{"id":"https://openalex.org/W3000563843","doi":"https://doi.org/10.1145/3338533.3366567","title":"Adaptive Bilinear Pooling for Fine-grained Representation Learning","display_name":"Adaptive Bilinear Pooling for Fine-grained Representation Learning","publication_year":2019,"publication_date":"2019-12-15","ids":{"openalex":"https://openalex.org/W3000563843","doi":"https://doi.org/10.1145/3338533.3366567","mag":"3000563843"},"language":"en","primary_location":{"id":"doi:10.1145/3338533.3366567","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3338533.3366567","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Multimedia Asia","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/A5036335729","display_name":"Shaobo Min","orcid":"https://orcid.org/0000-0002-7700-2149"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shaobo Min","raw_affiliation_strings":["University of Science and Technology of China, Guizhou Provincial Key Laboratory of Public Big Data"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Guizhou Provincial Key Laboratory of Public Big Data","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078162380","display_name":"Hongtao Xie","orcid":"https://orcid.org/0000-0002-6249-5315"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongtao Xie","raw_affiliation_strings":["University of Science and Technology of China, Guizhou Provincial Key Laboratory of Public Big Data"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Guizhou Provincial Key Laboratory of Public Big Data","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052363813","display_name":"Youliang Tian","orcid":"https://orcid.org/0000-0002-5974-1570"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youliang Tian","raw_affiliation_strings":["GuiZhou University, Guizhou, Provincial Key Laboratory of Public Big Data"],"affiliations":[{"raw_affiliation_string":"GuiZhou University, Guizhou, Provincial Key Laboratory of Public Big Data","institution_ids":["https://openalex.org/I178232147"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018564842","display_name":"Hantao Yao","orcid":"https://orcid.org/0000-0001-8125-2864"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hantao Yao","raw_affiliation_strings":["National Laboratory of Pattern, Recognition, Institute of Automation, Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern, Recognition, Institute of Automation, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046305086","display_name":"Yongdong Zhang","orcid":"https://orcid.org/0000-0002-1151-1792"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongdong Zhang","raw_affiliation_strings":["University of Science and Technology of China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5036335729"],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":0.4201,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.72530032,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998000264167786,"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":0.9997000098228455,"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/T10812","display_name":"Human Pose and Action Recognition","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"}}],"keywords":[{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.9201581478118896},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7923420667648315},{"id":"https://openalex.org/keywords/bilinear-interpolation","display_name":"Bilinear interpolation","score":0.7649933099746704},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.6849353313446045},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.646718442440033},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6331747770309448},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6219849586486816},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6137374639511108},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5672639012336731},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34511345624923706},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.22754007577896118}],"concepts":[{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.9201581478118896},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7923420667648315},{"id":"https://openalex.org/C205203396","wikidata":"https://www.wikidata.org/wiki/Q612143","display_name":"Bilinear interpolation","level":2,"score":0.7649933099746704},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.6849353313446045},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.646718442440033},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6331747770309448},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6219849586486816},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6137374639511108},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5672639012336731},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34511345624923706},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.22754007577896118},{"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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/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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3338533.3366567","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3338533.3366567","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Multimedia Asia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7799999713897705}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W874179280","https://openalex.org/W1496650988","https://openalex.org/W1511568086","https://openalex.org/W1797268635","https://openalex.org/W1928906481","https://openalex.org/W2104657103","https://openalex.org/W2118330267","https://openalex.org/W2138011018","https://openalex.org/W2146897752","https://openalex.org/W2160841154","https://openalex.org/W2170027846","https://openalex.org/W2554320282","https://openalex.org/W2604134068","https://openalex.org/W2737725206","https://openalex.org/W2740620254","https://openalex.org/W2752386593","https://openalex.org/W2752965000","https://openalex.org/W2763070548","https://openalex.org/W2780838211","https://openalex.org/W2788195014","https://openalex.org/W2798898313","https://openalex.org/W2883502031","https://openalex.org/W2898041613","https://openalex.org/W2946781947","https://openalex.org/W2963015611","https://openalex.org/W2963066927","https://openalex.org/W2963725249","https://openalex.org/W2963925503","https://openalex.org/W2964275061","https://openalex.org/W2981648435","https://openalex.org/W2997351497","https://openalex.org/W4291119380","https://openalex.org/W6741605058"],"related_works":["https://openalex.org/W2950524887","https://openalex.org/W2883502031","https://openalex.org/W2261271299","https://openalex.org/W4285020665","https://openalex.org/W2963066927","https://openalex.org/W4280638452","https://openalex.org/W3111811104","https://openalex.org/W4380083739","https://openalex.org/W2964944724","https://openalex.org/W3160506688"],"abstract_inverted_index":{"Fine-grained":[0],"representation":[1,25],"learning":[2,89,92,97,101,124],"targets":[3],"to":[4,40,113,126,160],"generate":[5],"discriminative":[6],"description":[7],"for":[8,76],"fine-grained":[9,186],"visual":[10,116,176],"objects.":[11],"Recently,":[12],"the":[13,31,45,133,142,162,193,196],"bilinear":[14,151],"feature":[15,37,60,152],"interaction":[16,38,61],"has":[17],"been":[18],"proved":[19],"effective":[20],"in":[21,50],"generating":[22],"powerful":[23],"high-order":[24],"with":[26,149],"spatially":[27],"invariant":[28],"information.":[29],"However,":[30],"existing":[32],"methods":[33],"apply":[34],"a":[35,51,58,72,77,109,128,154],"fixed":[36,110],"strategy":[39,75],"all":[41],"samples,":[42],"which":[43,68,139],"ignore":[44],"image":[46,82,143],"and":[47,94,164,189],"region":[48],"heterogeneity":[49],"dataset.":[52],"To":[53,145],"this":[54],"end,":[55],"we":[56],"propose":[57],"generalized":[59],"method,":[62],"named":[63],"Adaptive":[64],"Bilinear":[65],"Pooling":[66],"(ABP),":[67],"can":[69,140,168],"adaptively":[70],"infer":[71,127],"suitable":[73],"pooling":[74],"given":[78],"sample":[79],"based":[80],"on":[81,180],"content.":[83],"Specifically,":[84],"ABP":[85,147],"consists":[86],"of":[87,135,195],"two":[88,174],"strategies:":[90],"p-order":[91,100],"(P-net)":[93],"spatial":[95,122],"attention":[96,123],"(S-net).":[98],"The":[99,121,178],"predicts":[102],"an":[103,119],"optimal":[104],"exponential":[105],"coefficient":[106],"rather":[107],"than":[108],"order":[111],"number":[112],"extract":[114],"moderate":[115],"information":[117,171],"from":[118],"image.":[120],"aims":[125],"weighted":[129],"score":[130],"that":[131],"measures":[132],"importance":[134],"each":[136],"local":[137],"region,":[138],"compact":[141],"representations.":[144],"make":[146],"compatible":[148],"kernelized":[150],"interaction,":[153],"crossed":[155],"two-branch":[156],"structure":[157,167],"is":[158],"utilized":[159],"combine":[161],"P-net":[163],"S-net.":[165],"This":[166],"facilitate":[169],"complementary":[170],"exchange":[172],"between":[173],"different":[175],"branches.":[177],"experiments":[179],"three":[181],"widely":[182],"used":[183],"benchmarks,":[184],"including":[185],"object":[187],"classification":[188],"action":[190],"recognition,":[191],"demonstrate":[192],"effectiveness":[194],"proposed":[197],"method.":[198]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
