{"id":"https://openalex.org/W2887041979","doi":"https://doi.org/10.1109/tcsvt.2019.2903421","title":"CBinfer: Exploiting Frame-to-Frame Locality for Faster Convolutional Network Inference on Video Streams","display_name":"CBinfer: Exploiting Frame-to-Frame Locality for Faster Convolutional Network Inference on Video Streams","publication_year":2019,"publication_date":"2019-03-06","ids":{"openalex":"https://openalex.org/W2887041979","doi":"https://doi.org/10.1109/tcsvt.2019.2903421","mag":"2887041979"},"language":"en","primary_location":{"id":"doi:10.1109/tcsvt.2019.2903421","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2019.2903421","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"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 Circuits and Systems for Video Technology","raw_type":"journal-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1808.05488","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025399641","display_name":"Lukas Cavigelli","orcid":"https://orcid.org/0000-0003-1767-7715"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Lukas Cavigelli","raw_affiliation_strings":["ETH Z\u00fcrich, Z\u00fcrich, Switzerland","ETH Z\u00fcrich"],"raw_orcid":"https://orcid.org/0000-0003-1767-7715","affiliations":[{"raw_affiliation_string":"ETH Z\u00fcrich, Z\u00fcrich, Switzerland","institution_ids":["https://openalex.org/I35440088"]},{"raw_affiliation_string":"ETH Z\u00fcrich","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043408422","display_name":"Luca Benini","orcid":"https://orcid.org/0000-0001-8068-3806"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Luca Benini","raw_affiliation_strings":["ETH Z\u00fcrich, Z\u00fcrich, Switzerland","ETH Z\u00fcrich"],"raw_orcid":"https://orcid.org/0000-0001-8068-3806","affiliations":[{"raw_affiliation_string":"ETH Z\u00fcrich, Z\u00fcrich, Switzerland","institution_ids":["https://openalex.org/I35440088"]},{"raw_affiliation_string":"ETH Z\u00fcrich","institution_ids":["https://openalex.org/I35440088"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4068,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.63695341,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"30","issue":"5","first_page":"1451","last_page":"1465"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9991999864578247,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9988999962806702,"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":0.8313740491867065},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6479761600494385},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5846127867698669},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.5632805824279785},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5615583658218384},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5221343636512756},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.47733479738235474},{"id":"https://openalex.org/keywords/frame-rate","display_name":"Frame rate","score":0.4606817364692688},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.45610079169273376},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.4522630572319031},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4449543058872223},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4348955452442169},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.40569132566452026},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.39953044056892395},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.37698009610176086},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.12017372250556946},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09259957075119019},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.08742183446884155}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8313740491867065},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6479761600494385},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5846127867698669},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.5632805824279785},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5615583658218384},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5221343636512756},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.47733479738235474},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.4606817364692688},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.45610079169273376},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.4522630572319031},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4449543058872223},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4348955452442169},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40569132566452026},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.39953044056892395},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.37698009610176086},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.12017372250556946},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09259957075119019},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.08742183446884155},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1109/tcsvt.2019.2903421","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2019.2903421","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"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 Circuits and Systems for Video Technology","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1808.05488","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1808.05488","pdf_url":"https://arxiv.org/pdf/1808.05488","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":null,"raw_type":"text"},{"id":"pmh:oai:www.research-collection.ethz.ch:20.500.11850/282732","is_oa":true,"landing_page_url":"http://hdl.handle.net/20.500.11850/282732","pdf_url":null,"source":{"id":"https://openalex.org/S4306402302","display_name":"Repository for Publications and Research Data (ETH Zurich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I35440088","host_organization_name":"ETH