{"id":"https://openalex.org/W2808091730","doi":"https://doi.org/10.24963/ijcai.2018/171","title":"Centralized Ranking Loss with Weakly Supervised Localization for Fine-Grained Object Retrieval","display_name":"Centralized Ranking Loss with Weakly Supervised Localization for Fine-Grained Object Retrieval","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2808091730","doi":"https://doi.org/10.24963/ijcai.2018/171","mag":"2808091730"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2018/171","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/171","pdf_url":"https://www.ijcai.org/proceedings/2018/0171.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2018/0171.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054226277","display_name":"Xiawu Zheng","orcid":"https://orcid.org/0000-0002-6855-5403"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiawu Zheng","raw_affiliation_strings":["Fujian Key Laboratory of Sensing and Computing for Smart City, Xiamen University","School of Information Science and Engineering, Xiamen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fujian Key Laboratory of Sensing and Computing for Smart City, Xiamen University","institution_ids":["https://openalex.org/I191208505"]},{"raw_affiliation_string":"School of Information Science and Engineering, Xiamen University","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016080094","display_name":"Rongrong Ji","orcid":"https://orcid.org/0000-0001-9163-2932"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rongrong Ji","raw_affiliation_strings":["Fujian Key Laboratory of Sensing and Computing for Smart City, Xiamen University","School of Information Science and Engineering, Xiamen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fujian Key Laboratory of Sensing and Computing for Smart City, Xiamen University","institution_ids":["https://openalex.org/I191208505"]},{"raw_affiliation_string":"School of Information Science and Engineering, Xiamen University","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059926864","display_name":"Xiaoshuai Sun","orcid":"https://orcid.org/0000-0003-3912-9306"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoshuai Sun","raw_affiliation_strings":["Harbin Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100716576","display_name":"Yongjian Wu","orcid":"https://orcid.org/0000-0003-2007-6929"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongjian Wu","raw_affiliation_strings":["Tencent Technology (Shanghai) Co.,Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent Technology (Shanghai) Co.,Ltd","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112601777","display_name":"Feiyue Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feiyue Huang","raw_affiliation_strings":["Tencent Technology (Shanghai) Co.,Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent Technology (Shanghai) Co.,Ltd","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035747364","display_name":"Yanhua Yang","orcid":"https://orcid.org/0000-0002-7916-3683"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanhua Yang","raw_affiliation_strings":["Xidian University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian University","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.4338,"has_fulltext":false,"cited_by_count":64,"citation_normalized_percentile":{"value":0.93747461,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1226","last_page":"1233"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","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/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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9962999820709229,"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":0.8348332643508911},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8016905188560486},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7341660261154175},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7168415784835815},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.6564831733703613},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6374791860580444},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6184276342391968},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6152802109718323},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5690052509307861},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5589522123336792},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.5539820194244385},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5521385669708252},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.5405030250549316},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5332728624343872},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5304414629936218},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5275720357894897},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.5206443667411804},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.426960825920105},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38524729013442993},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3071194887161255},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08255583047866821}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8348332643508911},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8016905188560486},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7341660261154175},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7168415784835815},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.6564831733703613},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6374791860580444},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6184276342391