{"id":"https://openalex.org/W4221147401","doi":"https://doi.org/10.1109/tpami.2022.3198480","title":"EM-Driven Unsupervised Learning for Efficient Motion Segmentation","display_name":"EM-Driven Unsupervised Learning for Efficient Motion Segmentation","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4221147401","doi":"https://doi.org/10.1109/tpami.2022.3198480","pmid":"https://pubmed.ncbi.nlm.nih.gov/35984802"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2022.3198480","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3198480","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2201.02074","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102913988","display_name":"Etienne Meunier","orcid":"https://orcid.org/0000-0002-5310-2305"},"institutions":[{"id":"https://openalex.org/I4210133778","display_name":"Centre Inria de l'Universit\u00e9 de Rennes","ror":"https://ror.org/04040yw90","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1326498283","https://openalex.org/I4210133778"]},{"id":"https://openalex.org/I4210166586","display_name":"Laboratoire de Biologie Mol\u00e9culaire et Cellulaire des Eucaryotes","ror":"https://ror.org/05mx55f96","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I39804081","https://openalex.org/I4210096427","https://openalex.org/I4210166586"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Etienne Meunier","raw_affiliation_strings":["Inria, Centre Rennes - Bretagne Atlantique, Rennes cedex, France","Biologie Cellulaire et Cancer (26 Rue d'Ulm 75248 PARIS CEDEX 05 - France)","SERPICO - Space-timE RePresentation, Imaging and cellular dynamics of molecular COmplexes (Campus de Beaulieu 35042 Rennes cedex - France)"],"raw_orcid":"https://orcid.org/0000-0002-5310-2305","affiliations":[{"raw_affiliation_string":"Inria, Centre Rennes - Bretagne Atlantique, Rennes cedex, France","institution_ids":["https://openalex.org/I4210133778"]},{"raw_affiliation_string":"Biologie Cellulaire et Cancer (26 Rue d'Ulm 75248 PARIS CEDEX 05 - France)","institution_ids":["https://openalex.org/I4210166586"]},{"raw_affiliation_string":"SERPICO - Space-timE RePresentation, Imaging and cellular dynamics of molecular COmplexes (Campus de Beaulieu 35042 Rennes cedex - France)","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000203590","display_name":"Ana\u00efs Badoual","orcid":"https://orcid.org/0000-0001-7303-6344"},"institutions":[{"id":"https://openalex.org/I4210133778","display_name":"Centre Inria de l'Universit\u00e9 de Rennes","ror":"https://ror.org/04040yw90","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1326498283","https://openalex.org/I4210133778"]},{"id":"https://openalex.org/I4210166586","display_name":"Laboratoire de Biologie Mol\u00e9culaire et Cellulaire des Eucaryotes","ror":"https://ror.org/05mx55f96","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I39804081","https://openalex.org/I4210096427","https://openalex.org/I4210166586"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Anais Badoual","raw_affiliation_strings":["Inria, Centre Rennes - Bretagne Atlantique, Rennes cedex, France","Biologie Cellulaire et Cancer (26 Rue d'Ulm 75248 PARIS CEDEX 05 - France)","SERPICO - Space-timE RePresentation, Imaging and cellular dynamics of molecular COmplexes (Campus de Beaulieu 35042 Rennes cedex - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inria, Centre Rennes - Bretagne Atlantique, Rennes cedex, France","institution_ids":["https://openalex.org/I4210133778"]},{"raw_affiliation_string":"Biologie Cellulaire et Cancer (26 Rue d'Ulm 75248 PARIS CEDEX 05 - France)","institution_ids":["https://openalex.org/I4210166586"]},{"raw_affiliation_string":"SERPICO - Space-timE RePresentation, Imaging and cellular dynamics of molecular COmplexes (Campus de Beaulieu 35042 Rennes cedex - France)","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029961820","display_name":"Patrick Bouth\u00e9my","orcid":null},"institutions":[{"id":"https://openalex.org/I4210133778","display_name":"Centre Inria de l'Universit\u00e9 de Rennes","ror":"https://ror.org/04040yw90","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1326498283","https://openalex.org/I4210133778"]},{"id":"https://openalex.org/I4210166586","display_name":"Laboratoire de Biologie Mol\u00e9culaire et Cellulaire des