{"id":"https://openalex.org/W4411949793","doi":"https://doi.org/10.1109/iwcmc65282.2025.11059515","title":"An Efficient Hand Grasping Method Based on CVAE for Target Pose Estimation","display_name":"An Efficient Hand Grasping Method Based on CVAE for Target Pose Estimation","publication_year":2025,"publication_date":"2025-05-12","ids":{"openalex":"https://openalex.org/W4411949793","doi":"https://doi.org/10.1109/iwcmc65282.2025.11059515"},"language":"en","primary_location":{"id":"doi:10.1109/iwcmc65282.2025.11059515","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwcmc65282.2025.11059515","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Wireless Communications and Mobile Computing (IWCMC)","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/A5009468566","display_name":"Peijie Xu","orcid":"https://orcid.org/0000-0002-9050-6405"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pengpeng Xu","raw_affiliation_strings":["Research Institute of UBTech Robotics,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Institute of UBTech Robotics,Shenzhen,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102771665","display_name":"Dan Xia","orcid":"https://orcid.org/0000-0003-3522-7072"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dan Xia","raw_affiliation_strings":["Hohai University,Changzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hohai University,Changzhou,China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069618265","display_name":"Huaxi Zhang","orcid":"https://orcid.org/0000-0002-5914-8048"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huaxi Zhang","raw_affiliation_strings":["Research Institute of UBTech Robotics,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Institute of UBTech Robotics,Shenzhen,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019925709","display_name":"Wenlong Qin","orcid":"https://orcid.org/0000-0003-1905-5629"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wenlong Qin","raw_affiliation_strings":["Research Institute of UBTech Robotics,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Institute of UBTech Robotics,Shenzhen,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040709029","display_name":"Jianxin Pang","orcid":"https://orcid.org/0000-0002-3985-5802"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jianxin Pang","raw_affiliation_strings":["Research Institute of UBTech Robotics,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Institute of UBTech Robotics,Shenzhen,China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085029208","display_name":"Jun Cheng","orcid":"https://orcid.org/0000-0002-3483-747X"},"institutions":[{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Cheng","raw_affiliation_strings":["Shenzhen Institute of Advanced Technology,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Institute of Advanced Technology,Shenzhen,China","institution_ids":["https://openalex.org/I4210145761"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2546,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.77623015,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"299","last_page":"304"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9696999788284302,"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/T13382","display_name":"Robotics and Automated Systems","score":0.9664999842643738,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/computer-science","display_name":"Computer science","score":0.6942591667175293},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6727460622787476},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.5657055377960205},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5485962629318237},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.41795432567596436},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40340322256088257},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3211123049259186},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10483768582344055}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6942591667175293},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6727460622787476},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.5657055377960205},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5485962629318237},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41795432567596436},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40340322256088257},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3211123049259186},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10483768582344055},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iwcmc65282.2025.11059515","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwcmc65282.2025.11059515","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Wireless Communications and Mobile Computing (IWCMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1968976745","https://openalex.org/W2036637075","https://openalex.org/W2050449584","https://openalex.org/W2073668682","https://openalex.org/W2123079020","https://openalex.org/W2140586277","https://openalex.org/W2432137114","https://openalex.org/W2600030077","https://openalex.org/W2603737562","https://openalex.org/W2734472784","https://openalex.org/W2765811365","https://openalex.org/W2768611535","https://openalex.org/W2805556115","https://openalex.org/W2911020481","https://openalex.org/W2948571212","https://openalex.org/W2980216391","https://openalex.org/W3091619233","https://openalex.org/W3092037789","https://openalex.org/W3108441306","https://openalex.org/W3129140312","https://openalex.org/W3167551107","https://openalex.org/W3194622054","https://openalex.org/W3207888596","https://openalex.org/W4205295909","https://openalex.org/W4253948311","https://openalex.org/W4319301012","https://openalex.org/W4360897867","https://openalex.org/W4380450805","https://openalex.org/W4386071465","https://openalex.org/W4391793579","https://openalex.org/W4402475277"],"related_works":["https://openalex.org/W2123263858","https://openalex.org/W3127959533","https://openalex.org/W4387967917","https://openalex.org/W4387968151","https://openalex.org/W4386925306","https://openalex.org/W3132124459","https://openalex.org/W2946083937","https://openalex.org/W2736638679","https://openalex.org/W4313046826","https://openalex.org/W1968716783"],"abstract_inverted_index":{"With":[0],"the":[1,71,87],"advancement":[2],"of":[3],"humanoid":[4],"robot":[5],"industrialization,":[6],"dexterous":[7,28,48],"grasping":[8,97],"has":[9],"become":[10],"a":[11,41,51],"critical":[12],"research":[13],"area.":[14],"Traditional":[15],"two-finger":[16],"grippers,":[17],"while":[18],"effective":[19],"for":[20,33,46],"regular":[21],"geometries,":[22],"struggle":[23],"with":[24,73],"complex":[25],"shapes.":[26],"Multi-finger":[27],"hands":[29,49],"offer":[30],"significant":[31],"advantages":[32],"adapting":[34],"to":[35,70,78],"diverse":[36],"objects.":[37],"This":[38],"study":[39],"proposes":[40],"grasp":[42,61],"pose":[43],"estimation":[44],"method":[45,89],"multi-finger":[47],"utilizing":[50],"Conditional":[52],"Variational":[53],"Autoencoder":[54],"(CVAE)":[55],"framework.":[56],"Point":[57],"cloud":[58],"data":[59],"and":[60,93],"poses":[62],"from":[63],"industrial":[64],"components":[65],"are":[66],"used":[67],"as":[68],"inputs":[69],"CVAE,":[72],"K-Nearest":[74],"Neighbors":[75],"(KNN)":[76],"employed":[77],"enhance":[79],"local":[80],"feature":[81],"extraction.":[82],"Experimental":[83],"results":[84],"show":[85],"that":[86],"proposed":[88],"achieves":[90],"robust":[91],"generalization":[92],"stability":[94],"across":[95],"various":[96],"scenarios.":[98]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
