{"id":"https://openalex.org/W2981820283","doi":"https://doi.org/10.1145/3343031.3350962","title":"Visual Relation Detection with Multi-Level Attention","display_name":"Visual Relation Detection with Multi-Level Attention","publication_year":2019,"publication_date":"2019-10-15","ids":{"openalex":"https://openalex.org/W2981820283","doi":"https://doi.org/10.1145/3343031.3350962","mag":"2981820283"},"language":"en","primary_location":{"id":"doi:10.1145/3343031.3350962","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3343031.3350962","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th 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/A5017047744","display_name":"Sipeng Zheng","orcid":"https://orcid.org/0000-0001-5331-6314"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sipeng Zheng","raw_affiliation_strings":["Renmin University of China, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101776086","display_name":"Shizhe Chen","orcid":"https://orcid.org/0000-0002-7313-9703"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shizhe Chen","raw_affiliation_strings":["Renmin University of China, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009985839","display_name":"Qin Jin","orcid":"https://orcid.org/0000-0001-6486-6020"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qin Jin","raw_affiliation_strings":["Renmin University of China, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I78988378"],"apc_list":null,"apc_paid":null,"fwci":0.8235,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.81926563,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"121","last_page":"129"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","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/T11714","display_name":"Multimodal Machine Learning Applications","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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9994999766349792,"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":0.9991000294685364,"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":0.7493133544921875},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6923471093177795},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.6858921051025391},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5357298851013184},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.5275423526763916},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.49383479356765747},{"id":"https://openalex.org/keywords/sensory-cue","display_name":"Sensory cue","score":0.4674912989139557},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.45238661766052246},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4452819526195526},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.44077977538108826},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.43756648898124695},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.42032700777053833},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4076893925666809},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3972499668598175},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17142027616500854},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.11975648999214172}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7493133544921875},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6923471093177795},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.6858921051025391},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5357298851013184},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.5275423526763916},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.49383479356765747},{"id":"https://openalex.org/C111370547","wikidata":"https://www.wikidata.org/wiki/Q7451120","display_name":"Sensory cue","level":2,"score":0.4674912989139557},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.45238661766052246},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4452819526195526},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.44077977538108826},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.43756648898124695},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.42032700777053833},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4076893925666809},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3972499668598175},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17142027616500854},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.11975648999214172},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3343031.3350962","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3343031.3350962","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th 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":34,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W1584193343","https://openalex.org/W1586939924","https://openalex.org/W1892016050","https://openalex.org/W1905882502","https://openalex.org/W1933349210","https://openalex.org/W1969616664","https://openalex.org/W2028277005","https://openalex.org/W2049705550","https://openalex.org/W2081613070","https://openalex.org/W2102605133","https://openalex.org/W2114106396","https://openalex.org/W2127795553","https://openalex.org/W2153579005","https://openalex.org/W2277195237","https://openalex.org/W2479423890","https://openalex.org/W2579549467","https://openalex.org/W2591644541","https://openalex.org/W2605736949","https://openalex.org/W2607855566","https://openalex.org/W2613718673","https://openalex.org/W2625297138","https://openalex.org/W2752782242","https://openalex.org/W2777602943","https://openalex.org/W2807977755","https://openalex.org/W2883170015","https://openalex.org/W2883697687","https://openalex.org/W2962737704","https://openalex.org/W2963037989","https://openalex.org/W2963097937","https://openalex.org/W2963351448","https://openalex.org/W2963536419","https://openalex.org/W2963980128","https://openalex.org/W2964118342"],"related_works":["https://openalex.org/W2180954594","https://openalex.org/W2052835778","https://openalex.org/W2049003611","https://openalex.org/W2127804977","https://openalex.org/W2108418243","https://openalex.org/W164103134","https://openalex.org/W2787352659","https://openalex.org/W1970611213","https://openalex.org/W2916925572","https://openalex.org/W2093698361"],"abstract_inverted_index":{"Visual":[0,163],"relations,":[1],"which":[2,37,84,125,172,190],"describe":[3],"various":[4],"types":[5],"of":[6,22,48,82,90,168,200],"interactions":[7],"between":[8,93],"two":[9,94,154],"objects":[10,30],"in":[11,64],"the":[12,23,29,67,79,91,97,166,175,186,197],"image,":[13],"can":[14,31],"provide":[15],"critical":[16],"information":[17],"for":[18,59,109,195],"comprehensive":[19],"semantic":[20,44],"understanding":[21],"image.":[24],"Multiple":[25],"cues":[26,54,140],"related":[27],"to":[28,33,51],"contribute":[32],"visual":[34,60,75,120,157,201],"relation":[35,61,121,158,202],"detection,":[36],"mainly":[38],"include":[39],"appearances,":[40],"spacial":[41],"locations":[42],"and":[43,55,96,136,162],"meanings.":[45],"It":[46],"is":[47,70,191],"great":[49],"importance":[50,143],"represent":[52],"different":[53,98,107,110,139,142],"combine":[56,138],"them":[57],"effectively":[58],"detection.":[62],"However,":[63],"previous":[65,176],"works,":[66],"appearance":[68,128,133],"representation":[69,76,129],"simply":[71],"realized":[72],"by":[73],"global":[74],"based":[77],"on":[78,153],"bounding":[80],"boxes":[81],"objects,":[83,95],"may":[85],"not":[86],"capture":[87],"salient":[88,127],"regions":[89],"interaction":[92],"cue":[99],"representations":[100],"are":[101],"equally":[102],"concatenated":[103],"without":[104],"considering":[105],"their":[106],"contributions":[108],"relations.":[111],"In":[112],"this":[113],"work,":[114],"we":[115],"propose":[116],"a":[117,131,146],"multi-level":[118],"attention":[119,134,148],"detection":[122,159,203],"model":[123,171,180],"(MLA-VRD),":[124],"generates":[126],"via":[130,145],"multi-stage":[132],"strategy":[135],"adaptively":[137],"with":[141],"weighting":[144],"multi-cue":[147],"strategy.":[149],"Extensive":[150],"experiment":[151],"results":[152],"widely":[155],"used":[156],"datasets,":[160],"VRD":[161],"Genome,":[164],"demonstrate":[165],"effectiveness":[167],"our":[169],"proposed":[170,179],"significantly":[173],"outperforms":[174],"state-of-the-arts.":[177],"Our":[178],"also":[181],"achieves":[182],"superior":[183],"performance":[184],"under":[185],"zero-shot":[187],"learning":[188],"condition,":[189],"an":[192],"important":[193],"ordeal":[194],"testing":[196],"generalization":[198],"ability":[199],"models.":[204]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}