{"id":"https://openalex.org/W4383108616","doi":"https://doi.org/10.1109/icra48891.2023.10160786","title":"Self-Supervised Learning of Object Segmentation from Unlabeled RGB-D Videos","display_name":"Self-Supervised Learning of Object Segmentation from Unlabeled RGB-D Videos","publication_year":2023,"publication_date":"2023-05-29","ids":{"openalex":"https://openalex.org/W4383108616","doi":"https://doi.org/10.1109/icra48891.2023.10160786"},"language":"en","primary_location":{"id":"doi:10.1109/icra48891.2023.10160786","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icra48891.2023.10160786","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 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/A5101925893","display_name":"Shiyang Lu","orcid":"https://orcid.org/0009-0007-7857-8768"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shiyang Lu","raw_affiliation_strings":["Rutgers University,Department of Computer Science,New Brunswick,NJ,USA,08901"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers University,Department of Computer Science,New Brunswick,NJ,USA,08901","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025646177","display_name":"Yunfu Deng","orcid":null},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yunfu Deng","raw_affiliation_strings":["Rutgers University,Department of Electrical and Computer Engineering,New Brunswick,NJ,08901"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers University,Department of Electrical and Computer Engineering,New Brunswick,NJ,08901","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068615270","display_name":"Abdeslam Boularias","orcid":"https://orcid.org/0000-0002-5587-4560"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abdeslam Boularias","raw_affiliation_strings":["Rutgers University,Department of Computer Science,New Brunswick,NJ,USA,08901"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers University,Department of Computer Science,New Brunswick,NJ,USA,08901","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010667333","display_name":"Kostas E. Bekris","orcid":"https://orcid.org/0000-0002-0675-3324"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kostas Bekris","raw_affiliation_strings":["Rutgers University,Department of Computer Science,New Brunswick,NJ,USA,08901"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers University,Department of Computer Science,New Brunswick,NJ,USA,08901","institution_ids":["https://openalex.org/I102322142"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11816441,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"34","issue":null,"first_page":"7017","last_page":"7023"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9998000264167786,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9988999962806702,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9987999796867371,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8573403358459473},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8140735626220703},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6935135126113892},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6309143304824829},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5890274047851562},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.49751928448677063},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.4966738820075989},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4748057425022125},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.47466161847114563},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.462146133184433},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4467518627643585},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.42064282298088074},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4177488088607788},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.12690886855125427},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09068489074707031}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8573403358459473},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8140735626220703},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6935135126113892},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6309143304824829},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5890274047851562},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.49751928448677063},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.4966738820075989},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4748057425022125},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.47466161847114563},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.462146133184433},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4467518627643585},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.42064282298088074},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4177488088607788},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.12690886855125427},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09068489074707031},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra48891.2023.10160786","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icra48891.2023.10160786","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2883445677","display_name":null,"funder_award_id":"1734492,1846043,2132972","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W219040644","https://openalex.org/W1861492603","https://openalex.org/W1893195674","https://openalex.org/W1919709169","https://openalex.org/W1970531977","https://openalex.org/W1987648924","https://openalex.org/W2067191022","https://openalex.org/W2145001205","https://openalex.org/W2222512263","https://openalex.org/W2285211156","https://openalex.org/W2575671312","https://openalex.org/W2603737562","https://openalex.org/W2763391026","https://openalex.org/W2961348656","https://openalex.org/W2963749571","https://openalex.org/W2964309882","https://openalex.org/W2966885779","https://openalex.org/W2970642899","https://openalex.org/W3005680577","https://openalex.org/W3009561768","https://openalex.org/W3011972190","https://openalex.org/W3035060554","https://openalex.org/W3044828450","https://openalex.org/W3046136908","https://openalex.org/W3046208551","https://openalex.org/W3089768235","https://openalex.org/W3129110783","https://openalex.org/W3171007011","https://openalex.org/W3172288085","https://openalex.org/W3204767403","https://openalex.org/W3205087828","https://openalex.org/W3208608305","https://openalex.org/W3214349960","https://openalex.org/W4221167013","https://openalex.org/W4243493583","https://openalex.org/W4287120947","https://openalex.org/W6639102338","https://openalex.org/W6642952538","https://openalex.org/W6682124274","https://openalex.org/W6748481559","https://openalex.org/W6767021658","https://openalex.org/W6774314701","https://openalex.org/W6774670964","https://openalex.org/W6779326418","https://openalex.org/W6781542114","https://openalex.org/W6781732661","https://openalex.org/W6786614245","https://openalex.org/W6793555798","https://openalex.org/W6796303064","https://openalex.org/W6798280791","https://openalex.org/W6803857009","https://openalex.org/W6809805176","https://openalex.org/W6864332406"],"related_works":["https://openalex.org/W3125011624","https://openalex.org/W1508631387","https://openalex.org/W2370917603","https://openalex.org/W2952760143","https://openalex.org/W2017776670","https://openalex.org/W2347897961","https://openalex.org/W2979236518","https://openalex.org/W3016928466","https://openalex.org/W2358318464","https://openalex.org/W4389574804"],"abstract_inverted_index":{"This":[0],"work":[1],"proposes":[2],"a":[3,31,35,47,110,120,164],"self-supervised":[4,43],"learning":[5],"system":[6],"for":[7,160],"segmenting":[8],"rigid":[9],"objects":[10],"in":[11],"RGB":[12],"images.":[13],"The":[14,66,153],"proposed":[15,154],"pipeline":[16],"is":[17,46,61,74],"trained":[18],"on":[19,52,139],"unlabeled":[20],"RGB-D":[21],"videos":[22,82],"of":[23,41,56,150],"static":[24],"objects,":[25],"which":[26,146],"can":[27],"be":[28],"captured":[29],"with":[30,70],"camera":[32],"carried":[33],"by":[34,163],"mobile":[36],"robot.":[37],"A":[38],"key":[39],"feature":[40,112],"the":[42,53,57,124,136],"training":[44],"process":[45],"graph-matching":[48],"algorithm":[49],"that":[50,60],"operates":[51],"over-segmentation":[54],"output":[55],"point":[58,71],"cloud":[59,72],"reconstructed":[62],"from":[63,102],"each":[64],"video.":[65],"graph":[67],"matching,":[68],"along":[69],"registration,":[73],"able":[75],"to":[76,108,127],"find":[77],"reoccurring":[78],"object":[79,88,100,132,161],"patterns":[80],"across":[81],"and":[83,142],"combine":[84],"them":[85],"into":[86,131],"3D":[87,103],"pseudo":[89,104],"labels,":[90],"even":[91],"under":[92],"occlusions":[93],"or":[94],"different":[95],"viewing":[96],"angles.":[97],"Projected":[98],"2D":[99],"masks":[101],"labels":[105],"are":[106],"used":[107],"train":[109],"pixel-wise":[111],"extractor":[113],"through":[114],"contrastive":[115],"learning.":[116],"During":[117],"online":[118],"inference,":[119],"clustering":[121],"method":[122,155],"uses":[123],"learned":[125],"features":[126],"cluster":[128],"foreground":[129],"pixels":[130],"segments.":[133],"Experiments":[134],"highlight":[135],"method's":[137],"effectiveness":[138],"both":[140],"real":[141],"synthetic":[143],"video":[144],"datasets,":[145],"include":[147],"cluttered":[148],"scenes":[149],"tabletop":[151],"objects.":[152],"outperforms":[156],"existing":[157],"unsupervised":[158],"methods":[159],"segmentation":[162],"large":[165],"margin.":[166]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
