{"id":"https://openalex.org/W3205186076","doi":"https://doi.org/10.1109/icra48506.2021.9562046","title":"Robotic Grasping through Combined Image-Based Grasp Proposal and 3D Reconstruction","display_name":"Robotic Grasping through Combined Image-Based Grasp Proposal and 3D Reconstruction","publication_year":2021,"publication_date":"2021-05-30","ids":{"openalex":"https://openalex.org/W3205186076","doi":"https://doi.org/10.1109/icra48506.2021.9562046","mag":"3205186076"},"language":"en","primary_location":{"id":"doi:10.1109/icra48506.2021.9562046","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48506.2021.9562046","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 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/A5102830923","display_name":"Daniel Yang","orcid":"https://orcid.org/0000-0003-0532-1455"},"institutions":[{"id":"https://openalex.org/I4210101778","display_name":"Samsung (United States)","ror":"https://ror.org/01bfbvm65","country_code":"US","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210101778"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Daniel Yang","raw_affiliation_strings":["Samsung AI Center NY,New York,NY,10014","Samsung AI Center NY, New York, NY"],"affiliations":[{"raw_affiliation_string":"Samsung AI Center NY,New York,NY,10014","institution_ids":["https://openalex.org/I4210101778"]},{"raw_affiliation_string":"Samsung AI Center NY, New York, NY","institution_ids":["https://openalex.org/I4210101778"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080668728","display_name":"Tarik Tosun","orcid":"https://orcid.org/0000-0003-0866-0591"},"institutions":[{"id":"https://openalex.org/I4210101778","display_name":"Samsung (United States)","ror":"https://ror.org/01bfbvm65","country_code":"US","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210101778"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tarik Tosun","raw_affiliation_strings":["Samsung AI Center NY,New York,NY,10014","Samsung AI Center NY, New York, NY"],"affiliations":[{"raw_affiliation_string":"Samsung AI Center NY,New York,NY,10014","institution_ids":["https://openalex.org/I4210101778"]},{"raw_affiliation_string":"Samsung AI Center NY, New York, NY","institution_ids":["https://openalex.org/I4210101778"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066880690","display_name":"Benjamin Eisner","orcid":null},"institutions":[{"id":"https://openalex.org/I4210101778","display_name":"Samsung (United States)","ror":"https://ror.org/01bfbvm65","country_code":"US","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210101778"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Benjamin Eisner","raw_affiliation_strings":["Samsung AI Center NY,New York,NY,10014","Samsung AI Center NY, New York, NY"],"affiliations":[{"raw_affiliation_string":"Samsung AI Center NY,New York,NY,10014","institution_ids":["https://openalex.org/I4210101778"]},{"raw_affiliation_string":"Samsung AI Center NY, New York, NY","institution_ids":["https://openalex.org/I4210101778"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033839227","display_name":"Volkan Isler","orcid":"https://orcid.org/0000-0002-0868-5441"},"institutions":[{"id":"https://openalex.org/I4210101778","display_name":"Samsung (United States)","ror":"https://ror.org/01bfbvm65","country_code":"US","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210101778"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Volkan Isler","raw_affiliation_strings":["Samsung AI Center NY,New York,NY,10014","Samsung AI Center NY, New York, NY"],"affiliations":[{"raw_affiliation_string":"Samsung AI Center NY,New York,NY,10014","institution_ids":["https://openalex.org/I4210101778"]},{"raw_affiliation_string":"Samsung AI Center NY, New York, NY","institution_ids":["https://openalex.org/I4210101778"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100392975","display_name":"Daniel Lee","orcid":"https://orcid.org/0000-0001-5326-8148"},"institutions":[{"id":"https://openalex.org/I4210101778","display_name":"Samsung (United States)","ror":"https://ror.org/01bfbvm65","country_code":"US","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210101778"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Lee","raw_affiliation_strings":["Samsung AI Center NY,New York,NY,10014","Samsung AI Center NY, New York, NY"],"affiliations":[{"raw_affiliation_string":"Samsung AI Center NY,New York,NY,10014","institution_ids":["https://openalex.org/I4210101778"]},{"raw_affiliation_string":"Samsung AI Center NY, New York, NY","institution_ids":["https://openalex.org/I4210101778"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5102830923"],"corresponding_institution_ids":["https://openalex.org/I4210101778"],"apc_list":null,"apc_paid":null,"fwci":3.8451,"has_fulltext":false,"cited_by_count":36,"citation_normalized_percentile":{"value":0.93811029,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"6350","last_page":"6356"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9998999834060669,"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":0.9998999834060669,"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":0.991599977016449,"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":0.991100013256073,"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/grasp","display_name":"GRASP","score":0.981577455997467},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