{"id":"https://openalex.org/W4394596960","doi":"https://doi.org/10.1109/wacv57701.2024.00676","title":"Weakly-Supervised Representation Learning for Video Alignment and Analysis","display_name":"Weakly-Supervised Representation Learning for Video Alignment and Analysis","publication_year":2024,"publication_date":"2024-01-03","ids":{"openalex":"https://openalex.org/W4394596960","doi":"https://doi.org/10.1109/wacv57701.2024.00676"},"language":"en","primary_location":{"id":"doi:10.1109/wacv57701.2024.00676","doi":"https://doi.org/10.1109/wacv57701.2024.00676","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv57701.2024.00676","pdf_url":null,"source":{"id":"https://openalex.org/S4393918690","display_name":"IEEE Winter Conference on Applications of Computer Vision","issn_l":"2472-6737","issn":["2472-6737"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"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":"2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2302.04064","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070125882","display_name":"Guy Bar-Shalom","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405267758","display_name":"Verily Life Sciences LLC (United States)","ror":"https://ror.org/047305x76","country_code":"US","type":"company","lineage":["https://openalex.org/I4405267758"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guy Bar-Shalom","raw_affiliation_strings":["Verily"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Verily","institution_ids":["https://openalex.org/I4405267758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020974986","display_name":"George Leifman","orcid":"https://orcid.org/0000-0003-0819-1692","observed_orcids":["https://orcid.org/0000-0003-0819-1692"]},"institutions":[{"id":"https://openalex.org/I4405267758","display_name":"Verily Life Sciences LLC (United States)","ror":"https://ror.org/047305x76","country_code":"US","type":"company","lineage":["https://openalex.org/I4405267758"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"George Leifman","raw_affiliation_strings":["Verily"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Verily","institution_ids":["https://openalex.org/I4405267758"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020279598","display_name":"Michael Elad","orcid":"https://orcid.org/0000-0001-8131-6928","observed_orcids":["https://orcid.org/0000-0001-8131-6928"]},"institutions":[{"id":"https://openalex.org/I4405267758","display_name":"Verily Life Sciences LLC (United States)","ror":"https://ror.org/047305x76","country_code":"US","type":"company","lineage":["https://openalex.org/I4405267758"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Elad","raw_affiliation_strings":["Verily"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Verily","institution_ids":["https://openalex.org/I4405267758"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4405267758"],"apc_list":null,"apc_paid":null,"fwci":0.4344,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.67470471,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"6895","last_page":"6904"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9301999807357788,"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":0.9301999807357788,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.01769999973475933,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.012600000016391277,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/video-alignment","display_name":"video alignment","score":0.6700000166893005},{"id":"https://openalex.org/keywords/temporal-alignment","display_name":"temporal alignment","score":0.8539999723434448},{"id":"https://openalex.org/keywords/kl-divergence-minimization","display_name":"KL divergence minimization","score":0.8550000190734863},{"id":"https://openalex.org/keywords/transformer-encoder","display_name":"Transformer encoder","score":0.8859999775886536},{"id":"https://openalex.org/keywords/video-analysis","display_name":"video analysis","score":0.42399999499320984}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7546030282974243},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6066975593566895},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.588794469833374},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3683937191963196},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36839282512664795},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32931652665138245},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/wacv57701.2024.00676","doi":"https://doi.org/10.1109/wacv57701.2024.00676","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv57701.2024.00676","pdf_url":null,"source":{"id":"https://openalex.org/S4393918690","display_name":"IEEE Winter Conference on Applications of Computer Vision","issn_l":"2472-6737","issn":["2472-6737"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"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":"2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2302.04064","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2302.04064","pdf_url":"https://arxiv.org/pdf/2302.04064","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2302.04064","doi":"https://doi.org/10.48550/arxiv.2302.04064","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2302.04064","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2302.04064","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2302.04064","pdf_url":"https://arxiv.org/pdf/2302.04064","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4394596960.pdf","grobid_xml":"https://content.openalex.org/works/W4394596960.