{"id":"https://openalex.org/W3010252951","doi":"https://doi.org/10.1109/wacv45572.2020.9093294","title":"RPM-Net: Robust Pixel-Level Matching Networks for Self-Supervised Video Object Segmentation","display_name":"RPM-Net: Robust Pixel-Level Matching Networks for Self-Supervised Video Object Segmentation","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W3010252951","doi":"https://doi.org/10.1109/wacv45572.2020.9093294","mag":"3010252951"},"language":"en","primary_location":{"id":"doi:10.1109/wacv45572.2020.9093294","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093294","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101992968","display_name":"Youngeun Kim","orcid":"https://orcid.org/0000-0002-9404-6936"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]},{"id":"https://openalex.org/I4210099236","display_name":"Kootenay Association for Science & Technology","ror":"https://ror.org/011pv9p44","country_code":"CA","type":"nonprofit","lineage":["https://openalex.org/I4210099236"]}],"countries":["CA","KR"],"is_corresponding":false,"raw_author_name":"Youngeun Kim","raw_affiliation_strings":["KAIST"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KAIST","institution_ids":["https://openalex.org/I157485424","https://openalex.org/I4210099236"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025534005","display_name":"Seokeon Choi","orcid":"https://orcid.org/0000-0002-1695-5894"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]},{"id":"https://openalex.org/I4210099236","display_name":"Kootenay Association for Science & Technology","ror":"https://ror.org/011pv9p44","country_code":"CA","type":"nonprofit","lineage":["https://openalex.org/I4210099236"]}],"countries":["CA","KR"],"is_corresponding":false,"raw_author_name":"Seokeon Choi","raw_affiliation_strings":["KAIST"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KAIST","institution_ids":["https://openalex.org/I157485424","https://openalex.org/I4210099236"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028450684","display_name":"Hankyeol Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]},{"id":"https://openalex.org/I4210099236","display_name":"Kootenay Association for Science & Technology","ror":"https://ror.org/011pv9p44","country_code":"CA","type":"nonprofit","lineage":["https://openalex.org/I4210099236"]}],"countries":["CA","KR"],"is_corresponding":false,"raw_author_name":"Hankyeol Lee","raw_affiliation_strings":["KAIST"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KAIST","institution_ids":["https://openalex.org/I157485424","https://openalex.org/I4210099236"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100657826","display_name":"Taekyung Kim","orcid":"https://orcid.org/0000-0001-7401-098X"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]},{"id":"https://openalex.org/I4210099236","display_name":"Kootenay Association for Science & Technology","ror":"https://ror.org/011pv9p44","country_code":"CA","type":"nonprofit","lineage":["https://openalex.org/I4210099236"]}],"countries":["CA","KR"],"is_corresponding":false,"raw_author_name":"Taekyung Kim","raw_affiliation_strings":["KAIST"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KAIST","institution_ids":["https://openalex.org/I157485424","https://openalex.org/I4210099236"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069759184","display_name":"Changick Kim","orcid":"https://orcid.org/0000-0001-9323-8488"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]},{"id":"https://openalex.org/I4210099236","display_name":"Kootenay Association for Science & Technology","ror":"https://ror.org/011pv9p44","country_code":"CA","type":"nonprofit","lineage":["https://openalex.org/I4210099236"]}],"countries":["CA","KR"],"is_corresponding":false,"raw_author_name":"Changick Kim","raw_affiliation_strings":["KAIST"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KAIST","institution_ids":["https://openalex.org/I157485424","https://openalex.org/I4210099236"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4272,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.66948171,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2046","last_page":"2054"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":1.0,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":1.0,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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":0.9997000098228455,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8368357419967651},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7629317045211792},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7128428220748901},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6885733604431152},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.653373122215271},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6366809606552124},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4855465590953827},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.48541030287742615},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4417245090007782},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42573603987693787},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4133400321006775},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15496301651000977},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.135939359664917}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8368357419967651},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7629317045