{"id":"https://openalex.org/W2415243675","doi":"https://doi.org/10.1109/icra.2016.7487351","title":"Object discovery and grasp detection with a shared convolutional neural network","display_name":"Object discovery and grasp detection with a shared convolutional neural network","publication_year":2016,"publication_date":"2016-05-01","ids":{"openalex":"https://openalex.org/W2415243675","doi":"https://doi.org/10.1109/icra.2016.7487351","mag":"2415243675"},"language":"en","primary_location":{"id":"doi:10.1109/icra.2016.7487351","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2016.7487351","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Robotics and Automation (ICRA)","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/A5101833400","display_name":"Di Guo","orcid":"https://orcid.org/0000-0002-9816-0103"},"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":true,"raw_author_name":"Di Guo","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065667064","display_name":"Tao Kong","orcid":"https://orcid.org/0000-0002-9412-1457"},"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":"Tao Kong","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055546056","display_name":"Fuchun Sun","orcid":"https://orcid.org/0000-0003-3546-6305"},"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":"Fuchun Sun","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041101317","display_name":"Huaping Liu","orcid":"https://orcid.org/0000-0002-4042-6044"},"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":"Huaping Liu","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101833400"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":8.1134,"has_fulltext":false,"cited_by_count":71,"citation_normalized_percentile":{"value":0.976525,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2038","last_page":"2043"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":1.0,"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"}},{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9951000213623047,"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/T10868","display_name":"Soft Robotics and Applications","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/grasp","display_name":"GRASP","score":0.9743814468383789},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8009679317474365},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7981823086738586},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.7643133401870728},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7606543302536011},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5957879424095154},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5500683188438416},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5480674505233765},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.5294603705406189},{"id":"https://openalex.org/keywords/stack","display_name":"Stack (abstract data type)","score":0.4589870870113373},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44390997290611267},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.2030453085899353},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.06882408261299133}],"concepts":[{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.9743814468383789},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8009679317474365},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7981823086738586},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.7643133401870728},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7606543302536011},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5957879424095154},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5500683188438416},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5480674505233765},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.5294603705406189},{"id":"https://openalex.org/C9395851","wikidata":"https://www.wikidata.org/wiki/Q177929","display_name":"Stack (abstract data type)","level":2,"score":0.4589870870113373},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44390997290611267},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2030453085899353},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.06882408261299133}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra.2016.7487351","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2016.7487351","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1510186039","https://openalex.org/W1820657498","https://openalex.org/W1829663505","https://openalex.org/W1892339738","https://openalex.org/W1970741595","https://openalex.org/W1999156278","https://openalex.org/W2033223309","https://openalex.org/W2041376653","https://openalex.org/W2076189885","https://openalex.org/W2123435073","https://openalex.org/W2126496149","https://openalex.org/W2155893237","https://openalex.org/W2156219259","https://openalex.org/W2156222070","https://openalex.org/W2163605009","https://openalex.org/W2296360731","https://openalex.org/W3047905600","https://openalex.org/W4211241511","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W3185561939","https://openalex.org/W2095705906","https://openalex.org/W3111283311","https://openalex.org/W2975200075","https://openalex.org/W2801801420","https://openalex.org/W2007544051","https://openalex.org/W2732308154","https://openalex.org/W1988485990","https://openalex.org/W3177406559","https://openalex.org/W2334336442"],"abstract_inverted_index":{"Grasp":[0],"an":[1],"object":[2,27,34,138],"from":[3,39,139],"a":[4,12,32,45,60,88,99,124,136],"stack":[5,41,141],"of":[6,24,78,106,118],"objects":[7,108],"in":[8,14,73],"real-time":[9],"is":[10,49,81],"still":[11],"challenge":[13],"robotics.":[15],"This":[16],"requires":[17],"the":[18,22,40,53,79,93,116,131,140],"robot":[19,132],"to":[20,51],"have":[21],"ability":[23],"both":[25],"fast":[26],"discovery":[28],"and":[29,43,128,142],"grasp":[30,47,52,144],"detection:":[31],"target":[33,137],"should":[35],"be":[36],"picked":[37],"out":[38],"first":[42],"then":[44],"proper":[46],"configuration":[48],"applied":[50],"object.":[54],"In":[55],"this":[56],"paper,":[57],"we":[58,96,114],"propose":[59],"shared":[61,120],"convolutional":[62],"neural":[63],"network":[64],"(CNN)":[65],"which":[66,90,103],"can":[67,133],"simultaneously":[68],"implement":[69],"these":[70],"two":[71],"tasks":[72],"real-time.":[74],"The":[75],"processing":[76],"speed":[77],"model":[80,122],"about":[82],"100":[83],"frames":[84],"per":[85],"second":[86],"on":[87,123],"GPU":[89],"largely":[91],"satisfies":[92],"requirement.":[94],"Meanwhile,":[95],"also":[97],"establish":[98],"labeled":[100],"RGBD":[101],"dataset":[102],"contains":[104],"scenes":[105],"stacked":[107],"for":[109],"robotic":[110,126],"grasping.":[111],"At":[112],"last,":[113],"demonstrate":[115],"implementation":[117],"our":[119],"CNN":[121],"real":[125],"platform":[127],"show":[129],"that":[130],"accurately":[134],"discover":[135],"successfully":[143],"it.":[145]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":11},{"year":2016,"cited_by_count":1}],"updated_date":"2026-03-13T14:20:09.374765","created_date":"2025-10-10T00:00:00"}