{"id":"https://openalex.org/W2902346020","doi":"https://doi.org/10.1109/tip.2018.2884280","title":"Deep Online Video Stabilization With Multi-Grid Warping Transformation Learning","display_name":"Deep Online Video Stabilization With Multi-Grid Warping Transformation Learning","publication_year":2018,"publication_date":"2018-11-30","ids":{"openalex":"https://openalex.org/W2902346020","doi":"https://doi.org/10.1109/tip.2018.2884280","mag":"2902346020","pmid":"https://pubmed.ncbi.nlm.nih.gov/30507533"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2018.2884280","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2018.2884280","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5100415842","display_name":"Miao Wang","orcid":"https://orcid.org/0000-0002-4102-8582"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Miao Wang","raw_affiliation_strings":["Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4102-8582","affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059933272","display_name":"Guo-Ye Yang","orcid":"https://orcid.org/0000-0002-6539-2602"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guo-Ye Yang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103936574","display_name":"Jin-Kun Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin-Kun Lin","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049883689","display_name":"Song\u2013Hai Zhang","orcid":"https://orcid.org/0000-0003-0460-1586"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Song-Hai Zhang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0460-1586","affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022467818","display_name":"Ariel Shamir","orcid":"https://orcid.org/0000-0001-7082-7845"},"institutions":[{"id":"https://openalex.org/I138898306","display_name":"Reichman University","ror":"https://ror.org/01px5cv07","country_code":"IL","type":"education","lineage":["https://openalex.org/I138898306"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Ariel Shamir","raw_affiliation_strings":["Interdisciplinary Center Herzliya, Herzliya, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Interdisciplinary Center Herzliya, Herzliya, Israel","institution_ids":["https://openalex.org/I138898306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078420371","display_name":"Shao-Ping Lu","orcid":"https://orcid.org/0000-0002-8492-0925"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shao-Ping Lu","raw_affiliation_strings":["Nankai University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-8492-0925","affiliations":[{"raw_affiliation_string":"Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037233582","display_name":"Shi\u2010Min Hu","orcid":"https://orcid.org/0000-0001-7507-6542"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shi-Min Hu","raw_affiliation_strings":["Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7507-6542","affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.7701,"has_fulltext":false,"cited_by_count":153,"citation_normalized_percentile":{"value":0.96441751,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"28","issue":"5","first_page":"2283","last_page":"2292"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13579","display_name":"Image and Video Stabilization","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/T13579","display_name":"Image and Video Stabilization","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/T10531","display_name":"Advanced Vision and Imaging","score":0.9861000180244446,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9837999939918518,"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":0.8337265849113464},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7599582672119141},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6636912822723389},{"id":"https://openalex.org/keywords/image-stabilization","display_name":"Image stabilization","score":0.624731183052063},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6082491278648376},{"id":"https://openalex.org/keywords/image-warping","display_name":"Image warping","score":0.5566459894180298},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.5114799737930298},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5066012144088745},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4835910201072693},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4505017399787903},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4229007363319397},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.41110509634017944},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.18679258227348328}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8337265849113464},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7599582672119141},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6636912822723389},{"id":"https://openalex.org/C27402916","wikidata":"https://www.wikidata.org/wiki/Q31009","display_name":"Image stabilization","level":3,"score":0.624731183052063},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6082491278648376},{"id":"https://openalex.org/C157202957","wikidata":"https://www.wikidata.org/wiki/Q1659609","display_name":"Image warping","level":2,"score":0.5566459894180298},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5114799737930298},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5066012144088745},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4835910201072693},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4505017399787903},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4229007363319397},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41110509634017944},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18679258227348328},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2018.2884280","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2018.2884280","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Image