{"id":"https://openalex.org/W7123754571","doi":"https://doi.org/10.1109/tip.2026.3651963","title":"Blind Inversion Using Latent Diffusion Priors","display_name":"Blind Inversion Using Latent Diffusion Priors","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7123754571","doi":"https://doi.org/10.1109/tip.2026.3651963","pmid":"https://pubmed.ncbi.nlm.nih.gov/41528900"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2026.3651963","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3651963","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/A5061227106","display_name":"Bai Wj","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weimin Bai","raw_affiliation_strings":["Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100647472","display_name":"Siyi Chen","orcid":"https://orcid.org/0000-0002-3304-4486"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siyi Chen","raw_affiliation_strings":["School of Physics, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Physics, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010254581","display_name":"Wenzheng Chen","orcid":"https://orcid.org/0009-0008-5623-1963"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenzheng Chen","raw_affiliation_strings":["Wangxuan Institute of Computer Technology, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Wangxuan Institute of Computer Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5104343650","display_name":"He Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I4210127501","display_name":"National Center of Biomedical Analysis","ror":"https://ror.org/03k3bq214","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210127501"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"He Sun","raw_affiliation_strings":["National Biomedical Imaging Center, Beijing, China"],"affiliations":[{"raw_affiliation_string":"National Biomedical Imaging Center, Beijing, China","institution_ids":["https://openalex.org/I4210127501"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5061227106"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18175153,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"35","issue":null,"first_page":"1582","last_page":"1594"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.49480000138282776,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.49480000138282776,"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":0.1177000030875206,"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":0.06939999759197235,"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/prior-probability","display_name":"Prior probability","score":0.8626000285148621},{"id":"https://openalex.org/keywords/deblurring","display_name":"Deblurring","score":0.857699990272522},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.6675000190734863},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.4498000144958496},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.44190001487731934},{"id":"https://openalex.org/keywords/blind-deconvolution","display_name":"Blind deconvolution","score":0.41350001096725464},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4090999960899353},{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.40860000252723694},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.3952000141143799}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.8626000285148621},{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.857699990272522},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.6675000190734863},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5306000113487244},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.515500009059906},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.4498000144958496},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.44279998540878296},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.44190001487731934},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42329999804496765},{"id":"https://openalex.org/C30044814","wikidata":"https://www.wikidata.org/wiki/Q11334452","display_name":"Blind deconvolution","level":3,"score":0.41350001096725464},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4090999960899353},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.40860000252723694},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3995000123977661},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.3952000141143799},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.3944000005722046},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.36469998955726624},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.361299991607666},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3287999927997589},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.30399999022483826},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.29840001463890076},{"id":"https://openalex.org/C174576160","wikidata":"https://www.wikidata.org/wiki/Q1183700","display_name":"Deconvolution","level":2,"score":0.2930999994277954},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.28940001130104065},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28780001401901245},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C205372313","wikidata":"https://www.wikidata.org/wiki/Q355645","display_name":"Latent