{"id":"https://openalex.org/W7163127200","doi":"https://doi.org/10.1109/tip.2026.3697621","title":"Weakly Supervised Temporal Action Localization With Proposal-Level Action Consistency Learning","display_name":"Weakly Supervised Temporal Action Localization With Proposal-Level Action Consistency Learning","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7163127200","doi":"https://doi.org/10.1109/tip.2026.3697621","pmid":"https://pubmed.ncbi.nlm.nih.gov/42228666"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2026.3697621","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3697621","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5042105147","display_name":"Maodong Li","orcid":"https://orcid.org/0000-0001-5637-5862"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Maodong Li","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-0116-474X","affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137629877","display_name":"Zhihao Wang","orcid":"https://orcid.org/0009-0008-5966-0325"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihao Wang","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0009-0008-5966-0325","affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137696513","display_name":"Tian Wang","orcid":"https://orcid.org/0000-0001-8427-4495"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tian Wang","raw_affiliation_strings":["School of Artificial Intelligence, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8427-4495","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012136338","display_name":"Jingxiong Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingxiong Wang","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100370411","display_name":"Jian Wang","orcid":"https://orcid.org/0000-0002-1559-9314"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Wang","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-1559-9314","affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100374441","display_name":"Bo Li","orcid":"https://orcid.org/0000-0002-5802-7519"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]},{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bing Li","raw_affiliation_strings":["School of Computer Science and Hubei Luojia Laboratory, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-2165-2636","affiliations":[{"raw_affiliation_string":"School of Computer Science and Hubei Luojia Laboratory, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I196699116","https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.68854342,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"35","issue":null,"first_page":"5894","last_page":"5909"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.8946999907493591,"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":0.8946999907493591,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.015300000086426735,"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/T11431","display_name":"Action Observation and Synchronization","score":0.011800000444054604,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.476500004529953},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.448199987411499},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.4180000126361847},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.39480000734329224},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.3476000130176544},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.3395000100135803}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6754999756813049},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6657999753952026},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.476500004529953},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.448199987411499},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.4180000126361847},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.39480000734329224},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.3476000130176544},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3411000072956085},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.3395000100135803},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27239999175071716},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.26089999079704285},{"id":"https://openalex.org/C196340769","wikidata":"https://www.wikidata.org/wiki/Q7698910","display_name":"Temporal difference learning","level":3,"score":0.25839999318122864},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.257999986410141}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2026.3697621","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3697621","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},{"id":"pmid:42228666","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42228666","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.40013694763183594,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G2203848881","display_name":null,"funder_award_id":"202504005043","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2670355544","display_name":null,"funder_award_id":"20220484106","funder_id":"https://openalex.org/F4320334978","funder_display_name":"Beijing Nova Program"},{"id":"https://openalex.org/G3381026780","display_name":null,"funder_award_id":"92467108","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5675372752","display_name":null,"funder_award_id":"62032016","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7123472995","display_name":null,"funder_award_id":"20230484451","funder_id":"https://openalex.org/F4320334978","funder_display_name":"Beijing Nova Program"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320334978","display_name":"Beijing Nova Program","ror":"https://ror.org/034k14f91"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Existing":[0],"weakly":[1],"supervised":[2],"temporal":[3,173],"action":[4],"localization":[5,209],"(WTAL)":[6],"methods":[7],"typically":[8],"follow":[9],"a":[10,93,103,117,140,161],"decoupled":[11],"classification-localization":[12,83],"pipeline:":[13],"segment-level":[14],"classifiers":[15],"are":[16,22,60],"trained":[17],"first,":[18],"and":[19,52,79,134,159,191,199,213,221],"their":[20],"predictions":[21],"then":[23],"aggregated":[24],"to":[25,75,131,152,181,202],"score":[26,55,97],"proposals":[27],"at":[28,36],"inference.":[29],"Under":[30],"this":[31],"training-inference":[32],"discrepancy,":[33],"proposal":[34,58,87,96,124,183,204],"scoring":[35],"inference":[37],"relies":[38],"on":[39],"an":[40],"additional":[41],"aggregation":[42],"step,":[43],"which":[44],"can":[45],"accumulate":[46],"errors":[47],"from":[48,171],"noisy":[49],"segment":[50],"responses":[51],"thus":[53,80],"undermine":[54],"reliability.":[56],"Moreover,":[57],"scores":[59,170],"often":[61],"directly":[62],"used":[63],"as":[64],"confidence":[65],"without":[66],"explicit":[67],"score-quality":[68,77,88,193],"modeling":[69,197],"or":[70],"quality-aware":[71],"evaluation,":[72],"further":[73],"contributing":[74],"pronounced":[76],"misalignment":[78],"widening":[81],"the":[82,148,179,231],"gap.":[84],"To":[85],"address":[86],"misalignment,":[89],"we":[90],"propose":[91],"ACL-Net,":[92],"framework":[94],"for":[95],"calibration.":[98],"At":[99],"its":[100],"core":[101],"is":[102],"dual-axis":[104],"Proposal-level":[105],"Action":[106],"Consistency":[107,119,163],"Learning":[108],"(PACL)":[109],"paradigm,":[110],"implemented":[111],"through":[112],"two":[113],"complementary":[114],"modules:":[115],"(i)":[116],"Semantic":[118],"Module":[120,145,164],"(SCM)":[121],"that":[122,166],"refines":[123],"representations":[125],"by":[126],"maintaining":[127],"fused":[128,149],"class":[129,150],"centers":[130,151],"enforce":[132],"compact":[133],"robust":[135],"same-class":[136],"features;":[137],"within":[138],"SCM,":[139],"cross-modal":[141],"consistency-driven":[142],"Classification":[143],"Enhancement":[144],"(CEM)":[146],"denoises":[147],"mitigate":[153],"error":[154,234],"accumulation":[155],"under":[156],"weak":[157],"supervision;":[158],"(ii)":[160],"Process":[162],"(PCM)":[165],"derives":[167],"geometry-aware":[168],"reference":[169],"relative":[172,188],"relations":[174],"among":[175],"overlapping":[176],"proposals,":[177],"guiding":[178],"model":[180],"assess":[182],"quality":[184],"in":[185],"terms":[186],"of":[187],"process":[189,200],"completeness":[190],"improve":[192],"alignment.":[194],"By":[195],"jointly":[196],"semantic":[198],"consistency":[201],"calibrate":[203],"scores,":[205],"ACL-Net":[206],"markedly":[207,229],"improves":[208],"accuracy.":[210],"On":[211],"THUMOS14":[212],"ActivityNet1.3,":[214],"it":[215],"achieves":[216],"state-of-the-art":[217],"performance":[218],"with":[219],"uniform":[220],"substantial":[222],"gains":[223],"across":[224],"multiple":[225],"established":[226],"baselines,":[227],"while":[228],"lowering":[230],"expected":[232],"calibration":[233],"(ECE).":[235]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2026-06-03T00:00:00"}