{"id":"https://openalex.org/W4415540494","doi":"https://doi.org/10.1145/3746027.3754712","title":"Ex Pede Herculem, Predicting Global Actionness Curve from Local Clips","display_name":"Ex Pede Herculem, Predicting Global Actionness Curve from Local Clips","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415540494","doi":"https://doi.org/10.1145/3746027.3754712"},"language":null,"primary_location":{"id":"doi:10.1145/3746027.3754712","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3754712","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd 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/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xu Chen","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-1805-5435","affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yang Li","orcid":"https://orcid.org/0009-0004-3028-5972"},"institutions":[{"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":"Yang Li","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0009-0004-3028-5972","affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031819155","display_name":"Yahong Han","orcid":"https://orcid.org/0000-0003-2768-1398"},"institutions":[{"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":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-2768-1398","affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026951130","display_name":"Jialie Shen","orcid":"https://orcid.org/0000-0002-4560-8509"},"institutions":[{"id":"https://openalex.org/I165862685","display_name":"St George's, University of London","ror":"https://ror.org/040f08y74","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I165862685"]},{"id":"https://openalex.org/I4401726869","display_name":"City St George's, University of London","ror":"https://ror.org/047ybhc09","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I4401726869"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jialie Shen","raw_affiliation_strings":["Department of Computer Science, City St George's, University of London, London, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0002-4560-8509","affiliations":[{"raw_affiliation_string":"Department of Computer Science, City St George's, University of London, London, United Kingdom","institution_ids":["https://openalex.org/I165862685","https://openalex.org/I4401726869"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100385702"],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28957775,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7239","last_page":"7247"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9929999709129333,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9929999709129333,"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":0.9922000169754028,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.991599977016449,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5672000050544739},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5608000159263611},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.45809999108314514},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4472000002861023},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43810001015663147},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.42239999771118164}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6478999853134155},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5672000050544739},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5608000159263611},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5293999910354614},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.45809999108314514},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4472000002861023},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43810001015663147},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.42239999771118164},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41609999537467957},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.39809998869895935},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.3880000114440918},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3813000023365021},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38100001215934753},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2971999943256378},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.27790001034736633},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.25949999690055847},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.25119999051094055}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746027.3754712","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3754712","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1297212625","display_name":null,"funder_award_id":"62376186","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1927052826","https://openalex.org/W2100443089","https://openalex.org/W2997410994","https://openalex.org/W3081618117","https://openalex.org/W3119243803","https://openalex.org/W4382202907","https://openalex.org/W4391953443","https://openalex.org/W4407638641"],"related_works":[],"abstract_inverted_index":{"Dense":[0],"multi-label":[1],"action":[2,34,77],"detection":[3],"in":[4],"untrimmed":[5],"long":[6],"videos":[7],"is":[8],"a":[9,49,81],"formidable":[10],"task,":[11],"with":[12],"end-to-end":[13,96],"training":[14,97],"particularly":[15],"challenging":[16],"due":[17],"to":[18,38,64],"computational":[19],"constraints,":[20],"typically":[21],"involving":[22],"separate":[23],"stages":[24],"of":[25],"off-the-shelf":[26],"feature":[27],"extraction":[28],"and":[29,84,106],"subsequent":[30],"global":[31,76],"modeling":[32],"for":[33,43,87],"prediction.Existing":[35],"methods":[36],"fail":[37],"optimize":[39],"all":[40],"modules":[41],"jointly":[42],"better":[44],"performance.":[45],"We":[46],"introduce":[47],"FreETAD,":[48],"Frequency-based":[50],"End-to-end":[51],"Temporal":[52],"Action":[53],"Detection":[54],"approach,":[55],"which":[56],"shifts":[57],"the":[58,69,75,100],"focus":[59],"from":[60],"local":[61],"actionness":[62],"scores":[63],"frequency":[65],"component":[66],"estimation.":[67],"Using":[68],"short-term":[70],"Fourier":[71],"Transform,":[72],"FreETAD":[73,94],"reconstructs":[74],"curve":[78],"seamlessly.":[79],"With":[80],"DETR-like":[82],"decoder":[83],"frequency-encoded":[85],"vectors":[86],"queries,":[88],"it":[89],"enhances":[90],"multi-scale":[91],"time-frequency":[92],"interactions.":[93],"leverages":[95],"effectively,":[98],"boosting":[99],"mAP":[101],"by":[102],"1.5%":[103],"on":[104,108],"Charades":[105],"2.7%":[107],"MultiTHUMOS.":[109]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-25T00:00:00"}
