{"id":"https://openalex.org/W3093028144","doi":"https://doi.org/10.1145/3394171.3413555","title":"MM-Hand","display_name":"MM-Hand","publication_year":2020,"publication_date":"2020-10-12","ids":{"openalex":"https://openalex.org/W3093028144","doi":"https://doi.org/10.1145/3394171.3413555","mag":"3093028144"},"language":"en","primary_location":{"id":"doi:10.1145/3394171.3413555","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3413555","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/A5064729482","display_name":"Zhenyu Wu","orcid":"https://orcid.org/0000-0002-7183-6943"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhenyu Wu","raw_affiliation_strings":["Texas A&M University, College Station, TX, USA"],"affiliations":[{"raw_affiliation_string":"Texas A&M University, College Station, TX, USA","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114910210","display_name":"Duc Hoang","orcid":"https://orcid.org/0000-0003-4512-8465"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Duc Hoang","raw_affiliation_strings":["Texas A&M University, College Station, TX, USA"],"affiliations":[{"raw_affiliation_string":"Texas A&M University, College Station, TX, USA","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059470173","display_name":"Shih-Yao Lin","orcid":"https://orcid.org/0000-0003-3160-669X"},"institutions":[{"id":"https://openalex.org/I70745867","display_name":"KLA (United States)","ror":"https://ror.org/02rqhpa98","country_code":"US","type":"company","lineage":["https://openalex.org/I70745867"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shih-Yao Lin","raw_affiliation_strings":["Tencent America, Palo Alto, CA, USA"],"affiliations":[{"raw_affiliation_string":"Tencent America, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I70745867"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058457237","display_name":"Yusheng Xie","orcid":"https://orcid.org/0000-0002-8581-4614"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yusheng Xie","raw_affiliation_strings":["Amazon Web Services, Palo Alto, CA, USA"],"affiliations":[{"raw_affiliation_string":"Amazon Web Services, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049251280","display_name":"Liangjian Chen","orcid":"https://orcid.org/0000-0001-7038-9144"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liangjian Chen","raw_affiliation_strings":["University of California, Irvine, Irvine, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of California, Irvine, Irvine, CA, USA","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002217153","display_name":"Yen\u2010Yu Lin","orcid":"https://orcid.org/0000-0002-7183-6070"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yen-Yu Lin","raw_affiliation_strings":["National Chiao Tung University, Hsinchu City, Taiwan Roc"],"affiliations":[{"raw_affiliation_string":"National Chiao Tung University, Hsinchu City, Taiwan Roc","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048522863","display_name":"Zhangyang Wang","orcid":"https://orcid.org/0000-0002-2050-5693"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhangyang Wang","raw_affiliation_strings":["University of Texas at Austin, Austin, TX, USA"],"affiliations":[{"raw_affiliation_string":"University of Texas at Austin, Austin, TX, USA","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066173871","display_name":"Wei Fan","orcid":"https://orcid.org/0000-0002-5980-4527"},"institutions":[{"id":"https://openalex.org/I70745867","display_name":"KLA (United States)","ror":"https://ror.org/02rqhpa98","country_code":"US","type":"company","lineage":["https://openalex.org/I70745867"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Fan","raw_affiliation_strings":["Tencent America, Palo Alto, CA, USA"],"affiliations":[{"raw_affiliation_string":"Tencent America, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I70745867"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5064729482"],"corresponding_institution_ids":["https://openalex.org/I91045830"],"apc_list":null,"apc_paid":null,"fwci":1.1724,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.81452914,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2508","last_page":"2516"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998000264167786,"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/T10812","display_name":"Human Pose and Action