{"id":"https://openalex.org/W3146573442","doi":null,"title":"Video Classification with FineCoarse Networks.","display_name":"Video Classification with FineCoarse Networks.","publication_year":2021,"publication_date":"2021-03-29","ids":{"openalex":"https://openalex.org/W3146573442","mag":"3146573442"},"language":"en","primary_location":{"id":"mag:3146573442","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2103.15584","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,"listed_in":[],"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},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://export.arxiv.org/pdf/2103.15584","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063460572","display_name":"Guoxi Huang","orcid":"https://orcid.org/0000-0002-8481-0232","observed_orcids":["https://orcid.org/0000-0002-8481-0232"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guoxi Huang","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-8481-0232","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5002932489","display_name":"Adrian G. Bor\u015f","orcid":"https://orcid.org/0000-0001-7838-0021","observed_orcids":["https://orcid.org/0000-0001-7838-0021"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Adrian G. Bor\u015f","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-7838-0021","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":6,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9843999743461609,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9843999743461609,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.00839999970048666,"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":0.0007999999797903001,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/video-classification","display_name":"video classification","score":0.953000009059906},{"id":"https://openalex.org/keywords/motion-boundary-detection","display_name":"motion boundary detection","score":0.42800000309944153},{"id":"https://openalex.org/keywords/computational-efficiency","display_name":"computational efficiency","score":0.6320000290870667}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8067424893379211},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.6816431283950806},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.664404034614563},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6255879998207092},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6156889200210571},{"id":"https://openalex.org/C7545210","wikidata":"https://www.wikidata.org/wiki/Q838123","display_name":"Data redundancy","level":2,"score":0.5000209808349609},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4891086220741272},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.45048120617866516},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.42216914892196655},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3974107503890991},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.11282321810722351},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:3146573442","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2103.15584","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,"listed_in":[],"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}],"best_oa_location":{"id":"mag:3146573442","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2103.15584","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,"listed_in":[],"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},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W24089286","https://openalex.org/W1522734439","https://openalex.org/W1578985305","https://openalex.org/W1586730761","https://openalex.org/W1686810756","https://openalex.org/W1836465849","https://openalex.org/W1947481528","https://openalex.org/W2097117768","https://openalex.org/W2108598243","https://openalex.org/W2126579184","https://openalex.org/W2147253850","https://openalex.org/W2156303437","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2507009361","https://openalex.org/W2518108298","https://openalex.org/W2553594924","https://openalex.org/W2559833261","https://openalex.org/W2565639579","https://openalex.org/W2619082050","https://openalex.org/W2625366777","https://openalex.org/W2770804203","https://openalex.org/W2782776028","https://openalex.org/W2806331055","https://openalex.org/W2823177849","https://openalex.org/W2883429621","https://openalex.org/W2894724248","https://openalex.org/W2946948417","https://openalex.org/W2951309005","https://openalex.org/W2953084276","https://openalex.org/W2953111739","https://openalex.org/W2953296820","https://openalex.org/W2962710043","https://openalex.org/W2962934715","https://openalex.org/W2963091558","https://openalex.org/W2963155035","https://openalex.org/W2963163009","https://openalex.org/W2963216700","https://openalex.org/W2963446712","https://openalex.org/W2963457877","https://openalex.org/W2963820951","https://openalex.org/W2964094092","https://openalex.org/W2981385151","https://openalex.org/W2981860940","https://openalex.org/W2984287396","https://openalex.org/W2988396473","https://openalex.org/W2989728968","https://openalex.org/W2990152177","https://openalex.org/W2990503944","https://openalex.org/W3015218717","https://openalex.org/W3015538334","https://openalex.org/W3034600407","https://openalex.org/W3035303837","https://openalex.org/W3035619757","https://openalex.org/W3160173571"],"related_works":["https://openalex.org/W4213039568","https://openalex.org/W4285821711","https://openalex.org/W3134997228","https://openalex.org/W2978412477","https://openalex.org/W3087873390","https://openalex.org/W7036845635","https://openalex.org/W4402727061","https://openalex.org/W2126131029","https://openalex.org/W4392435119","https://openalex.org/W7131395417"],"abstract_inverted_index":{"A":[0],"rich":[1],"representation":[2],"of":[3,14,23,96,116,140],"the":[4,21,32,73,85,94,102,117,124,127,132,144,148,154,175],"information":[5,42,75,78,87,151],"in":[6,31,79,126],"video":[7,52,81,97,163],"data":[8,98],"can":[9,92],"be":[10],"realized":[11],"by":[12,28,122,131,153],"means":[13],"frequency":[15],"analysis.":[16],"Fine":[17],"motion":[18,150],"details":[19],"from":[20,76],"boundaries":[22],"moving":[24],"regions":[25],"are":[26,38],"characterized":[27],"high":[29],"frequencies":[30,37],"spatio-temporal":[33],"domain.":[34],"Meanwhile,":[35],"lower":[36],"encoded":[39],"with":[40,88,177],"coarse":[41,77,86],"containing":[43],"substantial":[44],"redundancy,":[45],"which":[46],"causes":[47],"low":[48,89],"efficiency":[49,95,115],"for":[50,71],"those":[51],"models":[53,165],"that":[54],"take":[55],"as":[56],"input":[57],"raw":[58,80],"RGB":[59],"frames.":[60],"In":[61],"this":[62],"work,":[63],"we":[64,91,109],"propose":[65],"a":[66,105,111],"Motion":[67],"Band-pass":[68],"Module":[69],"(MBPM)":[70],"separating":[72],"fine-grained":[74,149],"data.":[82],"By":[83,100],"representing":[84],"resolution,":[90],"increase":[93],"processing.":[99],"embedding":[101],"MBPM":[103],"into":[104],"two-pathway":[106],"CNN":[107],"architecture,":[108],"define":[110],"FineCoarse":[112,118,158],"network.":[113],"The":[114,156],"network":[119,159],"is":[120],"determined":[121],"avoiding":[123],"redundancy":[125],"feature":[128],"space":[129],"processed":[130],"two":[133],"pathways:":[134],"one":[135],"operates":[136,146],"on":[137,147,166,181],"downsampled":[138],"features":[139],"low-resolution":[141],"data,":[142],"while":[143],"other":[145],"captured":[152],"MBPM.":[155],"proposed":[157],"outperforms":[160],"many":[161],"recent":[162],"processing":[164],"Kinetics400,":[167],"UCF101":[168],"and":[169],"HMDB51.":[170],"Furthermore,":[171],"our":[172],"approach":[173],"achieves":[174],"state-of-the-art":[176],"57.0%":[178],"top-1":[179],"accuracy":[180],"Something-Something":[182],"V1.":[183]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2021-04-13T00:00:00"}