968},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6152802109718323},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5690052509307861},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5589522123336792},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.5539820194244385},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5521385669708252},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.5405030250549316},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5332728624343872},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5304414629936218},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5275720357894897},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.5206443667411804},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.426960825920105},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38524729013442993},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3071194887161255},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08255583047866821},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2018/171","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/171","pdf_url":"https://www.ijcai.org/proceedings/2018/0171.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2018/171","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/171","pdf_url":"https://www.ijcai.org/proceedings/2018/0171.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7099999785423279}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2808091730.pdf","grobid_xml":"https://content.openalex.org/works/W2808091730.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W744862910","https://openalex.org/W1496650988","https://openalex.org/W1686810756","https://openalex.org/W1797268635","https://openalex.org/W1898560071","https://openalex.org/W1903029394","https://openalex.org/W1928906481","https://openalex.org/W1975517671","https://openalex.org/W1980526845","https://openalex.org/W1995525705","https://openalex.org/W2021354639","https://openalex.org/W2108598243","https://openalex.org/W2124351162","https://openalex.org/W2138011018","https://openalex.org/W2295107390","https://openalex.org/W2479109623","https://openalex.org/W2520774990","https://openalex.org/W2543665857","https://openalex.org/W2547446130","https://openalex.org/W2555897561","https://openalex.org/W2613997951","https://openalex.org/W2768202427","https://openalex.org/W2962851944","https://openalex.org/W2963026686","https://openalex.org/W2963090248","https://openalex.org/W2963177757","https://openalex.org/W2964189431","https://openalex.org/W3099206234","https://openalex.org/W4239072543","https://openalex.org/W4308909683","https://openalex.org/W4385490361"],"related_works":["https://openalex.org/W2058965144","https://openalex.org/W2164382479","https://openalex.org/W2146343568","https://openalex.org/W98480971","https://openalex.org/W2150291671","https://openalex.org/W2013643406","https://openalex.org/W2027972911","https://openalex.org/W2157978810","https://openalex.org/W4391547476","https://openalex.org/W2597809628"],"abstract_inverted_index":{"Fine-grained":[0],"object":[1,44,81,134],"retrieval":[2,82],"has":[3],"attracted":[4],"extensive":[5,22],"research":[6],"focus":[7],"recently.":[8],"Its":[9],"state-of-the-art":[10,194],"schemesare":[11],"typically":[12],"based":[13],"upon":[14],"convolutional":[15],"neural":[16],"network":[17],"(CNN)":[18],"features.":[19,72],"Despite":[20],"the":[21,31,53,111,140,145,154,162,176,193],"progress,":[23],"two":[24],"issues":[25,87],"remain":[26],"open.":[27],"On":[28,52],"one":[29],"hand,":[30,55],"deep":[32],"features":[33,58,152],"are":[34,47,142],"coarsely":[35],"extracted":[36],"at":[37,43],"image":[38],"level":[39],"rather":[40],"than":[41],"precisely":[42,150],"level,":[45],"which":[46,101,132],"interrupted":[48],"by":[49,118],"background":[50],"clutters.":[51],"other":[54],"training":[56,107],"CNN":[57,146],"with":[59,136],"a":[60,78,89,95,103,119,124],"standard":[61],"triplet":[62,112],"loss":[63,99],"is":[64,130],"time":[65],"consuming":[66],"and":[67,114,166,186,205],"incapable":[68],"to":[69,110,149],"learn":[70],"discriminative":[71,115],"In":[73],"this":[74],"paper,":[75],"we":[76,93,158],"present":[77],"novel":[79,96],"fine-grained":[80],"scheme":[83,180],"that":[84,161],"conquers":[85],"these":[86],"in":[88],"unified":[90],"framework.":[91],"Firstly,":[92],"introduce":[94],"centralized":[97],"ranking":[98],"(CRL),":[100],"achieves":[102],"very":[104],"efficient":[105],"(1,000times":[106],"speedup":[108],"comparing":[109],"loss)":[113],"feature":[116,128],"learning":[117,169],"?centralized?":[120],"global":[121],"pooling.":[122],"Secondly,":[123],"weakly":[125,167],"supervised":[126,168],"attractive":[127],"extraction":[129],"proposed,":[131],"segments":[133],"contours":[135,141],"top-down":[137],"saliency.":[138],"Consequently,":[139],"integrated":[143],"into":[144],"response":[147],"map":[148],"extract":[151],"?within?":[153],"target":[155],"object.":[156],"Interestingly,":[157],"have":[159],"discovered":[160],"combination":[163],"of":[164],"CRL":[165],"can":[170],"reinforce":[171],"each":[172],"other.":[173],"We":[174,188],"evaluate":[175],"performance":[177],"ofthe":[178],"proposed":[179],"on":[181,207],"widely-used":[182],"benchmarks":[183],"including":[184],"CUB200-2011":[185],"CARS196.":[187],"havereported":[189],"significant":[190],"gains":[191],"over":[192,198],"schemes,":[195],"e.g.,":[196],"5.4%":[197],"SCDA":[199],"[Wei":[200],"et":[201],"al.,":[202],"2017]on":[203],"CARS196,":[204],"3.7%":[206],"CUB200-2011.":[208]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":6}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}