{"id":"https://openalex.org/W3093319304","doi":"https://doi.org/10.1145/3394171.3413889","title":"ShapeCaptioner: Generative Caption Network for 3D Shapes by Learning a Mapping from Parts Detected in Multiple Views to Sentences","display_name":"ShapeCaptioner: Generative Caption Network for 3D Shapes by Learning a Mapping from Parts Detected in Multiple Views to Sentences","publication_year":2020,"publication_date":"2020-10-12","ids":{"openalex":"https://openalex.org/W3093319304","doi":"https://doi.org/10.1145/3394171.3413889","mag":"3093319304"},"language":"en","primary_location":{"id":"doi:10.1145/3394171.3413889","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3413889","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":"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/A5068597652","display_name":"Zhizhong Han","orcid":"https://orcid.org/0000-0001-9540-9973"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhizhong Han","raw_affiliation_strings":["Tsinghua University & University of Maryland, College Park, MD, USA"],"affiliations":[{"raw_affiliation_string":"Tsinghua University & University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100408391","display_name":"Chao Chen","orcid":"https://orcid.org/0000-0003-1065-211X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Chen","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101691399","display_name":"Yu-Shen Liu","orcid":"https://orcid.org/0000-0001-7305-1915"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu-Shen Liu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014079156","display_name":"Matthias Zwicker","orcid":"https://orcid.org/0000-0001-8630-5515"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthias Zwicker","raw_affiliation_strings":["University of Maryland, College Park, MD, USA"],"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5068597652"],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":2.5402,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.9137763,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1018","last_page":"1027"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9988999962806702,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9988999962806702,"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":0.9987000226974487,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/closed-captioning","display_name":"Closed captioning","score":0.9005907773971558},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7964332103729248},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6394168138504028},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5953055620193481},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5829624533653259},{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.5815932154655457},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5115633606910706},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.45799216628074646},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3694987893104553},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2183036506175995}],"concepts":[{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.9005907773971558},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7964332103729248},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6394168138504028},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5953055620193481},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5829624533653259},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.5815932154655457},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5115633606910706},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.45799216628074646},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3694987893104553},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2183036506175995},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C27206212","wikidata":"https://www.wikidata.org/wiki/Q34178","display_name":"Theology","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3394171.3413889","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3413889","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":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.75}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1895577753","https://openalex.org/W1905882502","https://openalex.org/W1956340063","https://openalex.org/W2133459682","https://openalex.org/W2139501017","https://openalex.org/W2461132349","https://openalex.org/W2481240925","https://openalex.org/W2517836489","https://openalex.org/W2565662353","https://openalex.org/W2608153915","https://openalex.org/W2615230425","https://openalex.org/W2737072614","https://openalex.org/W2780605533","https://openalex.org/W2793251487","https://openalex.org/W2796996119","https://openalex.org/W2921891839","https://openalex.org/W2938455051","https://openalex.org/W2945774199","https://openalex.org/W2962968665","https://openalex.org/W2963026686","https://openalex.org/W2963048248","https://openalex.org/W2963121255","https://openalex.org/W2963123724","https://openalex.org/W2963270032","https://openalex.org/W2963926543","https://openalex.org/W2964018924","https://openalex.org/W2964078384","https://openalex.org/W2964199361","https://openalex.org/W2965157662","https://openalex.org/W2965615303","https://openalex.org/W2995027244","https://openalex.org/W2997460259","https://openalex.org/W3009750677","https://openalex.org/W3011514659","https://openalex.org/W3034493208","https://openalex.org/W3034964128","https://openalex.org/W3035378760","https://openalex.org/W3092946149"],"related_works":["https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W4395044357","https://openalex.org/W4287117424","https://openalex.org/W4387506531","https://openalex.org/W2087346071","https://openalex.org/W2967848559","https://openalex.org/W4299831724"],"abstract_inverted_index":{"3D":[0,8,25,57,81,94,118,140,151],"shape":[1,9,58,82,141,152],"captioning":[2,59,153],"is":[3],"a":[4,30,51,117,123],"challenging":[5],"application":[6],"in":[7,36,64,70,77,104],"understanding.":[10],"Captions":[11],"from":[12,60,80,93],"recent":[13],"multi-view":[14],"based":[15],"methods":[16],"reveal":[17],"that":[18,136],"they":[19],"cannot":[20],"capture":[21],"part-level":[22,34],"characteristics":[23,147],"of":[24,32,74],"shapes.":[26],"This":[27],"leads":[28],"to":[29,41,55,88,96,115,125,128,148],"lack":[31],"detailed":[33,145],"description":[35],"captions,":[37],"which":[38],"human":[39],"tend":[40],"focus":[42],"on.":[43],"To":[44],"resolve":[45],"this":[46,86],"issue,":[47],"we":[48],"propose":[49],"ShapeCaptioner,":[50],"generative":[52],"caption":[53],"network,":[54],"perform":[56],"semantic":[61],"parts":[62,102],"detected":[63,103],"multiple":[65,78,105],"views.":[66],"Our":[67,132],"novelty":[68],"lies":[69],"learning":[71,90],"the":[72,91,101,130],"knowledge":[73,87],"part":[75,111,146],"detection":[76],"views":[79,107],"segmentations":[83],"and":[84,120],"transferring":[85],"facilitate":[89,149],"mapping":[92],"shapes":[95],"sentences.":[97],"Specifically,":[98],"ShapeCaptioner":[99,137],"aggregates":[100],"colored":[106],"using":[108],"our":[109],"novel":[110],"class":[112],"specific":[113],"aggregation":[114],"represent":[116],"shape,":[119],"then,":[121],"employs":[122],"sequence":[124,126],"model":[127],"generate":[129],"caption.":[131],"outperforming":[133],"results":[134],"show":[135],"can":[138],"learn":[139],"features":[142],"with":[143],"more":[144],"better":[150],"than":[154],"previous":[155],"work.":[156]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}