{"id":"https://openalex.org/W3114883909","doi":"https://doi.org/10.3390/sym13010038","title":"Unsupervised Learning from Videos for Object Discovery in Single Images","display_name":"Unsupervised Learning from Videos for Object Discovery in Single Images","publication_year":2020,"publication_date":"2020-12-29","ids":{"openalex":"https://openalex.org/W3114883909","doi":"https://doi.org/10.3390/sym13010038","mag":"3114883909"},"language":"en","primary_location":{"id":"doi:10.3390/sym13010038","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym13010038","pdf_url":"https://www.mdpi.com/2073-8994/13/1/38/pdf?version=1609251033","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/13/1/38/pdf?version=1609251033","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101979974","display_name":"Dong Zhao","orcid":"https://orcid.org/0000-0002-3991-9570"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Zhao","raw_affiliation_strings":["School of Information Science and Engineering, Shandong University, Qingdao 266237, China"],"raw_orcid":"https://orcid.org/0000-0002-3991-9570","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Shandong University, Qingdao 266237, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073652008","display_name":"Baoqing Ding","orcid":"https://orcid.org/0000-0001-5256-9061"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baoqing Ding","raw_affiliation_strings":["School of Information Science and Engineering, Shandong University, Qingdao 266237, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Shandong University, Qingdao 266237, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055779216","display_name":"Yulin Wu","orcid":"https://orcid.org/0000-0001-8116-715X"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yulin Wu","raw_affiliation_strings":["School of Information Science and Engineering, Shandong University, Qingdao 266237, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Shandong University, Qingdao 266237, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100333468","display_name":"Lei Chen","orcid":"https://orcid.org/0000-0002-4279-3892"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Chen","raw_affiliation_strings":["School of Information Science and Engineering, Shandong University, Qingdao 266237, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Shandong University, Qingdao 266237, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102804953","display_name":"Hongchao Zhou","orcid":"https://orcid.org/0000-0002-9783-0873"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongchao Zhou","raw_affiliation_strings":["School of Information Science and Engineering, Shandong University, Qingdao 266237, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Shandong University, Qingdao 266237, China","institution_ids":["https://openalex.org/I154099455"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5102804953"],"corresponding_institution_ids":["https://openalex.org/I154099455"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.4792,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.66564286,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"13","issue":"1","first_page":"38","last_page":"38"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9997000098228455,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9997000098228455,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9994000196456909,"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":0.8260409235954285},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8203167915344238},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6541708111763},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6487036943435669},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6095956563949585},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5783870220184326},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5617903470993042},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5085729360580444},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.493948757648468},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.487196147441864},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.477422833442688},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.46423807740211487},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.45267534255981445},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4431193470954895},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4401625692844391},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4240262508392334},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.41373714804649353}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8260409235954285},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8203167915344238},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6541708111763},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6487036943435669},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6095956563949585},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5783870220184326},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5617903470993042},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5085729360580444},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.493948757648468},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.487196147441864},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.477422833442688},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.46423807740211487},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.45267534255981445},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4431193470954895},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4401625692844391},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4240262508392334},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.41373714804649353},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/sym13010038","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym13010038","pdf_url":"https://www.mdpi.com/2073-8994/13/1/38/pdf?version=1609251033","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5d6ec544660a466cba3cab2373ea0dd4","is_oa":true,"landing_page_url":"https://doaj.org/article/5d6ec544660a466cba3cab2373ea0dd4","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry, Vol 13, Iss 1, p 38 