Eucaryotes","ror":"https://ror.org/05mx55f96","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I39804081","https://openalex.org/I4210096427","https://openalex.org/I4210166586"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Patrick Bouthemy","raw_affiliation_strings":["Inria, Centre Rennes - Bretagne Atlantique, Rennes cedex, France","Biologie Cellulaire et Cancer (26 Rue d'Ulm 75248 PARIS CEDEX 05 - France)","SERPICO - Space-timE RePresentation, Imaging and cellular dynamics of molecular COmplexes (Campus de Beaulieu 35042 Rennes cedex - France)"],"raw_orcid":"https://orcid.org/0000-0002-7852-9831","affiliations":[{"raw_affiliation_string":"Inria, Centre Rennes - Bretagne Atlantique, Rennes cedex, France","institution_ids":["https://openalex.org/I4210133778"]},{"raw_affiliation_string":"Biologie Cellulaire et Cancer (26 Rue d'Ulm 75248 PARIS CEDEX 05 - France)","institution_ids":["https://openalex.org/I4210166586"]},{"raw_affiliation_string":"SERPICO - Space-timE RePresentation, Imaging and cellular dynamics of molecular COmplexes (Campus de Beaulieu 35042 Rennes cedex - France)","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.8703,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.86453881,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"45","issue":"4","first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9998999834060669,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9998999834060669,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9908999800682068,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9829999804496765,"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":0.777122974395752},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.7202437520027161},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6228899955749512},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6177583336830139},{"id":"https://openalex.org/keywords/affine-transformation","display_name":"Affine transformation","score":0.4697207510471344},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.45943233370780945},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36601993441581726},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32708051800727844},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32429036498069763},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12111222743988037},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.0742766261100769}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.777122974395752},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.7202437520027161},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6228899955749512},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6177583336830139},{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.4697207510471344},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.45943233370780945},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36601993441581726},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32708051800727844},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32429036498069763},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12111222743988037},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0742766261100769},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tpami.2022.3198480","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3198480","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:35984802","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35984802","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null},{"id":"pmh:oai:arXiv.org:2201.02074","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2201.02074","pdf_url":"https://arxiv.org/pdf/2201.02074","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:HAL:hal-03516617v1","is_oa":false,"landing_page_url":"https://hal.science/hal-03516617","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023, 45 (4), pp.4462-4473. &#x27E8;10.1109/TPAMI.2022.3198480&#x27E9;","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2201.02074","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2201.02074","pdf_url":"https://arxiv.org/pdf/2201.02074","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W1503398984","https://openalex.org/W1522301498","https://openalex.org/W1579853615","https://openalex.org/W1755891578","https://openalex.org/W1901129140","https://openalex.org/W1983578033","https://openalex.org/W1991278573","https://openalex.org/W1999052676","https://openalex.org/W1999305212","https://openalex.org/W2051434435","https://openalex.org/W2059279601","https://openalex.org/W2076208743","https://openalex.org/W2076756823","https://openalex.org/W2085669808","https://openalex.org/W2097099938","https://openalex.org/W2113708607","https://openalex.org/W2114190460","https://openalex.org/W2116918894","https://openalex.org/W2124514145","https://openalex.org/W2138682569","https://openalex.org/W2141720053","https://openalex.org/W2142912032","https://openalex.org/W2147253850","https://openalex.org/W2156928155","https://openalex.org/W2171116555","https://openalex.org/W2259424905","https://openalex.org/W2326050853","https://openalex.org/W2470139095","https://openalex.org/W2566030665","https://openalex.org/W2737008123","https://openalex.org/W2894138533","https://openalex.org/W2895340898","https://openalex.org/W2912857574","https://openalex.org/W2913055992","https://openalex.org/W2955084925","https://openalex.org/W2955863859","https://openalex.org/W2963150697","https://openalex.org/W2963548592","https://openalex.org/W2963551464","https://openalex.org/W2963878474","https://openalex.org/W2963881378","https://openalex.org/W2963983744","https://openalex.org/W2964968086","https://openalex.org/W2993235622","https://openalex.org/W3001586682","https://openalex.org/W3049318984","https://openalex.org/W3082701951","https://openalex.org/W3108460979","https://openalex.org/W3109908659","https://openalex.org/W3133902371","https://openalex.org/W3143732405","https://openalex.org/W3167938559","https://openalex.org/W3182236906","https://openalex.org/W3203092180","https://openalex.org/W6631190155","https://openalex.org/W6634817459","https://openalex.org/W6718986230","https://openalex.org/W6742720488","https://openalex.org/W6779809370","https://openalex.org/W6782806660","https://openalex.org/W6803205562","https://openalex.org/W6805200250","https://openalex.org/W6881106607"],"related_works":["https://openalex.org/W4295532600","https://openalex.org/W2063823869","https://openalex.org/W2047973478","https://openalex.org/W2067569035","https://openalex.org/W2090985514","https://openalex.org/W2113666009","https://openalex.org/W2012410061","https://openalex.org/W2053610073","https://openalex.org/W2970427506","https://openalex.org/W1997160662"],"abstract_inverted_index":{"In":[0,148],"this":[1],"paper,":[2],"we":[3,96],"present":[4],"a":[5,27,58,61,65,99,108,128],"CNN-based":[6],"fully":[7],"unsupervised":[8],"method":[9,151],"for":[10,101],"motion":[11,32,38,70,116,161],"segmentation":[12,71,100,162],"from":[13],"optical":[14,21,104,136,144],"flow.":[15],"We":[16,118],"assume":[17],"that":[18,74],"the":[19,49,87,92,135],"input":[20],"flow":[22,105,137,145],"can":[23,97],"be":[24],"represented":[25],"as":[26,146],"piecewise":[28],"set":[29],"of":[30,43,68],"parametric":[31],"models,":[33],"typically,":[34],"affine":[35],"or":[36,80],"quadratic":[37],"models.":[39,117],"The":[40],"core":[41],"idea":[42],"our":[44,69,150],"work":[45],"is":[46,94,152],"to":[47,55,86,140,156],"leverage":[48],"Expectation-Maximization":[50],"(EM)":[51],"framework":[52],"in":[53,57,84,107],"order":[54],"design":[56,155],"well-founded":[59],"manner":[60],"loss":[62,121],"function":[63],"and":[64,112,126,172,174],"training":[66],"procedure":[67],"neural":[72],"network":[73,93,142,163],"does":[75],"not":[76],"require":[77],"either":[78],"ground-truth":[79],"manual":[81],"annotation.":[82],"However,":[83],"contrast":[85],"classical":[88],"iterative":[89],"EM,":[90],"once":[91],"trained,":[95],"provide":[98],"any":[102,115,141],"unseen":[103],"field":[106],"single":[109],"inference":[110],"step":[111],"without":[113],"estimating":[114],"investigate":[119],"different":[120],"functions":[122],"including":[123],"robust":[124],"ones":[125],"propose":[127],"novel":[129],"efficient":[130],"data":[131],"augmentation":[132],"technique":[133],"on":[134,166],"field,":[138],"applicable":[139],"taking":[143],"input.":[147],"addition,":[149],"able":[153],"by":[154],"segment":[157],"multiple":[158],"motions.":[159],"Our":[160],"was":[164],"tested":[165],"four":[167],"benchmarks,":[168],"DAVIS2016,":[169],"SegTrackV2,":[170],"FBMS59,":[171],"MoCA,":[173],"performed":[175],"very":[176],"well,":[177],"while":[178],"being":[179],"fast":[180],"at":[181],"test":[182],"time.":[183]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":5}],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2025-10-10T00:00:00"}
