{"id":"https://openalex.org/W7160993731","doi":"https://doi.org/10.48550/arxiv.2605.11628","title":"Single-Shot HDR Recovery via a Video Diffusion Prior","display_name":"Single-Shot HDR Recovery via a Video Diffusion Prior","publication_year":2026,"publication_date":"2026-05-12","ids":{"openalex":"https://openalex.org/W7160993731","doi":"https://doi.org/10.48550/arxiv.2605.11628"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.11628","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.11628","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.11628","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046046825","display_name":"Chinmay Talegaonkar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Talegaonkar, Chinmay","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136088587","display_name":"Jinshi He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Jinshi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136006180","display_name":"Christopher McKenna","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"McKenna, Christopher","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5089343382","display_name":"Nicholas Antipa","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Antipa, Nicholas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.849399983882904,"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/T11019","display_name":"Image Enhancement Techniques","score":0.849399983882904,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.061500001698732376,"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":0.028999999165534973,"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/interpretability","display_name":"Interpretability","score":0.6266000270843506},{"id":"https://openalex.org/keywords/high-dynamic-range","display_name":"High dynamic range","score":0.6115000247955322},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.5289999842643738},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5048999786376953},{"id":"https://openalex.org/keywords/hallucinating","display_name":"Hallucinating","score":0.46309998631477356},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.4609000086784363},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4034000039100647},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.3799999952316284},{"id":"https://openalex.org/keywords/high-fidelity","display_name":"High fidelity","score":0.353300005197525}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7501999735832214},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7099000215530396},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6373000144958496},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6266000270843506},{"id":"https://openalex.org/C2780056265","wikidata":"https://www.wikidata.org/wiki/Q106239881","display_name":"High dynamic range","level":3,"score":0.6115000247955322},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.5289999842643738},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5048999786376953},{"id":"https://openalex.org/C2911011789","wikidata":"https://www.wikidata.org/wiki/Q130741","display_name":"Hallucinating","level":2,"score":0.46309998631477356},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.4609000086784363},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4034000039100647},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3799999952316284},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.353300005197525},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.32899999618530273},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.3285999894142151},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3264999985694885},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.32330000400543213},{"id":"https://openalex.org/C29081049","wikidata":"https://www.wikidata.org/wiki/Q1364242","display_name":"Image stitching","level":2,"score":0.3224000036716461},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.32030001282691956},{"id":"https://openalex.org/C11727466","wikidata":"https://www.wikidata.org/wiki/Q1628157","display_name":"Inpainting","level":3,"score":0.3142000138759613},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.29980000853538513},{"id":"https://openalex.org/C2781399445","wikidata":"https://www.wikidata.org/wiki/Q309254","display_name":"High-dynamic-range imaging","level":4,"score":0.296099990606308},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.29330000281333923},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.2930999994277954},{"id":"https://openalex.org/C8641274","wikidata":"https://www.wikidata.org/wiki/Q1030958","display_name":"Tone mapping","level":4,"score":0.2858000099658966},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.28119999170303345},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2572000026702881}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.11628","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.11628","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.11628","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.11628","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recent":[0],"generative":[1,150],"methods":[2],"for":[3,130],"single-shot":[4,49],"high":[5,141],"dynamic":[6,80],"range":[7,81],"(HDR)":[8],"image":[9,87,190,196],"reconstruction":[10,51,158,191],"show":[11,176],"promising":[12],"results,":[13],"but":[14],"often":[15],"struggle":[16],"with":[17,140,152],"preserving":[18],"fidelity":[19],"to":[20,28,71,188],"the":[21,39,58,114,122,128],"input":[22,142],"image.":[23,42,64],"They":[24],"require":[25],"separate":[26,131],"models":[27,132],"handle":[29],"highlights":[30],"and":[31,56,102,118,136,182],"shadows,":[32],"or":[33],"sacrifice":[34],"interpretability":[35],"by":[36,47,93],"directly":[37,106],"predicting":[38],"final":[40,123],"HDR":[41,50,63,109,138,187],"We":[43,65,84],"address":[44],"these":[45],"limitations":[46],"re-casting":[48],"as":[52,194],"conditional":[53],"video":[54,68],"generation":[55,181],"fusing":[57],"generated":[59],"frames":[60],"into":[61,121],"an":[62,73,108],"finetune":[66],"a":[67,78,94,199],"diffusion":[69],"model":[70,154],"generate":[72],"exposure":[74,116,134],"bracket,":[75],"conditioned":[76],"on":[77,156],"low":[79],"(LDR)":[82],"input.":[83,202],"fuse":[85],"this":[86,178],"bracket":[88],"using":[89],"per-pixel":[90],"weights":[91],"predicted":[92],"light-weight":[95],"UNet.":[96],"This":[97],"formulation":[98],"is":[99],"simple,":[100],"interpretable,":[101],"effective.":[103],"Rather":[104],"than":[105],"hallucinating":[107],"image,":[110],"it":[111,120],"explicitly":[112],"reconstructs":[113],"intermediate":[115],"stack":[117],"fuses":[119],"output.":[124],"Our":[125],"method":[126],"eliminates":[127],"need":[129],"across":[133],"regimes":[135],"produces":[137],"reconstructions":[139],"fidelity.":[143],"On":[144],"quantitative":[145],"benchmarks,":[146],"we":[147,175],"outperform":[148],"state-of-the-art":[149],"baselines":[151],"comparable":[153],"capacity":[155],"several":[157],"metrics.":[159],"Human":[160],"evaluators":[161],"further":[162],"prefer":[163],"our":[164],"results":[165],"in":[166],"72%":[167],"of":[168],"pairwise":[169],"comparisons":[170],"against":[171],"existing":[172],"methods.":[173],"Finally,":[174],"that":[177],"input-conditioned":[179],"sequence":[180],"fusion":[183],"framework":[184],"extends":[185],"beyond":[186],"other":[189],"tasks,":[192],"such":[193],"all-in-focus":[195],"recovery":[197],"from":[198],"single":[200],"defocus-blurred":[201]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-14T00:00:00"}
