{"id":"https://openalex.org/W7131122558","doi":"https://doi.org/10.1109/iccvw69036.2025.00314","title":"Difformer for Action Segmentation","display_name":"Difformer for Action Segmentation","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W7131122558","doi":"https://doi.org/10.1109/iccvw69036.2025.00314"},"language":null,"primary_location":{"id":"doi:10.1109/iccvw69036.2025.00314","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvw69036.2025.00314","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)","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/A5042042517","display_name":"Nicolas Aziere","orcid":"https://orcid.org/0000-0003-0780-5349"},"institutions":[{"id":"https://openalex.org/I131249849","display_name":"Oregon State University","ror":"https://ror.org/00ysfqy60","country_code":"US","type":"education","lineage":["https://openalex.org/I131249849"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nicolas Aziere","raw_affiliation_strings":["Oregon State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Oregon State University","institution_ids":["https://openalex.org/I131249849"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033035588","display_name":"Tieqiao Wang","orcid":"https://orcid.org/0000-0001-5354-8342"},"institutions":[{"id":"https://openalex.org/I131249849","display_name":"Oregon State University","ror":"https://ror.org/00ysfqy60","country_code":"US","type":"education","lineage":["https://openalex.org/I131249849"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tieqiao Wang","raw_affiliation_strings":["Oregon State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Oregon State University","institution_ids":["https://openalex.org/I131249849"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027742996","display_name":"Sini\u0161a Todorovi\u0107","orcid":"https://orcid.org/0000-0001-5793-5921"},"institutions":[{"id":"https://openalex.org/I131249849","display_name":"Oregon State University","ror":"https://ror.org/00ysfqy60","country_code":"US","type":"education","lineage":["https://openalex.org/I131249849"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sinisa Todorovic","raw_affiliation_strings":["Oregon State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Oregon State University","institution_ids":["https://openalex.org/I131249849"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I131249849"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.64502933,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3007","last_page":"3016"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.7936000227928162,"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":0.7936000227928162,"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/T12290","display_name":"Human Motion and Animation","score":0.03880000114440918,"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"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.024000000208616257,"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/benchmark","display_name":"Benchmark (surveying)","score":0.6762999892234802},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6606000065803528},{"id":"https://openalex.org/keywords/dirichlet-distribution","display_name":"Dirichlet distribution","score":0.5774999856948853},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5597000122070312},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5379999876022339},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5212000012397766},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.483599990606308},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.4796999990940094}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6762999892234802},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6606000065803528},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6000000238418579},{"id":"https://openalex.org/C169214877","wikidata":"https://www.wikidata.org/wiki/Q981016","display_name":"Dirichlet distribution","level":3,"score":0.5774999856948853},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5717999935150146},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5597000122070312},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5379999876022339},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5212000012397766},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.483599990606308},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.4796999990940094},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4611000120639801},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.45809999108314514},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39980000257492065},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.362199991941452},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.33889999985694885},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3248000144958496},{"id":"https://openalex.org/C2781280628","wikidata":"https://www.wikidata.org/wiki/Q5280766","display_name":"Dirichlet process","level":3,"score":0.321399986743927},{"id":"https://openalex.org/C141318989","wikidata":"https://www.wikidata.org/wiki/Q5753066","display_name":"Hierarchical Dirichlet process","level":4,"score":0.3188999891281128},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.2757999897003174},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.27399998903274536},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25279998779296875},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccvw69036.2025.00314","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvw69036.2025.00314","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8979553857","display_name":null,"funder_award_id":"2021-67021-35344","funder_id":"https://openalex.org/F4320332299","funder_display_name":"National Institute of Food and Agriculture"}],"funders":[{"id":"https://openalex.org/F4320332299","display_name":"National Institute of Food and Agriculture","ror":"https://ror.org/05qx3fv49"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W2031688197","https://openalex.org/W2099614498","https://openalex.org/W2103328396","https://openalex.org/W2109698606","https://openalex.org/W2111051539","https://openalex.org/W2884490794","https://openalex.org/W2963524571","https://openalex.org/W2963538371","https://openalex.org/W2963853051","https://openalex.org/W2964059111","https://openalex.org/W2990152177","https://openalex.org/W3014596384","https://openalex.org/W3039044273","https://openalex.org/W3083550439","https://openalex.org/W3108772932","https://openalex.org/W3119038403","https://openalex.org/W3166363426","https://openalex.org/W3204193736","https://openalex.org/W4225147643","https://openalex.org/W4300717114","https://openalex.org/W4312624947","https://openalex.org/W4312770813","https://openalex.org/W4313055276","https://openalex.org/W4313071313","https://openalex.org/W4379927854","https://openalex.org/W4386057769","https://openalex.org/W4390872435","https://openalex.org/W4390873568","https://openalex.org/W4390873751","https://openalex.org/W4402780112"],"related_works":[],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,45,64,70],"novel":[3],"approach":[4,39,94],"to":[5,23],"supervised":[6],"action":[7],"segmentation":[8],"that":[9,27,92],"explicitly":[10],"models":[11],"uncertainty":[12],"over":[13],"framewise":[14],"class":[15,42],"predictions":[16],"using":[17,69],"the":[18,30],"Dirichlet":[19,46],"distribution.":[20],"In":[21],"contrast":[22],"most":[24],"SOTA":[25],"methods":[26],"rely":[28],"on":[29,80],"multi-stage":[31],"refinement":[32],"of":[33,67],"initially":[34],"proposed":[35],"frame":[36],"labels,":[37],"our":[38,93],"recalibrates":[40],"frame-level":[41],"distributions":[43],"through":[44],"diffusion":[47],"process,":[48],"which":[49],"is":[50],"analytically":[51],"tractable":[52],"(closed-form)":[53],"and":[54,76,88,101],"hence":[55],"computationally":[56],"efficient.":[57],"Diffusion":[58],"parameters":[59,100],"are":[60],"estimated":[61],"only":[62],"at":[63],"sparse":[65],"set":[66],"keyframes":[68],"lightweight":[71],"module,":[72],"further":[73],"reducing":[74],"memory":[75],"runtime":[77],"costs.":[78],"Experiments":[79],"four":[81],"benchmark":[82],"datasets":[83],"-":[84,90],"Breakfast,":[85],"GTEA,":[86],"50Salads,":[87],"Assembly101":[89],"show":[91],"achieves":[95],"superior":[96],"accuracy":[97],"with":[98],"fewer":[99],"lower":[102],"computational":[103],"complexity":[104],"than":[105],"existing":[106],"approaches.":[107]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2026-02-24T00:00:00"}
