{"id":"https://openalex.org/W3093116134","doi":"https://doi.org/10.1145/3394171.3414022","title":"Weakly-Supervised Image Hashing through Masked Visual-Semantic Graph-based Reasoning","display_name":"Weakly-Supervised Image Hashing through Masked Visual-Semantic Graph-based Reasoning","publication_year":2020,"publication_date":"2020-10-12","ids":{"openalex":"https://openalex.org/W3093116134","doi":"https://doi.org/10.1145/3394171.3414022","mag":"3093116134"},"language":"en","primary_location":{"id":"doi:10.1145/3394171.3414022","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3414022","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Multimedia","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/A5101923561","display_name":"Lu Jin","orcid":"https://orcid.org/0000-0002-2964-426X"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lu Jin","raw_affiliation_strings":["Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017096005","display_name":"Zechao Li","orcid":"https://orcid.org/0000-0002-5341-5985"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zechao Li","raw_affiliation_strings":["Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032751833","display_name":"Yonghua Pan","orcid":"https://orcid.org/0000-0002-9615-5757"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yonghua Pan","raw_affiliation_strings":["Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035112538","display_name":"Jinhui Tang","orcid":"https://orcid.org/0000-0001-9008-222X"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinhui Tang","raw_affiliation_strings":["Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":1.8795,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.90553417,"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":"916","last_page":"924"},"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":0.9983999729156494,"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":0.9952999949455261,"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":0.7795524597167969},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.7201609015464783},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5723204016685486},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5304923057556152},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.48798054456710815},{"id":"https://openalex.org/keywords/feature-hashing","display_name":"Feature hashing","score":0.4330676198005676},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.42902565002441406},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4285479784011841},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4132678508758545},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4129312038421631},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3635817766189575},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3392290472984314},{"id":"https://openalex.org/keywords/hash-table","display_name":"Hash table","score":0.2667210102081299},{"id":"https://openalex.org/keywords/double-hashing","display_name":"Double hashing","score":0.08222153782844543}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7795524597167969},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.7201609015464783},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5723204016685486},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5304923057556152},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.48798054456710815},{"id":"https://openalex.org/C133667856","wikidata":"https://www.wikidata.org/wiki/Q5439682","display_name":"Feature hashing","level":5,"score":0.4330676198005676},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.42902565002441406},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4285479784011841},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4132678508758545},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4129312038421631},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3635817766189575},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3392290472984314},{"id":"https://openalex.org/C67388219","wikidata":"https://www.wikidata.org/wiki/Q207440","display_name":"Hash table","level":3,"score":0.2667210102081299},{"id":"https://openalex.org/C138111711","wikidata":"https://www.wikidata.org/wiki/Q478351","display_name":"Double hashing","level":4,"score":0.08222153782844543},{"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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3394171.3414022","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3414022","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1502916507","https://openalex.org/W1956333070","https://openalex.org/W1971238646","https://openalex.org/W1973693867","https://openalex.org/W1974647172","https://openalex.org/W1997107867","https://openalex.org/W2007972815","https://openalex.org/W2066440363","https://openalex.org/W2076063813","https://openalex.org/W2082453965","https://openalex.org/W2130660124","https://openalex.org/W2147717514","https://openalex.org/W2155803963","https://openalex.org/W2163605009","https://openalex.org/W2402125293","https://openalex.org/W2461086877","https://openalex.org/W2509619282","https://openalex.org/W2519936666","https://openalex.org/W2568737927","https://openalex.org/W2604298190","https://openalex.org/W2622826443","https://openalex.org/W2624945720","https://openalex.org/W2626778328","https://openalex.org/W2627183927","https://openalex.org/W2745461083","https://openalex.org/W2781821509","https://openalex.org/W2801086478","https://openalex.org/W2801765193","https://openalex.org/W2808282156","https://openalex.org/W2808604000","https://openalex.org/W2832876791","https://openalex.org/W2894879246","https://openalex.org/W2904458925","https://openalex.org/W2949049896","https://openalex.org/W2950577311","https://openalex.org/W2962954773","https://openalex.org/W2963495494","https://openalex.org/W2963656855","https://openalex.org/W2963901583","https://openalex.org/W2964158883","https://openalex.org/W2966146145","https://openalex.org/W2981138049","https://openalex.org/W2982376094","https://openalex.org/W3104374384","https://openalex.org/W6629956336"],"related_works":["https://openalex.org/W4381744218","https://openalex.org/W2767764284","https://openalex.org/W2059244188","https://openalex.org/W4211126162","https://openalex.org/W2035647105","https://openalex.org/W3158263601","https://openalex.org/W3087964089","https://openalex.org/W3192025065","https://openalex.org/W2146691237","https://openalex.org/W2296561062"],"abstract_inverted_index":{"With":[0],"the":[1,13,69,100,105,108,118,140,151,155,159,181,184],"popularization":[2],"of":[3,120,154,183],"social":[4],"websites,":[5],"many":[6],"methods":[7],"have":[8],"been":[9],"proposed":[10,185],"to":[11,50,67,93,103,134,144],"explore":[12],"noisy":[14,31,121],"tags":[15,74,128],"for":[16,55,59,187],"weakly-supervised":[17],"image":[18,56,109,188],"hashing.The":[19],"main":[20],"challenge":[21],"lies":[22],"in":[23],"learning":[24],"appropriate":[25],"and":[26,75,89,110,129],"sufficient":[27],"information":[28],"from":[29,132,165],"those":[30,166],"tags.":[32,122],"To":[33],"address":[34,117],"this":[35,37,95],"issue,":[36],"work":[38],"proposes":[39],"a":[40,64,171],"novel":[41],"Masked":[42],"visual-semantic":[43,53,137,161],"Graph-based":[44],"Reasoning":[45],"Network,":[46],"termed":[47],"as":[48],"MGRN,":[49],"learn":[51,135,145],"joint":[52,156,160],"representations":[54,162],"hashing.":[57],"Specifically,":[58],"each":[60],"image,":[61],"MGRN":[62,83],"constructs":[63],"relation":[65],"graph":[66],"capture":[68,104,126],"interactions":[70],"among":[71],"its":[72,111],"associated":[73,112],"performs":[76],"reasoning":[77],"with":[78,191],"Graph":[79],"Attention":[80],"Networks":[81],"(GAT).":[82],"randomly":[84],"masks":[85],"out":[86],"one":[87],"tag":[88],"then":[90],"make":[91],"GAT":[92,101],"predict":[94],"masked":[96],"tag.":[97],"This":[98],"forces":[99],"model":[102],"dependence":[106],"between":[107],"tags,":[113],"which":[114],"can":[115,125,149],"well":[116],"problem":[119],"Thus":[123],"it":[124],"key":[127],"visual":[130],"structures":[131],"images":[133],"well-aligned":[136],"representations.":[138],"Finally,":[139],"auto-encoders":[141],"is":[142],"leveraged":[143],"hash":[146,167],"codes":[147,168],"that":[148],"preserve":[150],"local":[152],"structure":[153],"space.":[157],"Meanwhile,":[158],"are":[163],"reconstructed":[164],"by":[169],"using":[170],"decoder.":[172],"Experimental":[173],"results":[174],"on":[175],"two":[176],"widely-used":[177],"benchmark":[178],"datasets":[179],"demonstrate":[180],"superiority":[182],"method":[186],"retrieval":[189],"compared":[190],"several":[192],"state-of-the-art":[193],"methods.":[194]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":7}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
