{"id":"https://openalex.org/W7167629454","doi":"https://doi.org/10.48550/arxiv.2607.04684","title":"TubeLite: Lightweight Multi-Actor Spatio-Temporal Action Detection","display_name":"TubeLite: Lightweight Multi-Actor Spatio-Temporal Action Detection","publication_year":2026,"publication_date":"2026-07-06","ids":{"openalex":"https://openalex.org/W7167629454","doi":"https://doi.org/10.48550/arxiv.2607.04684"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.04684","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.04684","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,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.04684","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5117778701","display_name":"Ali Soltaninezhad","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Soltaninezhad, Ali","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033597391","display_name":"Melissa Cote","orcid":"https://orcid.org/0000-0002-5594-977X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cote, Melissa","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064055012","display_name":"Alejandro Rico Espinosa","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Espinosa, Alejandro Rico","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048824702","display_name":"Tunai Porto Marques","orcid":"https://orcid.org/0000-0003-0850-9912"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marques, