.org/W3192357901","https://openalex.org/W2387360586","https://openalex.org/W2952736415","https://openalex.org/W3209723314","https://openalex.org/W1689909837","https://openalex.org/W2953362004","https://openalex.org/W4298525700"],"abstract_inverted_index":{"Weakly":[0],"Supervised":[1],"Object":[2],"Detection":[3],"(WSOD)":[4],"is":[5],"a":[6,29,86],"challenging":[7],"visual":[8],"understanding":[9],"task":[10],"due":[11],"to":[12,91,126],"the":[13,33,38,42,48,72,79,111,118,123],"absence":[14],"of":[15,37,51,74,122],"expensive":[16],"human":[17],"annotations":[18],"like":[19],"bounding":[20,30],"boxes":[21,77,94,116],"and":[22,66,96,113],"segmentation.":[23],"Recent":[24],"WSOD":[25,87,136],"methods":[26,46],"usually":[27],"generate":[28,114],"box":[31],"for":[32,110],"most":[34],"contrastive":[35],"part":[36],"object":[39,53],"rather":[40],"than":[41],"entire":[43],"object.":[44],"Some":[45],"alleviate":[47],"incompleteness":[49],"problem":[50],"detection":[52],"with":[54,132],"segmentation":[55,61,98,151],"supplement":[56],"or":[57],"classifier":[58,67,88,137],"refinement.":[59],"However,":[60],"requires":[62],"high":[63,97,150],"model":[64,99,152],"cost":[65,100],"refinement":[68,89,129,138],"highly":[69],"relies":[70],"on":[71,144],"quality":[73],"initial":[75],"candidate":[76,93],"at":[78,117],"beginning.":[80],"In":[81],"this":[82],"paper,":[83],"we":[84],"propose":[85],"approach":[90,103,139],"overcome":[92],"initialization":[95],"problems.":[101],"Our":[102],"can":[104,140],"get":[105],"high-quality":[106],"class-specific":[107],"activation":[108,124],"maps":[109],"objects":[112],"nail":[115],"maximum":[119],"response":[120],"point":[121],"map":[125],"suppress":[127],"incorrect":[128],"direction.":[130],"Compared":[131],"previous":[133],"methods,":[134],"our":[135],"achieve":[141],"42.1%":[142],"mAP":[143],"PASCAL":[145],"VOC":[146],"2007":[147],"benchmarks":[148],"without":[149],"cost.":[153]},"counts_by_year":[{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