Recognition","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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9962999820709229,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9918000102043152,"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":0.8182957768440247},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7126758098602295},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6966810822486877},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5432158708572388},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5422353148460388},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.5306761860847473},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5051432251930237},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.48369795083999634},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41103699803352356},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4103175699710846},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32760506868362427}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8182957768440247},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7126758098602295},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6966810822486877},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5432158708572388},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5422353148460388},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.5306761860847473},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5051432251930237},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.48369795083999634},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41103699803352356},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4103175699710846},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32760506868362427},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3394171.3413555","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3413555","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":[{"score":0.699999988079071,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1928739709","https://openalex.org/W2017817327","https://openalex.org/W2021160936","https://openalex.org/W2075156252","https://openalex.org/W2075598738","https://openalex.org/W2093414253","https://openalex.org/W2292335906","https://openalex.org/W2331128040","https://openalex.org/W2546353648","https://openalex.org/W2606627193","https://openalex.org/W2613806194","https://openalex.org/W2617297150","https://openalex.org/W2633413857","https://openalex.org/W2797046819","https://openalex.org/W2798478762","https://openalex.org/W2798714868","https://openalex.org/W2884985453","https://openalex.org/W2890816492","https://openalex.org/W2892644985","https://openalex.org/W2897765997","https://openalex.org/W2924910074","https://openalex.org/W2928699722","https://openalex.org/W2941359057","https://openalex.org/W2947815032","https://openalex.org/W2962793481","https://openalex.org/W2962808524","https://openalex.org/W2962811204","https://openalex.org/W2962963674","https://openalex.org/W2963073614","https://openalex.org/W2963266880","https://openalex.org/W2963403405","https://openalex.org/W2963709863","https://openalex.org/W2964002510","https://openalex.org/W2964093990","https://openalex.org/W2964097473","https://openalex.org/W2964304707","https://openalex.org/W2973857456","https://openalex.org/W2979577579","https://openalex.org/W2982164728","https://openalex.org/W2982601397","https://openalex.org/W2982795046","https://openalex.org/W2983541695","https://openalex.org/W2984529706","https://openalex.org/W2984624776","https://openalex.org/W2991530302","https://openalex.org/W2995893150","https://openalex.org/W2999225873","https://openalex.org/W3004835408","https://openalex.org/W3042868321","https://openalex.org/W3090855069"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W4246352526","https://openalex.org/W2964084369","https://openalex.org/W4307623796","https://openalex.org/W4394784820"],"abstract_inverted_index":{"Estimating":[0],"the":[1,52,82,95,101,105],"3D":[2,25,47,55,107],"hand":[3,21,26,49,64,108],"pose":[4,56,109],"from":[5],"a":[6,39,60,70],"monocular":[7],"RGB":[8,20],"image":[9],"is":[10,16,31],"important":[11],"but":[12],"challenging.":[13],"A":[14],"solution":[15],"training":[17],"on":[18,111],"large-scale":[19],"images":[22,50,84],"with":[23,69],"accurate":[24],"keypoint":[27],"annotations.":[28],"However,":[29],"it":[30],"too":[32],"expensive":[33],"in":[34],"practice.":[35],"Instead,":[36],"we":[37],"develop":[38],"learning-based":[40],"approach":[41],"to":[42],"synthesize":[43],"realistic,":[44],"diverse,":[45],"and":[46,89],"pose-preserving":[48],"under":[51],"guidance":[53],"of":[54,104],"information.":[57],"We":[58],"propose":[59],"3D-aware":[61],"multi-modal":[62],"guided":[63],"generative":[65],"network":[66],"(MM-Hand),":[67],"together":[68],"novel":[71],"geometry-based":[72],"curriculum":[73],"learning":[74],"strategy.":[75],"Our":[76],"extensive":[77],"experimental":[78],"results":[79],"demonstrate":[80],"that":[81],"3D-annotated":[83],"generated":[85],"by":[86],"MM-Hand":[87],"qualitatively":[88],"quantitatively":[90],"outperform":[91],"existing":[92],"options.":[93],"Moreover,":[94],"augmented":[96],"data":[97],"can":[98],"consistently":[99],"improve":[100],"quantitative":[102],"performance":[103],"state-of-the-art":[106],"estimators":[110],"two":[112],"benchmark":[113],"datasets.":[114],"The":[115],"code":[116],"will":[117],"be":[118],"available":[119],"at":[120],"https://github.com/ScottHoang/mm-hand.":[121]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":7}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2020-10-22T00:00:00"}