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W116902681","https://openalex.org/W343636949","https://openalex.org/W1522734439","https://openalex.org/W2008056655","https://openalex.org/W2116435618","https://openalex.org/W2137591992","https://openalex.org/W2194775991","https://openalex.org/W2321533354","https://openalex.org/W2326925005","https://openalex.org/W2487442924","https://openalex.org/W2518108298","https://openalex.org/W2591724398","https://openalex.org/W2619082050","https://openalex.org/W2626778328","https://openalex.org/W2769112066","https://openalex.org/W2918597803","https://openalex.org/W2937170809","https://openalex.org/W2949099979","https://openalex.org/W2953327099","https://openalex.org/W2963642716","https://openalex.org/W2963814513","https://openalex.org/W2964700958","https://openalex.org/W2986407524","https://openalex.org/W3001201412","https://openalex.org/W3005680577","https://openalex.org/W3035392611","https://openalex.org/W3036982689","https://openalex.org/W3042142460","https://openalex.org/W3109304426","https://openalex.org/W3126337037","https://openalex.org/W3147387781","https://openalex.org/W3147426949","https://openalex.org/W3159481202","https://openalex.org/W3162194961","https://openalex.org/W3174902251","https://openalex.org/W3214448253","https://openalex.org/W4224329855","https://openalex.org/W4224916651","https://openalex.org/W4226195309","https://openalex.org/W4289926852","https://openalex.org/W4298846483","https://openalex.org/W4312794305","https://openalex.org/W4312875607","https://openalex.org/W4313196251","https://openalex.org/W4362468962","https://openalex.org/W4386065447","https://openalex.org/W4386076413","https://openalex.org/W7133218718"],"related_works":["https://openalex.org/W3147426949","https://openalex.org/W4403780440","https://openalex.org/W3162194961","https://openalex.org/W4386065447","https://openalex.org/W4304084190","https://openalex.org/W4310885433","https://openalex.org/W4366197251","https://openalex.org/W4312247461","https://openalex.org/W2747016289","https://openalex.org/W3166187739"],"abstract_inverted_index":{"Many":[0],"tasks":[1],"in":[2,52,105],"video":[3,113,183],"analysis":[4,184],"and":[5,28,43,96],"understanding":[6],"boil":[7],"down":[8],"to":[9,17,25,49,107,119],"the":[10,19,50,71,81,98,102,109,124,135,138,156,166,169],"need":[11],"for":[12,35,92,153],"frame-based":[13],"feature":[14],"learning,":[15],"aiming":[16],"encapsulate":[18],"relevant":[20],"visual":[21],"content":[22],"so":[23],"as":[24,120],"enable":[26],"simpler":[27],"easier":[29],"subsequent":[30],"processing.":[31],"While":[32],"supervised":[33],"strategies":[34],"this":[36],"learning":[37,65,162],"task":[38],"can":[39],"be":[40],"envisioned,":[41],"self":[42],"weakly-supervised":[44,63],"alternatives":[45],"are":[46,132],"preferred":[47],"due":[48],"difficulties":[51],"getting":[53],"labeled":[54],"data.":[55],"This":[56],"paper":[57],"introduces":[58],"LRProp":[59],"\u2013":[60],"a":[61,89,116,149,176],"novel":[62,160],"representation":[64,161],"approach,":[66],"with":[67,134],"an":[68],"emphasis":[69],"on":[70,171],"application":[72],"of":[73,78,80,127,137,168],"temporal":[74,172],"alignment":[75,110,173],"between":[76,112],"pairs":[77],"videos":[79],"same":[82],"action":[83],"category.":[84],"The":[85,144],"proposed":[86,145],"approach":[87],"uses":[88,147],"transformer":[90],"encoder":[91],"extracting":[93],"frame-level":[94,139],"features,":[95],"employs":[97],"DTW":[99],"algorithm":[100,146],"within":[101],"training":[103],"iterations":[104],"order":[106],"identify":[108],"path":[111],"pairs.":[114],"Through":[115],"process":[117],"referred":[118],"\"pair-wise":[121],"position":[122],"propagation\",":[123],"probability":[125],"distributions":[126],"these":[128],"correspondences":[129],"per":[130],"location":[131],"matched":[133],"similarity":[136],"features":[140],"via":[141],"KL-divergence":[142],"minimization.":[143],"also":[148],"regularized":[150],"SoftDTW":[151],"loss":[152],"better":[154],"tuning":[155],"learned":[157],"features.":[158],"Our":[159],"paradigm":[163],"consistently":[164],"outperforms":[165],"state":[167],"art":[170],"tasks,":[174],"establishing":[175],"new":[177],"performance":[178],"bar":[179],"over":[180],"several":[181],"downstream":[182],"applications.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2024-04-10T00:00:00"}