{"id":"https://openalex.org/W2012718063","doi":"https://doi.org/10.1145/2502081.2502159","title":"Weakly-supervised multi-class object detection using multi-type 3D features","display_name":"Weakly-supervised multi-class object detection using multi-type 3D features","publication_year":2013,"publication_date":"2013-10-21","ids":{"openalex":"https://openalex.org/W2012718063","doi":"https://doi.org/10.1145/2502081.2502159","mag":"2012718063"},"language":"en","primary_location":{"id":"doi:10.1145/2502081.2502159","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2502081.2502159","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21st ACM international conference on Multimedia","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/A5045505869","display_name":"Asako Kanezaki","orcid":"https://orcid.org/0000-0003-3217-1405"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Asako Kanezaki","raw_affiliation_strings":["The University of Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010543059","display_name":"Yasuo Kuniyoshi","orcid":"https://orcid.org/0000-0001-8443-4161"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yasuo Kuniyoshi","raw_affiliation_strings":["The University of Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042711470","display_name":"Tatsuya Harada","orcid":"https://orcid.org/0000-0002-3712-3691"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tatsuya Harada","raw_affiliation_strings":["The University of Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5045505869"],"corresponding_institution_ids":["https://openalex.org/I74801974"],"apc_list":null,"apc_paid":null,"fwci":0.5443,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.69238224,"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":"605","last_page":"608"},"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":0.9998000264167786,"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":0.9998000264167786,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9980000257492065,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9948999881744385,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8487720489501953},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7428588271141052},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6765414476394653},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6554316282272339},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5963860750198364},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.538349986076355},{"id":"https://openalex.org/keywords/texture","display_name":"Texture (cosmology)","score":0.5303977727890015},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.518293559551239},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4409412741661072},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.42049896717071533},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.4155169129371643},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.35376691818237305}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8487720489501953},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7428588271141052},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6765414476394653},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6554316282272339},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5963860750198364},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.538349986076355},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.5303977727890015},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.518293559551239},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4409412741661072},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.42049896717071533},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.4155169129371643},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.35376691818237305},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2502081.2502159","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2502081.2502159","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21st ACM international conference on Multimedia","raw_type":"proceedings-article"},{"id":"pmh:oai:t2r2.star.titech.ac.jp:50527748","is_oa":false,"landing_page_url":"http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100823763","pdf_url":null,"source":{"id":"https://openalex.org/S4377196385","display_name":"Tokyo Tech Research Repository (Tokyo Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114531698","host_organization_name":"Tokyo Institute of Technology","host_organization_lineage":["https://openalex.org/I114531698"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2020477327","https://openalex.org/W2099528205","https://openalex.org/W2099606917","https://openalex.org/W2109450590","https://openalex.org/W2110119381","https://openalex.org/W2124154128","https://openalex.org/W2126006675","https://openalex.org/W2126833203","https://openalex.org/W2160218441","https://openalex.org/W2163474322","https://openalex.org/W2168356304","https://openalex.org/W3009009611"],"related_works":["https://openalex.org/W115686965","https://openalex.org/W2114275278","https://openalex.org/W4292830139","https://openalex.org/W4319309705","https://openalex.org/W1489511283","https://openalex.org/W4387272257","https://openalex.org/W2974914859","https://openalex.org/W2026565050","https://openalex.org/W2110244802","https://openalex.org/W949345935"],"abstract_inverted_index":{"We":[0,88],"propose":[1],"a":[2,15,53,94],"weakly-supervised":[3],"learning":[4],"method":[5,24,40,92,96],"for":[6],"object":[7,20,65],"detection":[8],"using":[9,97],"color":[10,77,98,113],"and":[11,81,99,114,123],"depth":[12,100,115],"images":[13,116],"of":[14,33,59,112,120],"real":[16],"environment":[17],"attached":[18],"with":[19,107,117],"labels.":[21],"The":[22],"proposed":[23],"applies":[25],"Multiple":[26],"Instance":[27],"Learning":[28],"to":[29,55,84],"find":[30],"proper":[31],"instances":[32],"the":[34,44,57,86],"objects":[35,50,122],"in":[36,43,52],"training":[37,61],"images.":[38,101],"This":[39],"is":[41],"novel":[42],"sense":[45],"that":[46,75,90],"it":[47],"learns":[48],"multiple":[49],"simultaneously":[51],"way":[54],"balance":[56],"scores":[58],"each":[60],"sample":[62],"across":[63],"all":[64],"classes.":[66],"Moreover,":[67],"we":[68,103],"combine":[69],"3D":[70],"features":[71],"considering":[72],"different":[73],"properties,":[74],"is,":[76],"texture,":[78,80],"grayscale":[79],"surface":[82],"curvature,":[83],"improve":[85],"performance.":[87],"show":[89],"our":[91,108],"surpasses":[93],"conventional":[95],"Furthermore,":[102],"evaluate":[104],"its":[105],"performance":[106],"new":[109],"dataset":[110],"consisting":[111],"weak":[118],"labels":[119],"100":[121],"various":[124],"backgrounds.":[125]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}