{"id":"https://openalex.org/W2995784647","doi":"https://doi.org/10.1109/wacv45572.2020.9093546","title":"Filter Distillation for Network Compression","display_name":"Filter Distillation for Network Compression","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W2995784647","doi":"https://doi.org/10.1109/wacv45572.2020.9093546","mag":"2995784647"},"language":"en","primary_location":{"id":"doi:10.1109/wacv45572.2020.9093546","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093546","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1807.10585","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046208400","display_name":"Xavier Suau","orcid":"https://orcid.org/0000-0002-4052-7048"},"institutions":[{"id":"https://openalex.org/I4210107260","display_name":"Apple (United Kingdom)","ror":"https://ror.org/01vpeym60","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210107260"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Xavier Suau","raw_affiliation_strings":["Apple"],"affiliations":[{"raw_affiliation_string":"Apple","institution_ids":["https://openalex.org/I4210107260"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043365442","display_name":"Luca Zappella","orcid":null},"institutions":[{"id":"https://openalex.org/I4210107260","display_name":"Apple (United Kingdom)","ror":"https://ror.org/01vpeym60","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210107260"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"uca Zappella","raw_affiliation_strings":["Apple"],"affiliations":[{"raw_affiliation_string":"Apple","institution_ids":["https://openalex.org/I4210107260"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071541814","display_name":"Nicholas Apostoloff","orcid":null},"institutions":[{"id":"https://openalex.org/I4210107260","display_name":"Apple (United Kingdom)","ror":"https://ror.org/01vpeym60","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210107260"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Nicholas Apostoloff","raw_affiliation_strings":["Apple"],"affiliations":[{"raw_affiliation_string":"Apple","institution_ids":["https://openalex.org/I4210107260"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5046208400"],"corresponding_institution_ids":["https://openalex.org/I4210107260"],"apc_list":null,"apc_paid":null,"fwci":0.20993464,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.46408784,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"3129","last_page":"3138"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11019","display_name":"Image Enhancement Techniques","score":0.9991000294685364,"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/computer-science","display_name":"Computer science","score":0.7302601337432861},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.6264239549636841},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5689011812210083},{"id":"https://openalex.org/keywords/data-compression-ratio","display_name":"Data compression ratio","score":0.49767187237739563},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4946300685405731},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.46443045139312744},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.46059027314186096},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.4466109275817871},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44595834612846375},{"id":"https://openalex.org/keywords/lossless-compression","display_name":"Lossless compression","score":0.4168705940246582},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.416762113571167},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.41148656606674194},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3724002242088318},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.3153168559074402},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20065265893936157},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1535915732383728},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.11260297894477844},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.0984443724155426},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07070353627204895}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7302601337432861},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.6264239549636841},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5689011812210083},{"id":"https://openalex.org/C94835093","wikidata":"https://www.wikidata.org/wiki/Q3113333","display_name":"Data compression ratio","level":5,"score":0.49767187237739563},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4946300685405731},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.46443045139312744},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.46059027314186096},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.4466109275817871},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44595834612846375},{"id":"https://openalex.org/C81081738","wikidata":"https://www.wikidata.org/wiki/Q55542","display_name":"Lossless compression","level":3,"score":0.4168705940246582},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.416762113571167},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.41148656606674194},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3724002242088318},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.3153168559074402},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20065265893936157},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1535915732383728},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.11260297894477844},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.0984443724155426},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07070353627204895},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/wacv45572.2020.9093546","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093546","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1807.10585","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1807.10585","pdf_url":"https://arxiv.org/pdf/1807.10585","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:2995784647","is_oa":true,"landing_page_url":"https://arxiv.org/abs/1807.10585","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1807.10585","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1807.10585","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"article-journal"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1807.10585","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