{"id":"https://openalex.org/W4304098231","doi":"https://doi.org/10.1145/3503161.3551585","title":"Multiple Temporal Fusion based Weakly-supervised Pre-training Techniques for Video Categorization","display_name":"Multiple Temporal Fusion based Weakly-supervised Pre-training Techniques for Video Categorization","publication_year":2022,"publication_date":"2022-10-10","ids":{"openalex":"https://openalex.org/W4304098231","doi":"https://doi.org/10.1145/3503161.3551585"},"language":"en","primary_location":{"id":"doi:10.1145/3503161.3551585","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503161.3551585","pdf_url":null,"source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","issn_l":null,"issn":null,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"conference-paper","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/A5102245433","display_name":"Xiaochen Cai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaochen Cai","raw_affiliation_strings":["4Paradigm Inc., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"4Paradigm Inc., Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020229717","display_name":"Hengxing Cai","orcid":"https://orcid.org/0000-0001-9780-2330"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hengxing Cai","raw_affiliation_strings":["4Paradigm Inc., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"4Paradigm Inc., Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018669598","display_name":"Boqing Zhu","orcid":"https://orcid.org/0000-0001-7867-2112"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Boqing Zhu","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013340793","display_name":"Kele Xu","orcid":"https://orcid.org/0000-0001-5997-5169"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kele Xu","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032604295","display_name":"Wei-Wei Tu","orcid":"https://orcid.org/0000-0002-2407-0252"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Weiwei Tu","raw_affiliation_strings":["4Paradigm Inc., Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"4Paradigm Inc., Changsha, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039795290","display_name":"Dawei Feng","orcid":"https://orcid.org/0000-0002-7587-8905"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dawei Feng","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7089","last_page":"7093"},"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":0.9993000030517578,"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":0.9991999864578247,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.8625447750091553},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8229432106018066},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6331220865249634},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5583044290542603},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5489023327827454},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45031100511550903},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4288123548030853},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39696845412254333}],"concepts":[{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.8625447750091553},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8229432106018066},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6331220865249634},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5583044290542603},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5489023327827454},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45031100511550903},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4288123548030853},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39696845412254333},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3503161.3551585","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503161.3551585","pdf_url":null,"source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","issn_l":null,"issn":null,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Multimedia","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":13,"referenced_works":["https://openalex.org/W2102605133","https://openalex.org/W2108598243","https://openalex.org/W2425121537","https://openalex.org/W2507009361","https://openalex.org/W2559085405","https://openalex.org/W2625366777","https://openalex.org/W2963315828","https://openalex.org/W2963703197","https://openalex.org/W2964084369","https://openalex.org/W2980037812","https://openalex.org/W3126721948","https://openalex.org/W3138516171","https://openalex.org/W4312560592"],"related_works":["https://openalex.org/W2165912799","https://openalex.org/W2735662278","https://openalex.org/W2382615723","https://openalex.org/W4311804456","https://openalex.org/W1987484445","https://openalex.org/W2623658258","https://openalex.org/W2143413548","https://openalex.org/W1969219540","https://openalex.org/W2370459448","https://openalex.org/W2521035608"],"abstract_inverted_index":{"In":[0],"this":[1,84],"paper,":[2],"we":[3,18,54],"present":[4],"our":[5],"solution":[6],"of":[7,46,66,83],"the":[8,20,33,44,69,75,79],"ACM":[9],"Multimedia":[10],"2022":[11],"pre-training":[12],"for":[13,35],"video":[14,25,80],"understanding":[15],"challenge.":[16,85],"First,":[17],"pre-train":[19],"models":[21,58],"on":[22],"large-scale":[23],"weakly-supervised":[24],"datasets":[26],"with":[27],"different":[28,47,56],"temporal":[29,51],"resolutions,":[30],"then":[31],"fine-tune":[32],"model":[34],"downstream":[36],"application.":[37],"Quantitative":[38],"comparisons":[39],"are":[40],"conducted":[41],"to":[42],"evaluate":[43],"performance":[45],"networks":[48],"at":[49],"multiple":[50],"resolutions.":[52],"Moreover,":[53],"fusion":[55],"pre-trained":[57],"through":[59],"weighted":[60],"averaging.":[61],"We":[62],"achieve":[63],"an":[64],"accuracy":[65],"62.39%":[67],"in":[68,78],"testing":[70],"set,":[71],"which":[72],"ranked":[73],"as":[74],"first":[76],"place":[77],"categorization":[81],"track":[82]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