211792},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7128428220748901},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6885733604431152},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.653373122215271},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6366809606552124},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4855465590953827},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.48541030287742615},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4417245090007782},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42573603987693787},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4133400321006775},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15496301651000977},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.135939359664917},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wacv45572.2020.9093294","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093294","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W65124300","https://openalex.org/W589665618","https://openalex.org/W1555148682","https://openalex.org/W1903029394","https://openalex.org/W1954128991","https://openalex.org/W1973054923","https://openalex.org/W2138682569","https://openalex.org/W2161236525","https://openalex.org/W2412782625","https://openalex.org/W2462481369","https://openalex.org/W2470139095","https://openalex.org/W2560474170","https://openalex.org/W2562457735","https://openalex.org/W2564998703","https://openalex.org/W2601564443","https://openalex.org/W2605229288","https://openalex.org/W2610147486","https://openalex.org/W2737035197","https://openalex.org/W2750515003","https://openalex.org/W2759011671","https://openalex.org/W2766386624","https://openalex.org/W2768489488","https://openalex.org/W2769602411","https://openalex.org/W2787709582","https://openalex.org/W2798441772","https://openalex.org/W2798823518","https://openalex.org/W2799157347","https://openalex.org/W2799239273","https://openalex.org/W2799256316","https://openalex.org/W2799262584","https://openalex.org/W2883955876","https://openalex.org/W2889658408","https://openalex.org/W2890447039","https://openalex.org/W2890853604","https://openalex.org/W2891491194","https://openalex.org/W2916743882","https://openalex.org/W2921676720","https://openalex.org/W2952793010","https://openalex.org/W2962825871","https://openalex.org/W2963195262","https://openalex.org/W2963253279","https://openalex.org/W2963426332","https://openalex.org/W2963481481","https://openalex.org/W2963548592","https://openalex.org/W2963857746","https://openalex.org/W2964040697","https://openalex.org/W2967291630","https://openalex.org/W6617526114","https://openalex.org/W6633204899","https://openalex.org/W6743811873","https://openalex.org/W6745122469","https://openalex.org/W6753318354","https://openalex.org/W6753986461","https://openalex.org/W6754033419"],"related_works":["https://openalex.org/W2517104666","https://openalex.org/W2541791370","https://openalex.org/W2005437358","https://openalex.org/W2035976912","https://openalex.org/W1669643531","https://openalex.org/W2337415362","https://openalex.org/W2008656436","https://openalex.org/W2134924024","https://openalex.org/W2023558673","https://openalex.org/W4312857205"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,17,133,157],"introduce":[4],"a":[5,24],"self-supervised":[6,152,164],"approach":[7],"for":[8,41],"video":[9,120,153,167],"object":[10,121,154,168],"segmentation":[11,122,169],"without":[12],"human":[13],"labeled":[14],"data.":[15],"Specifically,":[16],"present":[18],"Robust":[19],"Pixel-level":[20],"Matching":[21],"Networks":[22],"(RPM-Net),":[23],"novel":[25],"deep":[26],"architecture":[27],"that":[28,108],"matches":[29,72],"pixels":[30,73],"between":[31,74,163],"adjacent":[32],"frames,":[33],"using":[34,87],"only":[35],"color":[36],"information":[37],"from":[38],"unlabeled":[39],"videos":[40],"training.":[42],"Technically,":[43],"RPM-Net":[44],"can":[45],"be":[46],"separated":[47],"in":[48,101,119],"two":[49],"main":[50],"modules.":[51],"The":[52],"embedding":[53,62,82],"module":[54,67,92],"first":[55],"projects":[56],"input":[57],"images":[58],"into":[59],"high":[60],"dimensional":[61],"space.":[63],"Then":[64],"the":[65,81,109,114,160],"matching":[66,91],"with":[68],"deformable":[69,88,94],"convolution":[70,95],"layers":[71],"reference":[75],"and":[76,130,145,147,165],"target":[77],"frames":[78],"based":[79],"on":[80,98,138,151,173],"features.":[83],"Unlike":[84],"previous":[85],"methods":[86],"convolution,":[89],"our":[90],"adopts":[93],"to":[96,116],"focus":[97],"similar":[99],"features":[100],"spatio-temporally":[102],"neighboring":[103],"pixels.":[104],"Our":[105],"experiments":[106,137],"show":[107],"selective":[110],"feature":[111],"sampling":[112],"improves":[113],"robustness":[115],"challenging":[117],"problems":[118],"such":[123],"as":[124],"camera":[125],"shake,":[126],"fast":[127],"motion,":[128],"deformation,":[129],"occlusion.":[131],"Also,":[132],"carry":[134],"out":[135],"comprehensive":[136],"three":[139],"public":[140],"datasets":[141],"(i.e.,":[142],"DAVIS-2017,":[143],"SegTrack-v2,":[144],"Youtube-Objects)":[146],"achieve":[148],"state-of-the-art":[149],"performance":[150,161],"segmentation.":[155],"Moreover,":[156],"significantly":[158],"reduce":[159],"gap":[162],"fully-supervised":[166],"(41.0%":[170],"vs.":[171],"52.5%":[172],"DAVIS-2017":[174],"validation":[175],"set).":[176]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