7537075281143188},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7368304133415222},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7257238030433655},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6109105348587036},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5774262547492981},{"id":"https://openalex.org/keywords/grippers","display_name":"Grippers","score":0.5200688242912292},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.48911052942276},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4666799306869507},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1449517011642456}],"concepts":[{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.981577455997467},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7537075281143188},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7368304133415222},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7257238030433655},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6109105348587036},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5774262547492981},{"id":"https://openalex.org/C2775960376","wikidata":"https://www.wikidata.org/wiki/Q1435859","display_name":"Grippers","level":2,"score":0.5200688242912292},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.48911052942276},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4666799306869507},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1449517011642456},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"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/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra48506.2021.9562046","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48506.2021.9562046","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.6600000262260437}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W70651934","https://openalex.org/W1510186039","https://openalex.org/W1959608418","https://openalex.org/W2005756025","https://openalex.org/W2083461908","https://openalex.org/W2119851068","https://openalex.org/W2158782408","https://openalex.org/W2194775991","https://openalex.org/W2342277278","https://openalex.org/W2524140598","https://openalex.org/W2560722161","https://openalex.org/W2600030077","https://openalex.org/W2603737562","https://openalex.org/W2786036844","https://openalex.org/W2811406147","https://openalex.org/W2925173345","https://openalex.org/W2925241625","https://openalex.org/W2962737955","https://openalex.org/W2962746398","https://openalex.org/W2962778872","https://openalex.org/W2962920843","https://openalex.org/W2963446712","https://openalex.org/W2963627347","https://openalex.org/W2964000117","https://openalex.org/W2964239605","https://openalex.org/W2969090342","https://openalex.org/W2972998376","https://openalex.org/W2986303149","https://openalex.org/W2995905276","https://openalex.org/W3003495719","https://openalex.org/W3045473040","https://openalex.org/W3089966216","https://openalex.org/W4288106818","https://openalex.org/W4288414710","https://openalex.org/W6640963894","https://openalex.org/W6703956885","https://openalex.org/W6747827861","https://openalex.org/W6750179221","https://openalex.org/W6752823625","https://openalex.org/W6760546089","https://openalex.org/W6766377360","https://openalex.org/W6767276508"],"related_works":["https://openalex.org/W2583647647","https://openalex.org/W4210583734","https://openalex.org/W2613999385","https://openalex.org/W2389377526","https://openalex.org/W184672670","https://openalex.org/W2189406283","https://openalex.org/W2793366677","https://openalex.org/W1636820063","https://openalex.org/W3185561939","https://openalex.org/W4386794497"],"abstract_inverted_index":{"We":[0,132],"present":[1],"a":[2,11,17,29,121,129,143,162],"novel":[3],"approach":[4],"to":[5,42,50,65],"robotic":[6],"grasp":[7,13,54,58,67,76,96,145],"planning":[8],"using":[9,46],"both":[10,43,68,112],"learned":[12,18,144],"proposal":[14,59,146],"network":[15,91],"and":[16,70,95,114,152],"3D":[19],"shape":[20],"reconstruction":[21,49,149],"network.":[22],"Our":[23],"system":[24,62,109,157],"generates":[25],"6-DOF":[26],"grasps":[27],"from":[28],"single":[30],"RGB-D":[31],"image":[32],"of":[33,107,141],"the":[34,47,52,57,75,79,85,90,105,139],"target":[35],"object,":[36],"which":[37],"is":[38,63,81],"provided":[39],"as":[40],"input":[41,86],"networks.":[44],"By":[45],"geometric":[48,148],"refine":[51],"candidate":[53],"produced":[55],"by":[56],"network,":[60],"our":[61,101,108,156],"able":[64],"accurately":[66],"known":[69,113],"unknown":[71,115],"objects,":[72],"even":[73],"when":[74],"location":[77],"on":[78],"object":[80],"not":[82],"visible":[83],"in":[84,120,128,161],"image.This":[87],"paper":[88],"presents":[89],"architectures,":[92],"training":[93],"procedures,":[94],"refinement":[97],"method":[98],"that":[99,137,155],"comprise":[100],"system.":[102],"Experiments":[103],"demonstrate":[104],"efficacy":[106],"at":[110],"grasping":[111,163],"objects":[116],"(91%":[117],"success":[118,126],"rate":[119,127],"physical":[122],"robot":[123],"environment,":[124],"84%":[125],"simulated":[130],"environment).":[131],"additionally":[133],"perform":[134],"ablation":[135],"studies":[136],"show":[138,154],"benefits":[140],"combining":[142],"with":[147],"for":[150],"grasping,":[151],"also":[153],"outperforms":[158],"several":[159],"baselines":[160],"task.":[164]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
