{"id":"https://openalex.org/W4417125386","doi":"https://doi.org/10.1145/3757377.3763961","title":"QMF-Blend: Quantized Matrix Factorization for Efficient Blendshape Compression","display_name":"QMF-Blend: Quantized Matrix Factorization for Efficient Blendshape Compression","publication_year":2025,"publication_date":"2025-12-08","ids":{"openalex":"https://openalex.org/W4417125386","doi":"https://doi.org/10.1145/3757377.3763961"},"language":null,"primary_location":{"id":"doi:10.1145/3757377.3763961","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3757377.3763961","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the SIGGRAPH Asia 2025 Conference Papers","raw_type":"proceedings-article"},"type":"article","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":"https://openalex.org/A5120723897","display_name":"Roman Fedotov","orcid":"https://orcid.org/0009-0001-9606-7810"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Roman Fedotov","raw_affiliation_strings":["Meta Reality Labs, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"Meta Reality Labs, Sydney, Australia","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008262518","display_name":"Brian Budge","orcid":"https://orcid.org/0009-0005-9305-3260"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brian Budge","raw_affiliation_strings":["Meta Reality Labs, Redmond, USA"],"affiliations":[{"raw_affiliation_string":"Meta Reality Labs, Redmond, USA","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5104420733","display_name":"Ladislav Kavan","orcid":"https://orcid.org/0000-0001-8549-0878"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ladislav Kavan","raw_affiliation_strings":["Meta Reality Labs, Zurich, Switzerland"],"affiliations":[{"raw_affiliation_string":"Meta Reality Labs, Zurich, Switzerland","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5120723897"],"corresponding_institution_ids":["https://openalex.org/I4210128585"],"apc_list":null,"apc_paid":null,"fwci":1.428,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.87644776,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9613999724388123,"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/T11448","display_name":"Face recognition and analysis","score":0.9613999724388123,"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":0.016300000250339508,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.004100000020116568,"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/computation","display_name":"Computation","score":0.5882999897003174},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.5702999830245972},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.567799985408783},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.5529000163078308},{"id":"https://openalex.org/keywords/data-compression-ratio","display_name":"Data compression ratio","score":0.5467000007629395},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.490200012922287},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.4797999858856201},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.4323999881744385}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6955000162124634},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5882999897003174},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.5702999830245972},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.567799985408783},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5644999742507935},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.5529000163078308},{"id":"https://openalex.org/C94835093","wikidata":"https://www.wikidata.org/wiki/Q3113333","display_name":"Data compression ratio","level":5,"score":0.5467000007629395},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.490200012922287},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.4797999858856201},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.4323999881744385},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.4307999908924103},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.4251999855041504},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.4171000123023987},{"id":"https://openalex.org/C25797200","wikidata":"https://www.wikidata.org/wiki/Q828137","display_name":"Compression ratio","level":3,"score":0.4122999906539917},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.39469999074935913},{"id":"https://openalex.org/C81081738","wikidata":"https://www.wikidata.org/wiki/Q55542","display_name":"Lossless compression","level":3,"score":0.3564000129699707},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3490999937057495},{"id":"https://openalex.org/C502989409","wikidata":"https://www.wikidata.org/wiki/Q11425","display_name":"Animation","level":2,"score":0.3066999912261963},{"id":"https://openalex.org/C54243161","wikidata":"https://www.wikidata.org/wiki/Q39333","display_name":"Texture compression","level":5,"score":0.30320000648498535},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30000001192092896},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C17349429","wikidata":"https://www.wikidata.org/wiki/Q1049914","display_name":"Matrix multiplication","level":3,"score":0.26969999074935913},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.2565000057220459}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3757377.3763961","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3757377.3763961","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the SIGGRAPH Asia 2025 Conference Papers","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1588539311","https://openalex.org/W1902027874","https://openalex.org/W1989305290","https://openalex.org/W1991359153","https://openalex.org/W2010512491","https://openalex.org/W2014035212","https://openalex.org/W2028959903","https://openalex.org/W2040364019","https://openalex.org/W2052728883","https://openalex.org/W2127114523","https://openalex.org/W2134389879","https://openalex.org/W2135046866","https://openalex.org/W2152005648","https://openalex.org/W2160547390","https://openalex.org/W2168860802","https://openalex.org/W2531006541","https://openalex.org/W2769666294","https://openalex.org/W3048366741","https://openalex.org/W3186344031","https://openalex.org/W4234257842","https://openalex.org/W4310379806","https://openalex.org/W4328028163","https://openalex.org/W4385536531","https://openalex.org/W4388410846","https://openalex.org/W4400573520","https://openalex.org/W4402770565"],"related_works":[],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"introduce":[4],"a":[5,36],"state-of-the-art":[6,103,125,132],"blendshape":[7,33],"compression":[8,55,75,93],"algorithm":[9,48],"that":[10],"significantly":[11],"reduces":[12],"storage":[13],"requirements":[14],"and":[15,28,42,59,109,128],"computational":[16,60],"complexity":[17],"in":[18,52],"facial":[19,137],"animation.":[20],"Our":[21,90],"approach":[22],"leverages":[23],"large":[24],"sparse":[25,83],"matrix":[26],"factorization":[27],"quantization":[29],"to":[30,79,96,120],"compress":[31],"high-dimensional":[32],"coefficients":[34],"into":[35],"compact":[37],"representation,":[38],"preserving":[39,110],"essential":[40],"features":[41,111],"high-frequency":[43],"geometric":[44],"details.":[45],"The":[46],"proposed":[47],"outperforms":[49],"existing":[50],"methods":[51],"terms":[53],"of":[54,77],"ratio,":[56],"reconstruction":[57],"quality,":[58],"efficiency.":[61],"We":[62],"demonstrate":[63],"its":[64],"effectiveness":[65],"through":[66],"extensive":[67],"experiments":[68],"on":[69,88,126,133,139],"various":[70],"animated":[71],"face":[72],"models,":[73],"achieving":[74],"factors":[76],"up":[78,95,119],"100":[80],"\u00d7":[81,98,122],"over":[82],"blendshapes":[84],"with":[85,143],"minimal":[86],"impact":[87],"quality.":[89],"technique":[91],"offers":[92],"rates":[94],"4.6":[97],"better":[99],"than":[100,124,131],"the":[101],"prior":[102],"while":[104],"also":[105],"improving":[106],"approximation":[107],"error":[108],"like":[112],"wrinkles.":[113],"Additionally,":[114],"our":[115],"runtime":[116],"computation":[117],"is":[118],"3":[121],"faster":[123,130],"CPU":[127],"70%":[129],"GPU,":[134],"facilitating":[135],"high-quality":[136],"animation":[138],"low-powered":[140],"computing":[141],"platforms":[142],"limited":[144],"resources.":[145]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-12-08T00:00:00"}