{"id":"https://openalex.org/W7148326528","doi":"https://doi.org/10.1109/tpami.2026.3680159","title":"Learning Continuous Spatiotemporal Implicit Neural Fields for Unsupervised Video Denoising","display_name":"Learning Continuous Spatiotemporal Implicit Neural Fields for Unsupervised Video Denoising","publication_year":2026,"publication_date":"2026-04-02","ids":{"openalex":"https://openalex.org/W7148326528","doi":"https://doi.org/10.1109/tpami.2026.3680159","pmid":"https://pubmed.ncbi.nlm.nih.gov/41926400"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2026.3680159","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2026.3680159","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":["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/A5059112338","display_name":"Xiaowan Hu","orcid":"https://orcid.org/0000-0001-7364-4489"},"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":"Xiaowan Hu","raw_affiliation_strings":["School of Electronic and Information Engineering, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7364-4489","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132734464","display_name":"Henan Liu","orcid":null},"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":"Henan Liu","raw_affiliation_strings":["School of Electronic and Information Engineering, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0003-2141-5256","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101582578","display_name":"Ce Zheng","orcid":"https://orcid.org/0009-0001-3140-6236"},"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":"Ce Zheng","raw_affiliation_strings":["School of Electronic and Information Engineering, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0001-3140-6236","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006533393","display_name":"Xiao Li","orcid":"https://orcid.org/0000-0002-3577-7915"},"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":"Xinyang Li","raw_affiliation_strings":["College of AI, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-3880-5448","affiliations":[{"raw_affiliation_string":"College of AI, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5132821850","display_name":"Mai Xu","orcid":null},"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":"Mai Xu","raw_affiliation_strings":["School of Electronic and Information Engineering, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0277-3301","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28168005,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"48","issue":"8","first_page":"9415","last_page":"9433"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.6830999851226807,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.6830999851226807,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.05660000070929527,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.024000000208616257,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.590499997138977},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4724999964237213},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.47029998898506165},{"id":"https://openalex.org/keywords/video-denoising","display_name":"Video denoising","score":0.4422999918460846},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.40799999237060547},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.3598000109195709},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3357999920845032}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7745000123977661},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.754800021648407},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.590499997138977},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4756999909877777},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4724999964237213},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.47029998898506165},{"id":"https://openalex.org/C30814859","wikidata":"https://www.wikidata.org/wiki/Q4119603","display_name":"Video denoising","level":5,"score":0.4422999918460846},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.40799999237060547},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.3598000109195709},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3357999920845032},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.32409998774528503},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.31790000200271606},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.295199990272522},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.28780001401901245},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.27790001034736633},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.26910001039505005},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.25369998812675476},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.25200000405311584}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2026.3680159","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2026.3680159","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:41926400","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41926