{"id":"https://openalex.org/W3207914472","doi":"https://doi.org/10.1145/3474085.3475424","title":"Video-to-Image Casting: A Flatting Method for Video Analysis","display_name":"Video-to-Image Casting: A Flatting Method for Video Analysis","publication_year":2021,"publication_date":"2021-10-17","ids":{"openalex":"https://openalex.org/W3207914472","doi":"https://doi.org/10.1145/3474085.3475424","mag":"3207914472"},"language":"en","primary_location":{"id":"doi:10.1145/3474085.3475424","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3474085.3475424","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Multimedia","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/A5100385702","display_name":"Xu Chen","orcid":"https://orcid.org/0000-0002-1805-5435"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xu Chen","raw_affiliation_strings":["Chongqing University of Posts and Telecommunications &amp; Chongqing Key Laboratory of Signal and Information Processing, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"Chongqing University of Posts and Telecommunications &amp; Chongqing Key Laboratory of Signal and Information Processing, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021881939","display_name":"Chenqiang Gao","orcid":"https://orcid.org/0000-0003-4174-4148"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenqiang Gao","raw_affiliation_strings":["Chongqing University of Posts and Telecommunications &amp; Chongqing Key Laboratory of Signal and Information Processing, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"Chongqing University of Posts and Telecommunications &amp; Chongqing Key Laboratory of Signal and Information Processing, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100773623","display_name":"Feng Yang","orcid":"https://orcid.org/0000-0003-0413-8640"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Yang","raw_affiliation_strings":["Chongqing University of Posts and Telecommunications &amp; Chongqing Key Laboratory of Signal and Information Processing, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"Chongqing University of Posts and Telecommunications &amp; Chongqing Key Laboratory of Signal and Information Processing, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100354377","display_name":"Xiaohan Wang","orcid":"https://orcid.org/0000-0001-6206-7911"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]},{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohan Wang","raw_affiliation_strings":["Zhejiang University &amp; Baidu Research, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University &amp; Baidu Research, Hangzhou, China","institution_ids":["https://openalex.org/I98301712","https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005421447","display_name":"Yi Yang","orcid":"https://orcid.org/0000-0002-0512-880X"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Yang","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031819155","display_name":"Yahong Han","orcid":"https://orcid.org/0000-0003-2768-1398"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]},{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yahong Han","raw_affiliation_strings":["Tianjin University &amp; Peng Cheng Laboratory, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Tianjin University &amp; Peng Cheng Laboratory, Tianjin, China","institution_ids":["https://openalex.org/I4210136793","https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100385702"],"corresponding_institution_ids":["https://openalex.org/I10535382"],"apc_list":null,"apc_paid":null,"fwci":0.1921,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.49998366,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"4958","last_page":"4966"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":1.0,"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":1.0,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9876999855041504,"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":0.9865999817848206,"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":0.8130688667297363},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6987525820732117},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6450834274291992},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6227149963378906},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.566698431968689},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.518144965171814},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4401794970035553},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4248814880847931},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3830181956291199},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.26682084798812866},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.14892607927322388},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07456305623054504}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8130688667297363},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6987525820732117},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6450834274291992},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6227149963378906},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.566698431968689},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.518144965171814},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4401794970035553},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4248814880847931},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3830181956291199},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.26682084798812866},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.14892607927322388},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07456305623054504},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3474085.3475424","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3474085.3475424","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.4300000071525574,"display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G2919837275","display_name":null,"funder_award_id":"cstc2018jcyjAX0227,cstc2020jcyj-msxmX0835","funder_id":"https://openalex.org/F4320327865","funder_display_name":"Chongqing