{"id":"https://openalex.org/W2902429567","doi":"https://doi.org/10.1109/icpr.2018.8545540","title":"Discriminate Cross-modal Quantization for Efficient Retrieval","display_name":"Discriminate Cross-modal Quantization for Efficient Retrieval","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2902429567","doi":"https://doi.org/10.1109/icpr.2018.8545540","mag":"2902429567"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2018.8545540","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545540","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th 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/A5100614090","display_name":"Peng Sun","orcid":"https://orcid.org/0000-0002-1227-5533"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Peng Sun","raw_affiliation_strings":["School of Computer Science and Engineering and Beijing Advanced Innovation, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering and Beijing Advanced Innovation, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100613014","display_name":"Cheng Yan","orcid":"https://orcid.org/0000-0002-5021-6841"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Yan","raw_affiliation_strings":["School of Computer Science and Engineering and Beijing Advanced Innovation, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering and Beijing Advanced Innovation, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100328271","display_name":"Shuai Wang","orcid":"https://orcid.org/0000-0002-1570-6570"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Wang","raw_affiliation_strings":["School of Computer Science and Engineering and Beijing Advanced Innovation, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering and Beijing Advanced Innovation, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101790836","display_name":"Xiao Bai","orcid":"https://orcid.org/0000-0001-8561-9299"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Bai","raw_affiliation_strings":["School of Computer Science and Engineering and Beijing Advanced Innovation, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering and Beijing Advanced Innovation, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100614090"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14082989,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3328","last_page":"3334"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":1.0,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":1.0,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.993399977684021,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9858999848365784,"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/computer-science","display_name":"Computer science","score":0.6585580110549927},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6122159361839294},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.5926640629768372},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.5848770141601562},{"id":"https://openalex.org/keywords/binary-code","display_name":"Binary code","score":0.5803980231285095},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.5442259311676025},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.5336651802062988},{"id":"https://openalex.org/keywords/hamming-space","display_name":"Hamming space","score":0.5207788348197937},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.506271481513977},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.4720022678375244},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4464419186115265},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.44549819827079773},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4438047409057617},{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.43867552280426025},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3555179238319397},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21529966592788696},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.17775261402130127},{"id":"https://openalex.org/keywords/hamming-code","display_name":"Hamming code","score":0.10522729158401489},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.10520920157432556}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6585580110549927},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6122159361839294},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.5926640629768372},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.5848770141601562},{"id":"https://openalex.org/C63435697","wikidata":"https://www.wikidata.org/wiki/Q864135","display_name":"Binary code","level":3,"score":0.5803980231285095},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.5442259311676025},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5336651802062988},{"id":"https://openalex.org/C2779494224","wikidata":"https://www.wikidata.org/wiki/Q5645799","display_name":"Hamming space","level":5,"score":0.5207788348197937},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.506271481513977},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.4720022678375244},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4464419186115265},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.44549819827079773},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4438047409057617},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.43867552280426025},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3555179238319397},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21529966592788696},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.17775261402130127},{"id":"https://openalex.org/C73150493","wikidata":"https://www.wikidata.org/wiki/Q853922","display_name":"Hamming code","level":4,"score":0.10522729158401489},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.10520920157432556},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C157125643","wikidata":"https://www.wikidata.org/wiki/Q884707","display_name":"Block code","level":3,"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/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2018.8545540","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545540","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6800000071525574}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W138284169","https://openalex.org/W199018803","https://openalex.org/W1910300841","https://openalex.org/W1922199343","https://openalex.org/W1970055505","https://openalex.org/W1976258951","https://openalex.org/W1977182282","https://openalex.org/W1996219872","https://openalex.org/W2007972815","https://openalex.org/W2038436420","https://openalex.org/W2086958058","https://openalex.org/W2087193308","https://openalex.org/W2113606819","https://openalex.org/W2124509324","https://openalex.org/W2138118304","https://openalex.org/W2143321506","https://openalex.org/W2155803963","https://openalex.org/W2267050401","https://openalex.org/W2337086876","https://openalex.org/W2461972671","https://openalex.org/W2951581059","https://openalex.org/W3098232083","https://openalex.org/W6605707561","https://openalex.org/W6608183366","https://openalex.org/W6676903177","https://openalex.org/W6681232786","https://openalex.org/W6693399182"],"related_works":["https://openalex.org/W2981938443","https://openalex.org/W2578909082","https://openalex.org/W2760998155","https://openalex.org/W4288718166","https://openalex.org/W2748725735","https://openalex.org/W2036753599","https://openalex.org/W2949049896","https://openalex.org/W2963839334","https://openalex.org/W2797819729","https://openalex.org/W4297909034"],"abstract_inverted_index":{"Efficient":[0],"cross-modal":[1,21,79],"retrieval":[2,40],"involves":[3],"searching":[4],"similar":[5],"items":[6],"across":[7],"different":[8,84],"modalities,":[9],"e.g.,":[10],"using":[11],"an":[12],"image(text)":[13],"to":[14,50,100,115,128],"search":[15,162],"for":[16,72,124],"texts(images).":[17],"To":[18,37,66],"speed":[19],"up":[20],"retrieval,":[22],"hashing-based":[23],"methods":[24,44],"threshold":[25],"continuous":[26],"embeddings":[27,46],"into":[28,47,86],"binary":[29,140],"codes,":[30],"inducing":[31],"substantial":[32],"loss":[33],"of":[34],"accuracy":[35],"retrieval.":[36],"further":[38],"improve":[39],"performance,":[41],"several":[42],"quantization-based":[43],"quantize":[45],"real-valued":[48],"codewords":[49],"maximumlly":[51],"preserve":[52],"inter-modal":[53],"and":[54,142],"intra-modal":[55],"similarity":[56],"relation,":[57],"while":[58],"the":[59,73,97,125,131,135,138],"discrimination":[60],"between":[61],"dissimilar":[62],"data":[63,92],"is":[64,108,122],"ignored.":[65],"address":[67],"these":[68],"challenges,":[69],"we":[70],"propose,":[71],"first":[74],"time,":[75],"a":[76,87,101,105,143],"novel":[77],"discriminate":[78],"quantization(DCMQ)":[80],"which":[81],"nonlinearly":[82],"maps":[83],"modalities":[85],"common":[88],"space":[89],"where":[90],"ir-relevant":[91],"points":[93,98],"are":[94],"semantically":[95],"separable:":[96],"belonging":[99],"class":[102],"lie":[103],"in":[104,161],"cluster":[106],"that":[107,156],"not":[109],"overlapped":[110],"with":[111,148],"other":[112,116],"clusters":[113],"corresponding":[114],"classes.":[117],"An":[118],"effective":[119],"optimization":[120],"algorithm":[121],"developed":[123],"proposed":[126],"method":[127],"jointly":[129],"learn":[130],"modality-specific":[132],"mapping":[133],"functions,":[134],"sharing":[136],"codebooks,":[137],"unified":[139],"codes":[141],"linear":[144],"classifier.":[145],"Experimental":[146],"comparison":[147],"state-of-the-art":[149],"algorithms":[150],"over":[151],"three":[152],"benchmark":[153],"datasets":[154],"demonstrates":[155],"DCMQ":[157],"achieves":[158],"significant":[159],"improvement":[160],"accuracy.":[163]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}