{"id":"https://openalex.org/W4403791753","doi":"https://doi.org/10.1145/3664647.3680853","title":"LD-BFR: Vector-Quantization-Based Face Restoration Model with Latent Diffusion Enhancement","display_name":"LD-BFR: Vector-Quantization-Based Face Restoration Model with Latent Diffusion Enhancement","publication_year":2024,"publication_date":"2024-10-26","ids":{"openalex":"https://openalex.org/W4403791753","doi":"https://doi.org/10.1145/3664647.3680853"},"language":"en","primary_location":{"id":"doi:10.1145/3664647.3680853","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3680853","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","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":null,"display_name":"Yuzhen Du","orcid":"https://orcid.org/0009-0000-0709-8811"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuzhen Du","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0000-0709-8811","affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103325900","display_name":"Teng Hu","orcid":"https://orcid.org/0009-0008-1247-5931"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Teng Hu","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0008-1247-5931","affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054879013","display_name":"Ran Yi","orcid":"https://orcid.org/0000-0003-1858-3358"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ran Yi","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-1858-3358","affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084218062","display_name":"Lizhuang Ma","orcid":"https://orcid.org/0000-0003-1653-4341"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lizhuang Ma","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-1653-4341","affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2852","last_page":"2860"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9970999956130981,"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":0.9970999956130981,"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/T11448","display_name":"Face recognition and analysis","score":0.9922000169754028,"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":0.9908000230789185,"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/vector-quantization","display_name":"Vector quantization","score":0.5795788764953613},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.5707710981369019},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5472358465194702},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5117073059082031},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47242724895477295},{"id":"https://openalex.org/keywords/learning-vector-quantization","display_name":"Learning vector quantization","score":0.4642876386642456},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.42677438259124756},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42048782110214233},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34662187099456787},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1646108627319336}],"concepts":[{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.5795788764953613},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.5707710981369019},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5472358465194702},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5117073059082031},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47242724895477295},{"id":"https://openalex.org/C40567965","wikidata":"https://www.wikidata.org/wiki/Q1820283","display_name":"Learning vector quantization","level":3,"score":0.4642876386642456},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.42677438259124756},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42048782110214233},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34662187099456787},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1646108627319336},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3664647.3680853","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3680853","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2895542678","https://openalex.org/W2955625300","https://openalex.org/W2962770929","https://openalex.org/W2963743395","https://openalex.org/W3035574324","https://openalex.org/W3036167779","https://openalex.org/W3106746951","https://openalex.org/W3167297682","https://openalex.org/W3174166237","https://openalex.org/W3180355996","https://openalex.org/W3180391059","https://openalex.org/W3191805365","https://openalex.org/W3208549483","https://openalex.org/W4283373024","https://openalex.org/W4285307305","https://openalex.org/W4312400623","https://openalex.org/W4312933868","https://openalex.org/W4312971930","https://openalex.org/W4390873198","https://openalex.org/W6779823529"],"related_works":["https://openalex.org/W2100968651","https://openalex.org/W4243803532","https://openalex.org/W2352648934","https://openalex.org/W4230688072","https://openalex.org/W1915693853","https://openalex.org/W1530525041","https://openalex.org/W2378212145","https://openalex.org/W2798892016","https://openalex.org/W2100492357","https://openalex.org/W2202992072"],"abstract_inverted_index":{"Blind":[0],"Face":[1],"Restoration":[2],"(BFR)":[3],"aims":[4],"to":[5,48,65,96,121,149],"restore":[6,51,97],"high-quality":[7,110,123,135,144],"face":[8],"images":[9,12,52,125],"from":[10],"low-quality":[11],"with":[13,57,126],"unknown":[14],"degradation.":[15],"Previous":[16],"GAN-based":[17],"or":[18],"ViT-based":[19],"methods":[20,37],"have":[21,26],"shown":[22],"promising":[23],"results,":[24],"but":[25],"identity":[27],"details":[28],"loss":[29],"once":[30],"degradation":[31,55],"is":[32,174],"severe;":[33],"while":[34],"recent":[35],"diffusion-based":[36,68],"work":[38],"on":[39],"image":[40,100],"level":[41],"and":[42,60,85],"take":[43],"a":[44,73,91,102,147],"lot":[45],"of":[46,82,132,153,164],"time":[47,63],"infer.":[49],"To":[50],"in":[53,101,116],"any":[54],"types":[56],"high":[58],"quality":[59],"spend":[61],"less":[62],"compared":[64],"the":[66,80,98,108,114,130,133,143,151,161,168],"classic":[67],"method,":[69],"we":[70,89,106],"propose":[71],"LD-BFR,":[72],"novel":[74],"BFR":[75,170],"framework":[76],"that":[77],"integrates":[78],"both":[79],"strengths":[81],"vector":[83,94],"quantization":[84,95],"latent":[86,118,155],"diffusion.":[87],"First,":[88],"employ":[90],"Dual":[92],"Cross-Attention":[93],"degraded":[99],"global":[103],"manner.":[104],"Then":[105],"utilize":[107],"restored":[109,124],"quantized":[111],"feature":[112,136,145],"as":[113,146],"guidance":[115],"our":[117,139,154,165],"diffusion":[119,156],"model":[120,166],"generate":[122],"rich":[127],"details.":[128],"With":[129],"help":[131],"proposed":[134],"injection":[137],"module,":[138],"LD-BFR":[140],"effectively":[141],"injects":[142],"condition":[148],"guide":[150],"generation":[152],"model.":[157],"Extensive":[158],"experiments":[159],"demonstrate":[160],"superior":[162],"performance":[163],"over":[167],"SOTA":[169],"methods.":[171],"The":[172],"code":[173],"available":[175],"at:":[176],"https://github.com/YuzhenD/LD-BFR.git":[177]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}