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2073-8994/13/1/38/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/sym13010038","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/sym13010038","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym13010038","pdf_url":"https://www.mdpi.com/2073-8994/13/1/38/pdf?version=1609251033","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3129999161","display_name":null,"funder_award_id":"Grant No. 62001267","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7179575984","display_name":null,"funder_award_id":"62001267","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7227965641","display_name":null,"funder_award_id":"2020HW017","funder_id":"https://openalex.org/F4320311026","funder_display_name":"Shandong University"}],"funders":[{"id":"https://openalex.org/F4320311026","display_name":"Shandong University","ror":"https://ror.org/0207yh398"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3114883909.pdf","grobid_xml":"https://content.openalex.org/works/W3114883909.grobid-xml"},"referenced_works_count":79,"referenced_works":["https://openalex.org/W95926497","https://openalex.org/W219040644","https://openalex.org/W343636949","https://openalex.org/W1498436455","https://openalex.org/W1528789833","https://openalex.org/W1686810756","https://openalex.org/W1901129140","https://openalex.org/W1919709169","https://openalex.org/W1954128991","https://openalex.org/W1963920598","https://openalex.org/W1964884769","https://openalex.org/W1966601141","https://openalex.org/W1970899458","https://openalex.org/W1973054923","https://openalex.org/W1989348325","https://openalex.org/W1996140089","https://openalex.org/W2086052791","https://openalex.org/W2099471712","https://openalex.org/W2106471914","https://openalex.org/W2110370288","https://openalex.org/W2110534101","https://openalex.org/W2113708607","https://openalex.org/W2129260071","https://openalex.org/W2136922672","https://openalex.org/W2137950182","https://openalex.org/W2157244733","https://openalex.org/W2160847065","https://openalex.org/W2171116555","https://openalex.org/W2179146407","https://openalex.org/W2185208441","https://openalex.org/W2194775991","https://openalex.org/W2295160225","https://openalex.org/W2298532145","https://openalex.org/W2321533354","https://openalex.org/W2322739735","https://openalex.org/W2326050853","https://openalex.org/W2326925005","https://openalex.org/W2329995605","https://openalex.org/W2342877626","https://openalex.org/W2402395722","https://openalex.org/W2469838300","https://openalex.org/W2470139095","https://openalex.org/W2470142083","https://openalex.org/W2535388113","https://openalex.org/W2566030665","https://openalex.org/W2567514223","https://openalex.org/W2575671312","https://openalex.org/W2582761847","https://openalex.org/W2604392022","https://openalex.org/W2610147486","https://openalex.org/W2612860663","https://openalex.org/W2743157634","https://openalex.org/W2750549109","https://openalex.org/W2884436604","https://openalex.org/W2898543156","https://openalex.org/W2922119905","https://openalex.org/W2936835627","https://openalex.org/W2950083900","https://openalex.org/W2950187998","https://openalex.org/W2950926078","https://openalex.org/W2952339589","https://openalex.org/W2952863374","https://openalex.org/W2953259386","https://openalex.org/W2955084925","https://openalex.org/W2962849746","https://openalex.org/W2963090248","https://openalex.org/W2963395775","https://openalex.org/W2963420272","https://openalex.org/W2963749571","https://openalex.org/W2963983744","https://openalex.org/W3001586682","https://openalex.org/W3003662786","https://openalex.org/W3009672847","https://openalex.org/W3012889273","https://openalex.org/W3070936185","https://openalex.org/W4248881677","https://openalex.org/W6605611481","https://openalex.org/W6675895156","https://openalex.org/W6678200344"],"related_works":["https://openalex.org/W2983142544","https://openalex.org/W2891059443","https://openalex.org/W4281663961","https://openalex.org/W3208888551","https://openalex.org/W4313561566","https://openalex.org/W3208386644","https://openalex.org/W4220682630","https://openalex.org/W4389832810","https://openalex.org/W3163146846","https://openalex.org/W3133533225"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,18,38,79,82,109,117,127,130],"method":[4,134,201],"for":[5,163,187],"discovering":[6],"the":[7,29,56,75,88,143,152,157,173,185,199,218,223],"primary":[8,203],"objects":[9,36,204],"in":[10,17,166],"single":[11,39,110,167],"images":[12,183,221],"by":[13],"learning":[14,22,213],"from":[15,37,108,161,172,217],"videos":[16,162,179],"purely":[19],"unsupervised":[20,211],"manner\u2014the":[21],"process":[23],"is":[24,32,45,135,170],"based":[25,136],"on":[26,137,192],"videos,":[27],"but":[28],"generated":[30],"network":[31,159],"able":[33],"to":[34,101,140],"discover":[35],"input":[40,186],"image.":[41,111],"The":[42,189],"rough":[43],"idea":[44],"that":[46,60,177,198,210],"an":[47],"image":[48,123,212],"typically":[49],"consists":[50,125],"of":[51,78,90,126,182,220,226],"multiple":[52],"object":[53,92,106,164,194],"instances":[54,107],"(like":[55],"foreground":[57,128],"and":[58,67,129,146,206,222],"background)":[59],"have":[61],"spatial":[62],"transformations":[63],"across":[64],"video":[65,80],"frames":[66],"they":[68],"can":[69,98,215],"be":[70,99],"sparsely":[71,141],"represented.":[72],"By":[73],"exploring":[74],"sparsity":[76,219],"representation":[77],"with":[81],"neural":[83],"network,":[84],"one":[85],"may":[86],"learn":[87],"features":[89],"each":[91,122],"instance":[93],"without":[94],"any":[95],"labels,":[96],"which":[97,149,169,208],"used":[100],"discover,":[102],"recognize,":[103],"or":[104,180],"distinguish":[105],"In":[112],"this":[113],"paper,":[114],"we":[115],"consider":[116],"relatively":[118],"simple":[119],"scenario,":[120],"where":[121],"roughly":[124],"background.":[131],"Our":[132],"proposed":[133,200],"encoder-decoder":[138],"structures":[139],"represent":[142],"foreground,":[144],"background,":[145],"segmentation":[147,195],"mask,":[148],"further":[150],"reconstruct":[151],"original":[153],"images.":[154],"We":[155],"apply":[156],"feed-forward":[158],"trained":[160],"discovery":[165],"images,":[168],"different":[171],"previous":[174],"co-segmentation":[175],"methods":[176],"require":[178],"collections":[181],"as":[184],"inference.":[188],"experimental":[190],"results":[191],"various":[193],"benchmarks":[196],"demonstrate":[197],"extracts":[202],"accurately":[205],"robustly,":[207],"suggests":[209],"tasks":[214],"benefit":[216],"inter-frame":[224],"structure":[225],"videos.":[227]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