1807.10585","pdf_url":"https://arxiv.org/pdf/1807.10585","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"score":0.6100000143051147,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2995784647.pdf","grobid_xml":"https://content.openalex.org/works/W2995784647.grobid-xml"},"referenced_works_count":82,"referenced_works":["https://openalex.org/W1821462560","https://openalex.org/W1903029394","https://openalex.org/W1965555277","https://openalex.org/W1996901117","https://openalex.org/W2036887984","https://openalex.org/W2071128523","https://openalex.org/W2108598243","https://openalex.org/W2114766824","https://openalex.org/W2125101937","https://openalex.org/W2134797427","https://openalex.org/W2141155619","https://openalex.org/W2161591461","https://openalex.org/W2167215970","https://openalex.org/W2181101938","https://openalex.org/W2194775991","https://openalex.org/W2233116163","https://openalex.org/W2294370754","https://openalex.org/W2294543795","https://openalex.org/W2295405790","https://openalex.org/W2300242332","https://openalex.org/W2312434537","https://openalex.org/W2553902701","https://openalex.org/W2605135468","https://openalex.org/W2608609325","https://openalex.org/W2752514874","https://openalex.org/W2754084392","https://openalex.org/W2788800397","https://openalex.org/W2798170643","https://openalex.org/W2799197246","https://openalex.org/W2883028206","https://openalex.org/W2894568827","https://openalex.org/W2898756011","https://openalex.org/W2962684187","https://openalex.org/W2962835968","https://openalex.org/W2962851801","https://openalex.org/W2962921245","https://openalex.org/W2962965870","https://openalex.org/W2962980542","https://openalex.org/W2963000224","https://openalex.org/W2963048316","https://openalex.org/W2963145730","https://openalex.org/W2963225922","https://openalex.org/W2963287528","https://openalex.org/W2963300879","https://openalex.org/W2963363373","https://openalex.org/W2963626527","https://openalex.org/W2963628712","https://openalex.org/W2963674932","https://openalex.org/W2963759574","https://openalex.org/W2964118293","https://openalex.org/W2964152344","https://openalex.org/W2964217848","https://openalex.org/W2964233199","https://openalex.org/W2964299589","https://openalex.org/W3118608800","https://openalex.org/W6637373629","https://openalex.org/W6637551013","https://openalex.org/W6638523607","https://openalex.org/W6638632666","https://openalex.org/W6649495467","https://openalex.org/W6677103964","https://openalex.org/W6677580257","https://openalex.org/W6679667936","https://openalex.org/W6681015464","https://openalex.org/W6681017033","https://openalex.org/W6683826617","https://openalex.org/W6684563725","https://openalex.org/W6685444988","https://openalex.org/W6685802191","https://openalex.org/W6696912008","https://openalex.org/W6697099898","https://openalex.org/W6698200048","https://openalex.org/W6725543821","https://openalex.org/W6726275242","https://openalex.org/W6739917289","https://openalex.org/W6743958420","https://openalex.org/W6748581759","https://openalex.org/W6748728731","https://openalex.org/W6751769266","https://openalex.org/W6751946184","https://openalex.org/W6755509189","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W3024084317","https://openalex.org/W2942142338","https://openalex.org/W3205242123","https://openalex.org/W2911892981","https://openalex.org/W2902991518","https://openalex.org/W2923555562","https://openalex.org/W2963735024","https://openalex.org/W3106178055","https://openalex.org/W2883028206","https://openalex.org/W3186412620","https://openalex.org/W2788153607","https://openalex.org/W2914261901","https://openalex.org/W2737100304","https://openalex.org/W3206875170","https://openalex.org/W3120250747","https://openalex.org/W3009383973","https://openalex.org/W2948954216","https://openalex.org/W2794427825","https://openalex.org/W3120310601","https://openalex.org/W2789197829"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3,129],"introduce":[4],"Principal":[5],"Filter":[6],"Analysis":[7],"(PFA),":[8],"an":[9,112,185],"easy":[10],"to":[11,30,55,58,110,144,210],"use":[12],"and":[13,69,156,158,172,182,192,216],"effective":[14],"method":[15],"for":[16,167],"neural":[17],"network":[18,28,34,60],"compression.":[19],"PFA":[20,119,150,174,199],"exploits":[21],"the":[22,41,44,51,76,81,88,94,102,124,137],"correlation":[23,125],"between":[24],"filter":[25],"responses":[26,89,128],"within":[27],"layers":[29],"recommend":[31],"a":[32,71,97,145,176],"smaller":[33],"that":[35,74,100,134,198],"maintain":[36],"as":[37,39,63],"much":[38],"possible":[40],"accuracy":[42,186],"of":[43,65,84,90,115,126,140,179,188,218],"full":[45],"model.":[46],"We":[47],"propose":[48],"two":[49],"algorithms:":[50],"first":[52],"allows":[53],"users":[54],"target":[56],"compression":[57,103,161,177],"specific":[59,146],"property,":[61],"such":[62],"number":[64],"trainable":[66],"variable":[67],"(footprint),":[68],"produces":[70],"compressed":[72],"model":[73],"satisfies":[75],"requested":[77],"property":[78],"while":[79,93,148,205],"preserving":[80],"maximum":[82],"amount":[83],"spectral":[85],"energy":[86],"in":[87,131],"each":[91,106,142],"layer,":[92],"second":[95],"is":[96,151,200],"parameter-free":[98],"heuristic":[99],"selects":[101],"used":[104],"at":[105],"layer":[107],"by":[108],"trying":[109],"mimic":[111],"ideal":[113],"set":[114],"uncorrelated":[116],"responses.":[117],"Since":[118],"compresses":[120],"networks":[121],"based":[122],"on":[123,169],"their":[127],"show":[130,197],"our":[132],"experiments":[133],"it":[135],"gains":[136],"additional":[138],"flexibility":[139],"adapting":[141],"architecture":[143],"domain":[147],"compressing.":[149],"evaluated":[152],"against":[153],"several":[154],"architectures":[155],"datasets,":[157],"shows":[159],"considerable":[160],"rates":[162],"without":[163],"compromising":[164],"accuracy,":[165],"e.g.,":[166],"VGG-16":[168],"CIFAR-10,":[170],"CIFAR-100":[171],"ImageNet,":[173],"achieves":[175],"rate":[178],"8x,":[180],"3x,":[181],"1.4x":[183],"with":[184,202],"gain":[187],"0.4%,":[189],"1.4%":[190],"points,":[191],"2.4%":[193],"respectively.":[194],"Our":[195],"tests":[196],"competitive":[201],"state-of-the-art":[203],"approaches":[204],"removing":[206],"adoption":[207],"barriers":[208],"thanks":[209],"its":[211],"practical":[212],"implementation,":[213],"intuitive":[214],"philosophy":[215],"ease":[217],"use.":[219]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}