Processing","raw_type":"journal-article"},{"id":"pmid:30507533","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30507533","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 image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1978086988","display_name":null,"funder_award_id":"2216/15","funder_id":"https://openalex.org/F4320322252","funder_display_name":"Israel Science Foundation"},{"id":"https://openalex.org/G2569772245","display_name":null,"funder_award_id":"61561146393","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3807797804","display_name":null,"funder_award_id":"2016M601032","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G797295151","display_name":null,"funder_award_id":"61521002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320322252","display_name":"Israel Science Foundation","ror":"https://ror.org/04sazxf24"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W603908379","https://openalex.org/W764651262","https://openalex.org/W1522301498","https://openalex.org/W1677409904","https://openalex.org/W1955055330","https://openalex.org/W1981693481","https://openalex.org/W2021211494","https://openalex.org/W2049092359","https://openalex.org/W2050763094","https://openalex.org/W2057412674","https://openalex.org/W2085261163","https://openalex.org/W2096621047","https://openalex.org/W2108598243","https://openalex.org/W2113018061","https://openalex.org/W2125281025","https://openalex.org/W2156303437","https://openalex.org/W2156598602","https://openalex.org/W2169574628","https://openalex.org/W2194775991","https://openalex.org/W2519006193","https://openalex.org/W2552465644","https://openalex.org/W2558246008","https://openalex.org/W2560435561","https://openalex.org/W2586480386","https://openalex.org/W2591837242","https://openalex.org/W2609107023","https://openalex.org/W2740546229","https://openalex.org/W2949155196","https://openalex.org/W2950813077","https://openalex.org/W2962793481","https://openalex.org/W2963073614","https://openalex.org/W2963547393","https://openalex.org/W6618372016","https://openalex.org/W6637400245","https://openalex.org/W6682864246","https://openalex.org/W6720244596","https://openalex.org/W6726497367"],"related_works":["https://openalex.org/W1670332068","https://openalex.org/W2095618524","https://openalex.org/W2735770592","https://openalex.org/W1971024059","https://openalex.org/W1502062143","https://openalex.org/W4224236531","https://openalex.org/W4291993329","https://openalex.org/W2063177452","https://openalex.org/W2413982977","https://openalex.org/W2268850994"],"abstract_inverted_index":{"Video":[0],"stabilization":[1,19,71,186],"techniques":[2,20],"are":[3],"essential":[4],"for":[5,44,131],"most":[6],"hand-held":[7,170],"captured":[8],"videos":[9,207,215],"due":[10],"to":[11,26,39,182,204],"high-frequency":[12],"shakes.":[13],"Several":[14],"2D,":[15],"2.5D":[16],"and":[17,112,143,162,216],"3D-based":[18],"have":[21],"been":[22,37],"presented":[23],"previously,":[24],"but":[25],"our":[27,176,199],"knowledge,":[28],"no":[29],"solutions":[30],"based":[31,91],"on":[32,92,98],"deep":[33],"neural":[34,62,76,119],"networks":[35],"had":[36],"proposed":[38,177,200],"date.":[40],"The":[41],"main":[42],"reason":[43],"this":[45,65],"omission":[46],"is":[47,202],"shortage":[48],"in":[49,223],"training":[50],"data":[51],"as":[52,54,209],"well":[53],"the":[55,59,109,136,153],"challenge":[56],"of":[57,127,139,159],"modeling":[58],"problem":[60],"using":[61,73,189],"networks.":[63],"In":[64],"paper,":[66],"we":[67,96,155],"present":[68],"a":[69,74,87,125,157,167],"video":[70,164,185],"technique":[72],"convolutional":[75],"network.":[77],"Previous":[78],"works":[79],"usually":[80],"propose":[81],"an":[82],"offline":[83,184],"algorithm":[84],"that":[85,104,175],"smoothes":[86],"holistic":[88],"camera":[89,101,110,141,148],"path":[90,102],"feature":[93,224],"matching.":[94,227],"Instead,":[95],"focus":[97],"low-latency,":[99],"real-time":[100],"smoothing,":[103],"does":[105,113],"not":[106,114],"explicitly":[107],"represent":[108],"path,":[111],"use":[115],"future":[116,190],"frames.":[117],"Our":[118],"network":[120],"model,":[121],"called":[122],"StabNet,":[123],"learns":[124],"set":[126,138],"mesh-grid":[128],"transformations":[129],"progressively":[130],"each":[132],"input":[133],"frame":[134],"from":[135],"previous":[137],"stabalized":[140],"frames,":[142,191],"creates":[144],"stable":[145],"corresponding":[146],"latent":[147],"paths":[149],"implicitly.":[150],"To":[151],"train":[152],"network,":[154],"collect":[156],"dataset":[158],"synchronized":[160],"steady":[161],"unsteady":[163],"pairs":[165],"via":[166],"specially":[168],"designed":[169],"hardware.":[171],"Experimental":[172],"results":[173],"show":[174],"online":[178],"method":[179],"performs":[180],"comparatively":[181],"traditional":[183],"methods":[187,221],"without":[188],"while":[192],"running":[193],"about":[194],"10\u00d7":[195],"faster.":[196],"More":[197],"importantly,":[198],"StabNet":[201],"able":[203],"handle":[205],"low-quality":[206],"such":[208],"night-scene":[210],"videos,":[211,213,218],"watermarked":[212],"blurry":[214],"noisy":[217],"where":[219],"existing":[220],"fail":[222],"extraction":[225],"or":[226]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":28},{"year":2024,"cited_by_count":27},{"year":2023,"cited_by_count":29},{"year":2022,"cited_by_count":19},{"year":2021,"cited_by_count":22},{"year":2020,"cited_by_count":15},{"year":2019,"cited_by_count":8}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}