Research Program of Basic Research and Frontier Technology"},{"id":"https://openalex.org/G4398117279","display_name":null,"funder_award_id":"61571071,61906025,61932009","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320327865","display_name":"Chongqing Research Program of Basic Research and Frontier Technology","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W24089286","https://openalex.org/W1522734439","https://openalex.org/W1745334888","https://openalex.org/W1983364832","https://openalex.org/W2097117768","https://openalex.org/W2108598243","https://openalex.org/W2110275531","https://openalex.org/W2141200610","https://openalex.org/W2141859737","https://openalex.org/W2487442924","https://openalex.org/W2502312327","https://openalex.org/W2507009361","https://openalex.org/W2560474170","https://openalex.org/W2625366777","https://openalex.org/W2766402183","https://openalex.org/W2770804203","https://openalex.org/W2799176631","https://openalex.org/W2806331055","https://openalex.org/W2883429621","https://openalex.org/W2891446678","https://openalex.org/W2896347987","https://openalex.org/W2912152775","https://openalex.org/W2948242301","https://openalex.org/W2949117887","https://openalex.org/W2952186347","https://openalex.org/W2955874753","https://openalex.org/W2962934715","https://openalex.org/W2963091558","https://openalex.org/W2963125977","https://openalex.org/W2963155035","https://openalex.org/W2963420272","https://openalex.org/W2963524571","https://openalex.org/W2963631366","https://openalex.org/W2963820951","https://openalex.org/W2963972490","https://openalex.org/W2964037671","https://openalex.org/W2982277552","https://openalex.org/W2990152177","https://openalex.org/W2990503944","https://openalex.org/W3010874390","https://openalex.org/W3034572008","https://openalex.org/W3035303837","https://openalex.org/W3035413240","https://openalex.org/W3100481960","https://openalex.org/W3119401101","https://openalex.org/W6833403949"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4231775656","https://openalex.org/W4321487865","https://openalex.org/W2046435967","https://openalex.org/W4313906399","https://openalex.org/W4239306820","https://openalex.org/W4391266461","https://openalex.org/W2964954556","https://openalex.org/W2351938575","https://openalex.org/W2388359778"],"abstract_inverted_index":{"Previous":[0],"mainstream":[1],"video":[2,20,60,154],"analysis":[3],"methods,":[4],"especially":[5],"3D":[6,198],"CNNs-based":[7],"models,":[8],"mainly":[9],"aim":[10],"to":[11,18,47,57,91,138],"transfer":[12],"frameworks":[13],"from":[14],"the":[15,19,25,48,59,69,78,93,97,106,118,124,146,152],"image":[16,32],"domain":[17],"domain,":[21],"and":[22,37,61,81,170],"they":[23],"follow":[24],"regime":[26],"which":[27],"has":[28,117],"been":[29],"succeeded":[30],"in":[31],"processing,":[33],"i.e.,":[34,67,163],"large-scale":[35],"benchmarks":[36,189],"deep":[38],"networks.":[39],"However,":[40],"processing":[41],"videos":[42,140],"is":[43],"still":[44],"time-consuming":[45],"due":[46],"increased":[49],"computational":[50],"cost.":[51],"In":[52],"this":[53,101],"paper,":[54],"we":[55,84,111,129,156],"propose":[56],"flat":[58],"construct":[62],"a":[63,73,86,132],"Spatio-temporal":[64],"Image":[65],"(STI),":[66],"squeezing":[68],"temporal":[70],"dimension":[71],"into":[72],"spatial":[74],"plane.":[75],"To":[76,144],"pursuit":[77],"video-level":[79,107],"modeling":[80],"efficient":[82],"architecture,":[83],"devise":[85],"Collective":[87],"Convolution":[88],"(CoConv)":[89],"operation":[90,103,116],"replace":[92],"2D":[94,126,133],"convolution.":[95],"With":[96],"holistic":[98],"sampling":[99],"strategy,":[100],"novel":[102],"can":[104,130,181],"extract":[105],"spatio-temporal":[108],"representation.":[109],"Moreover,":[110],"ensure":[112],"that":[113,178],"each":[114],"CoConv":[115,137],"same":[119],"number":[120],"of":[121,148],"parameters":[122],"as":[123],"original":[125],"filter,":[127],"thus":[128],"utilize":[131],"network":[134],"equipped":[135],"with":[136,196],"analyze":[139],"without":[141],"additional":[142],"computations.":[143],"verify":[145],"effectiveness":[147],"our":[149,179],"method":[150,180],"for":[151],"general":[153],"analysis,":[155],"evaluate":[157],"it":[158],"on":[159,187],"three":[160],"typical":[161],"tasks,":[162],"supervised":[164],"action":[165,168],"recognition,":[166,169],"self-supervised":[167],"dynamic":[171],"texture":[172],"recognition.":[173],"Extensive":[174],"experimental":[175],"results":[176],"show":[177],"achieve":[182],"comparable":[183],"or":[184],"state-of-the-art":[185],"performances":[186],"these":[188],"while":[190],"using":[191],"much":[192],"fewer":[193],"computations":[194],"compared":[195],"its":[197],"counterpart.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