400","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":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.45502805709838867,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1435134057","display_name":null,"funder_award_id":"62501027","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3844525474","display_name":null,"funder_award_id":"32571275","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3864562958","display_name":null,"funder_award_id":"62450131","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4414130214","display_name":null,"funder_award_id":"62206011","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6069380152","display_name":null,"funder_award_id":"L223021","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"},{"id":"https://openalex.org/G6127711580","display_name":null,"funder_award_id":"62231002","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/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1965221572","https://openalex.org/W2056370875","https://openalex.org/W2097073572","https://openalex.org/W2153663612","https://openalex.org/W2601564443","https://openalex.org/W2902857081","https://openalex.org/W2953334512","https://openalex.org/W2963031226","https://openalex.org/W2963782415","https://openalex.org/W2965669158","https://openalex.org/W2967656728","https://openalex.org/W3034233131","https://openalex.org/W3034239311","https://openalex.org/W3035051775","https://openalex.org/W3119800349","https://openalex.org/W3128923825","https://openalex.org/W3137474318","https://openalex.org/W3157035436","https://openalex.org/W3174829522","https://openalex.org/W3174865552","https://openalex.org/W3176148916","https://openalex.org/W3178981087","https://openalex.org/W3195625084","https://openalex.org/W4200150166","https://openalex.org/W4214617338","https://openalex.org/W4297243218","https://openalex.org/W4312371645","https://openalex.org/W4312933730","https://openalex.org/W4312938066","https://openalex.org/W4382240324","https://openalex.org/W4387967952","https://openalex.org/W4388625761","https://openalex.org/W4389574259","https://openalex.org/W4392543517","https://openalex.org/W4396982422","https://openalex.org/W4402727237","https://openalex.org/W4403209965","https://openalex.org/W4403878297","https://openalex.org/W4409310914","https://openalex.org/W4409367435","https://openalex.org/W4409370186","https://openalex.org/W7133203186","https://openalex.org/W7133207340","https://openalex.org/W7133233038","https://openalex.org/W7160048515"],"related_works":[],"abstract_inverted_index":{"Video":[0],"denoising":[1,76,95],"is":[2],"fundamental":[3],"to":[4,61,116],"low-level":[5],"vision":[6],"and":[7,19,28,56,64,177,191],"real-world":[8],"imaging,":[9],"yet":[10],"existing":[11],"self-supervised":[12,74],"methods":[13],"remain":[14],"fragile":[15],"under":[16],"severe":[17],"noise":[18],"complex":[20],"motion.":[21],"Most":[22],"approaches":[23],"still":[24],"rely":[25],"on":[26,52,85,175,189],"spatially":[27],"temporally":[29],"discrete":[30],"grid-based":[31],"representations:":[32],"blind-spot":[33,109],"networks":[34],"enforce":[35],"J-invariance":[36],"by":[37,72],"masking":[38],"center":[39],"pixels":[40],"with":[41,97,135],"a":[42,79,92,98,108,144,159],"limited":[43],"receptive":[44],"field,":[45,163],"while":[46,143],"recurrent":[47],"models":[48],"build":[49],"temporal":[50,129,133],"dependencies":[51],"discretized":[53,155],"frame":[54],"sequences":[55],"noise-sensitive":[57],"optical":[58,171],"flow,":[59],"leading":[60],"error":[62],"accumulation":[63],"motion":[65,139],"artifacts.":[66],"We":[67],"address":[68],"this":[69],"model":[70,96],"bottleneck":[71],"reformulating":[73],"video":[75,94,156,180,194],"as":[77],"learning":[78],"continuous":[80,160],"spatiotemporal":[81,99,161],"implicit":[82,87,100,110,132],"field.":[83],"Building":[84],"coordinate-based":[86],"neural":[88,101],"representations,":[89,118],"we":[90],"propose":[91],"unified":[93],"field":[102,112],"(SINF).":[103],"In":[104,127],"the":[105,128],"spatial":[106,111,146],"domain,":[107,130],"maps":[113],"coordinates":[114],"directly":[115],"pixel-level":[117],"enabling":[119,164],"globally":[120],"informed":[121],"texture":[122],"recovery":[123],"beyond":[124],"receptive-field":[125],"limits.":[126],"an":[131],"embedding":[134],"periodic":[136],"activations":[137],"encodes":[138],"continuously":[140],"over":[141],"time,":[142],"time-aware":[145],"graph":[147],"module":[148],"refines":[149],"cross-frame":[150],"alignment.":[151],"Together,":[152],"SINF":[153,185],"remodels":[154],"signals":[157],"into":[158],"intensity":[162],"more":[165],"robust":[166],"pixel-wise":[167],"associations":[168],"than":[169],"coarse":[170],"flow.":[172],"Extensive":[173],"experiments":[174],"synthetic":[176,190],"real":[178,192],"noisy":[179,193],"benchmarks":[181],"demonstrate":[182],"that":[183],"our":[184],"achieves":[186],"state-of-the-art":[187],"performance":[188],"benchmarks.":[195]},"counts_by_year":[],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2026-04-03T00:00:00"}