Zurich","host_organization_lineage":["https://openalex.org/I35440088"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/submittedVersion"},{"id":"doi:10.48550/arxiv.1808.05488","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1808.05488","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"},{"id":"doi:10.3929/ethz-b-000282732","is_oa":true,"landing_page_url":"https://doi.org/10.3929/ethz-b-000282732","pdf_url":null,"source":{"id":"https://openalex.org/S7407051236","display_name":"ETH Z\u00fcrich Research Collection","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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"},{"id":"mag:2887041979","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1808.05488","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1808.05488","pdf_url":"https://arxiv.org/pdf/1808.05488","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":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.9100000262260437,"id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G4287651321","display_name":null,"funder_award_id":"162524","funder_id":"https://openalex.org/F4320320924","funder_display_name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung"}],"funders":[{"id":"https://openalex.org/F4320320924","display_name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung","ror":"https://ror.org/00yjd3n13"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":57,"referenced_works":["https://openalex.org/W764651262","https://openalex.org/W1667652561","https://openalex.org/W1677182931","https://openalex.org/W1843951383","https://openalex.org/W1861492603","https://openalex.org/W1903029394","https://openalex.org/W2063906779","https://openalex.org/W2070167224","https://openalex.org/W2091902424","https://openalex.org/W2117539524","https://openalex.org/W2125203716","https://openalex.org/W2142694332","https://openalex.org/W2155893237","https://openalex.org/W2172654076","https://openalex.org/W2260498192","https://openalex.org/W2279098554","https://openalex.org/W2285660444","https://openalex.org/W2300242332","https://openalex.org/W2336589871","https://openalex.org/W2337344472","https://openalex.org/W2340897893","https://openalex.org/W2411715258","https://openalex.org/W2424629859","https://openalex.org/W2431931973","https://openalex.org/W2477177239","https://openalex.org/W2520083297","https://openalex.org/W2524365899","https://openalex.org/W2559085405","https://openalex.org/W2563860341","https://openalex.org/W2606822607","https://openalex.org/W2623629680","https://openalex.org/W2626129225","https://openalex.org/W2678047256","https://openalex.org/W2759287047","https://openalex.org/W2771435580","https://openalex.org/W2786320458","https://openalex.org/W2796347433","https://openalex.org/W2796457364","https://openalex.org/W2952999519","https://openalex.org/W2962836170","https://openalex.org/W2962965870","https://openalex.org/W2963037989","https://openalex.org/W2963125010","https://openalex.org/W2963163009","https://openalex.org/W2963439282","https://openalex.org/W2963816728","https://openalex.org/W2964228333","https://openalex.org/W2964253307","https://openalex.org/W3024621361","https://openalex.org/W3121517425","https://openalex.org/W6639102338","https://openalex.org/W6698200048","https://openalex.org/W6703414193","https://openalex.org/W6726273544","https://openalex.org/W6734062232","https://openalex.org/W6789476068","https://openalex.org/W7071414696"],"related_works":["https://openalex.org/W2950164958","https://openalex.org/W2077699347","https://openalex.org/W2980692634","https://openalex.org/W2946900496","https://openalex.org/W2979332426","https://openalex.org/W2889666003","https://openalex.org/W2755747701","https://openalex.org/W3133850457","https://openalex.org/W2976783886","https://openalex.org/W3159259800","https://openalex.org/W3080878076","https://openalex.org/W2522007498","https://openalex.org/W3099971873","https://openalex.org/W3033240234","https://openalex.org/W2899505949","https://openalex.org/W3176583247","https://openalex.org/W2587232479","https://openalex.org/W3139722631","https://openalex.org/W3015305895","https://openalex.org/W3080464627"],"abstract_inverted_index":{"The":[0],"last":[1],"few":[2],"years":[3],"have":[4],"brought":[5],"advances":[6],"in":[7,18,98,177],"computer":[8],"vision":[9],"at":[10,111],"an":[11,78,99,131,178],"amazing":[12],"pace,":[13],"grounded":[14],"on":[15,51,65,72,106,161],"new":[16],"findings":[17],"deep":[19],"neural":[20],"network":[21,67,124],"construction":[22],"and":[23,44,81,119,144],"training":[24],"as":[25,27],"well":[26],"the":[28,46,87,107,123,150,187],"availability":[29],"of":[30,48,56,58,90,102,116,122,134,147,149,152,181],"large":[31],"labeled":[32],"datasets.":[33],"Applying":[34],"these":[35],"networks":[36,50],"to":[37,155,184],"images":[38],"demands":[39],"a":[40,83,112,126,140,145,172],"high":[41],"computational":[42],"effort":[43],"pushes":[45],"use":[47],"state-of-the-art":[49],"real-time":[52,70],"video":[53,164],"data":[54],"out":[55],"reach":[57],"embedded":[59,73],"platforms.":[60,75],"Many":[61],"recent":[62],"works":[63],"focus":[64],"reducing":[66],"complexity":[68],"for":[69,125,139,158,186],"inference":[71,95],"computing":[74],"We":[76],"adopt":[77],"orthogonal":[79],"viewpoint":[80],"propose":[82],"novel":[84],"algorithm":[85],"exploiting":[86],"spatio-temporal":[88],"sparsity":[89],"pixel":[91],"changes.":[92],"This":[93],"optimized":[94],"procedure":[96],"resulted":[97],"average":[100,132],"speed-up":[101,133],"9.1X":[103],"over":[104],"cuDNN":[105],"Tegra":[108],"X2":[109],"platform":[110],"negligible":[113],"accuracy":[114],"loss":[115],"<;":[117],"0.1%":[118],"no":[120],"retraining":[121],"semantic":[127],"segmentation":[128],"application.":[129],"Similarly,":[130],"7.0X":[135],"has":[136],"been":[137],"achieved":[138],"pose":[141],"detection":[142,160],"DNN":[143],"reduction":[146],"5X":[148],"number":[151],"arithmetic":[153],"operations":[154],"be":[156],"performed":[157],"object":[159],"static":[162],"camera":[163],"surveillance":[165],"data.":[166],"These":[167],"throughput":[168],"gains":[169],"combined":[170],"with":[171],"lower":[173],"power":[174],"consumption":[175],"result":[176],"energy":[179],"efficiency":[180],"511GOp/s/W":[182],"compared":[183],"70GOp/s/W":[185],"baseline.":[188]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
