{"id":"https://openalex.org/W2756627269","doi":"https://doi.org/10.1109/icra.2018.8460950","title":"Label Fusion: A Pipeline for Generating Ground Truth Labels for Real RGBD Data of Cluttered Scenes","display_name":"Label Fusion: A Pipeline for Generating Ground Truth Labels for Real RGBD Data of Cluttered Scenes","publication_year":2018,"publication_date":"2018-05-01","ids":{"openalex":"https://openalex.org/W2756627269","doi":"https://doi.org/10.1109/icra.2018.8460950","mag":"2756627269"},"language":"en","primary_location":{"id":"doi:10.1109/icra.2018.8460950","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2018.8460950","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hdl.handle.net/1721.1/129426","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5029732124","display_name":"Pat Marion","orcid":null},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Pat Marion","raw_affiliation_strings":["Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021289514","display_name":"Pete Florence","orcid":"https://orcid.org/0000-0002-7148-5645"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peter R. Florence","raw_affiliation_strings":["Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018953170","display_name":"Lucas Manuelli","orcid":null},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lucas Manuelli","raw_affiliation_strings":["Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074291890","display_name":"Russ Tedrake","orcid":null},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Russ Tedrake","raw_affiliation_strings":["Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5029732124"],"corresponding_institution_ids":["https://openalex.org/I63966007"],"apc_list":null,"apc_paid":null,"fwci":6.0628,"has_fulltext":false,"cited_by_count":112,"citation_normalized_percentile":{"value":0.97276536,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3235","last_page":"3242"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994999766349792,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9994999766349792,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T12549","display_name":"Image and Object Detection Techniques","score":0.9983999729156494,"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":0.824164628982544},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.777100682258606},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.7457945346832275},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.6895551681518555},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6795116662979126},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6456245183944702},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.579110324382782},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.484681636095047},{"id":"https://openalex.org/keywords/pipeline-transport","display_name":"Pipeline transport","score":0.47703784704208374},{"id":"https://openalex.org/keywords/polygon-mesh","display_name":"Polygon mesh","score":0.4741372764110565},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4307031035423279},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37729015946388245},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.16465085744857788}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.824164628982544},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.777100682258606},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7457945346832275},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.6895551681518555},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6795116662979126},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6456245183944702},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.579110324382782},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.484681636095047},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.47703784704208374},{"id":"https://openalex.org/C31487907","wikidata":"https://www.wikidata.org/wiki/Q1154597","display_name":"Polygon mesh","level":2,"score":0.4741372764110565},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4307031035423279},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37729015946388245},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.16465085744857788},{"id":"https://openalex.org/C87717796","wikidata":"https://www.wikidata.org/wiki/Q146326","display_name":"Environmental 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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icra.2018.8460950","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2018.8460950","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},{"id":"pmh:oai:dspace.mit.edu:1721.1/129426","is_oa":true,"landing_page_url":"https://hdl.handle.net/1721.1/129426","pdf_url":null,"source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv","raw_type":"http://purl.org/eprint/type/ConferencePaper"}],"best_oa_location":{"id":"pmh:oai:dspace.mit.edu:1721.1/129426","is_oa":true,"landing_page_url":"https://hdl.handle.net/1721.1/129426","pdf_url":null,"source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv","raw_type":"http://purl.org/eprint/type/ConferencePaper"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1938204631","https://openalex.org/W1945811542","https://openalex.org/W2009422376","https://openalex.org/W2034950486","https://openalex.org/W2059625476","https://openalex.org/W2117539524","https://openalex.org/W2221752211","https://openalex.org/W2250172176","https://openalex.org/W2344109021","https://openalex.org/W2412782625","https://openalex.org/W2431874326","https://openalex.org/W2443711627","https://openalex.org/W2487365028","https://openalex.org/W2519911873","https://openalex.org/W2563685048","https://openalex.org/W2580726517","https://openalex.org/W2593617942","https://openalex.org/W2594519801","https://openalex.org/W2600030077","https://openalex.org/W2603737562","https://openalex.org/W2963654160","https://openalex.org/W2963678509","https://openalex.org/W2963730616","https://openalex.org/W2963782069","https://openalex.org/W6640575961","https://openalex.org/W6688892919","https://openalex.org/W6691696098","https://openalex.org/W6703177225","https://openalex.org/W6722836162","https://openalex.org/W6726839888","https://openalex.org/W6734868337"],"related_works":["https://openalex.org/W4380433113","https://openalex.org/W4386072068","https://openalex.org/W252339960","https://openalex.org/W2390529043","https://openalex.org/W2378320433","https://openalex.org/W2358343511","https://openalex.org/W2051877971","https://openalex.org/W1970117064","https://openalex.org/W1787170397","https://openalex.org/W4292347844"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"network":[2],"(DNN)":[3],"architectures":[4],"have":[5,54],"been":[6],"shown":[7],"to":[8,31,53,84,102,116,159,175,179,194],"outperform":[9],"traditional":[10],"pipelines":[11,27],"for":[12,46,61,148],"object":[13,95,133,164],"segmentation":[14],"and":[15,94,111,186,204],"pose":[16],"estimation":[17],"using":[18,127],"RGBD":[19,89,100,150],"data,":[20],"but":[21],"the":[22,34,39,124,137,141,153,190],"performance":[23,197],"of":[24,38,58,105,132,139,152,187],"these":[25,48],"DNN":[26,200],"is":[28,37,52,70,184],"directly":[29],"tied":[30],"how":[32,180],"representative":[33],"training":[35,182],"data":[36,60,90,183,191],"true":[40],"data.":[41],"Hence":[42],"a":[43,55,67,82,106,118,128,168,199],"key":[44],"requirement":[45,68],"employing":[47],"methods":[49],"in":[50,166],"practice":[51],"large":[56],"set":[57],"labeled":[59,163],"your":[62],"specific":[63],"robotic":[64],"manipulation":[65],"task,":[66],"that":[69],"not":[71],"generally":[72],"satisfied":[73],"by":[74],"existing":[75,113],"datasets.":[76],"In":[77],"this":[78,173],"paper":[79],"we":[80,144],"develop":[81],"pipeline":[83,156,206],"rapidly":[85],"generate":[86],"high":[87,196],"quality":[88,189],"with":[91],"pixelwise":[92],"labels":[93,147],"poses.":[96],"We":[97,122,171],"use":[98,172],"an":[99],"camera":[101],"collect":[103,160],"video":[104],"scene":[107,143],"from":[108,198],"multiple":[109],"viewpoints":[110],"leverage":[112],"reconstruction":[114,126],"techniques":[115],"produce":[117,146],"3D":[119,125,142],"dense":[120],"reconstruction.":[121],"label":[123],"human":[129],"assisted":[130],"ICP-fitting":[131],"meshes.":[134],"By":[135],"reprojecting":[136],"results":[138],"labeling":[140],"can":[145],"each":[149],"image":[151],"scene.":[154],"This":[155],"enabled":[157],"us":[158],"over":[161],"1,000,000":[162],"instances":[165],"just":[167],"few":[169],"days.":[170],"dataset":[174,203],"answer":[176],"questions":[177],"related":[178],"much":[181],"required,":[185],"what":[188],"must":[192],"be,":[193],"achieve":[195],"architecture.":[201],"Our":[202],"annotation":[205],"are":[207],"available":[208],"at":[209],"labelfusion.csail.mit.edu.":[210]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":16},{"year":2021,"cited_by_count":20},{"year":2020,"cited_by_count":18},{"year":2019,"cited_by_count":15},{"year":2018,"cited_by_count":4}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}