image","level":3,"score":0.2597000002861023},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.25589999556541443},{"id":"https://openalex.org/C203504353","wikidata":"https://www.wikidata.org/wiki/Q4765461","display_name":"Anisotropic diffusion","level":3,"score":0.2517000138759613}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2026.3651963","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3651963","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:41528900","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41528900","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":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.4188022017478943}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W183071939","https://openalex.org/W1895439721","https://openalex.org/W1973567017","https://openalex.org/W1996726072","https://openalex.org/W2015810892","https://openalex.org/W2032506791","https://openalex.org/W2044810215","https://openalex.org/W2108598243","https://openalex.org/W2109357213","https://openalex.org/W2166887721","https://openalex.org/W2295936755","https://openalex.org/W2331376995","https://openalex.org/W2465552163","https://openalex.org/W2508457857","https://openalex.org/W2574952845","https://openalex.org/W2759428153","https://openalex.org/W2762685704","https://openalex.org/W2787255625","https://openalex.org/W2964013315","https://openalex.org/W2982795046","https://openalex.org/W3002289736","https://openalex.org/W3003301247","https://openalex.org/W3024020995","https://openalex.org/W3034724715","https://openalex.org/W3109585842","https://openalex.org/W3167568784","https://openalex.org/W3170697543","https://openalex.org/W3205399766","https://openalex.org/W3216476011","https://openalex.org/W4206375146","https://openalex.org/W4211119455","https://openalex.org/W4239863109","https://openalex.org/W4312293341","https://openalex.org/W4312894520","https://openalex.org/W4312933868","https://openalex.org/W4385318467","https://openalex.org/W4386065784","https://openalex.org/W4386065887","https://openalex.org/W4386071957","https://openalex.org/W4386075660","https://openalex.org/W4386075894","https://openalex.org/W4386080645","https://openalex.org/W4386437472","https://openalex.org/W4390872797","https://openalex.org/W4390873331","https://openalex.org/W4390873542","https://openalex.org/W4390874424","https://openalex.org/W4403002842"],"related_works":[],"abstract_inverted_index":{"Diffusion":[0],"models":[1,60],"have":[2],"emerged":[3],"as":[4],"powerful":[5,57],"tools":[6],"for":[7,138],"solving":[8,90],"inverse":[9,77,92,162,177],"problems":[10,78,93],"due":[11],"to":[12,16],"their":[13,32],"exceptional":[14],"ability":[15],"model":[17],"complex":[18],"prior":[19,200],"distributions.":[20],"However,":[21],"existing":[22],"methods":[23],"predominantly":[24],"assume":[25],"known":[26,114],"forward":[27,115,123],"operators":[28,40],"(i.e.,":[29],"non-blind),":[30],"limiting":[31],"applicability":[33],"in":[34,174],"practical":[35],"settings":[36],"where":[37],"acquiring":[38],"such":[39],"is":[41,89],"costly.":[42],"Additionally,":[43,130],"many":[44],"current":[45],"approaches":[46],"rely":[47],"on":[48,126,184],"pixel-space":[49],"diffusion":[50,59,81],"models,":[51],"leaving":[52],"the":[53,84,101,119,122,127],"potential":[54],"of":[55,86],"more":[56,74,145],"latent":[58,80],"(LDMs)":[61],"underexplored.":[62],"In":[63],"this":[64],"paper,":[65],"we":[66,131],"introduce":[67],"LatentDEM,":[68],"an":[69,95],"innovative":[70],"technique":[71],"that":[72],"addresses":[73],"challenging":[75],"blind":[76,91,149,187],"using":[79,109],"priors.":[82],"At":[83],"core":[85],"our":[87],"method":[88],"within":[94],"iterative":[96],"Expectation-Maximization":[97],"(EM)":[98],"framework:":[99],"(1)":[100],"E-step":[102],"recovers":[103],"clean":[104],"images":[105],"from":[106],"corrupted":[107],"observations":[108],"LDM":[110,139],"priors":[111,140],"and":[112,117,141,147,160,189],"a":[113,153],"model,":[116],"(2)":[118],"M-step":[120],"estimates":[121],"operator":[124],"based":[125],"recovered":[128],"images.":[129],"propose":[132],"two":[133],"novel":[134],"optimization":[135],"techniques":[136],"tailored":[137],"EM":[142],"frameworks,":[143],"yielding":[144],"accurate":[146],"efficient":[148],"inversion":[150],"results.":[151],"As":[152],"general":[154],"framework,":[155],"LatentDEM":[156],"supports":[157],"both":[158],"linear":[159],"non-linear":[161,175],"problems.":[163,179],"Beyond":[164],"common":[165],"2D":[166,186],"image":[167],"restoration":[168],"tasks,":[169,194],"it":[170],"enables":[171],"new":[172],"capabilities":[173],"3D":[176,190],"rendering":[178],"We":[180],"validate":[181],"LatentDEM's":[182],"performance":[183],"representative":[185],"deblurring":[188],"pose-free":[191],"sparse-view":[192],"reconstruction":[193],"demonstrating":[195],"its":[196],"superior":[197],"efficacy":[198],"over":[199],"arts.":[201],"The":[202],"project":[203],"page":[204],"can":[205],"be":[206],"found":[207],"at":[208],"https://ai4imaging.github.io/latentdem/.":[209]},"counts_by_year":[],"updated_date":"2026-02-20T06:14:18.993340","created_date":"2026-01-14T00:00:00"}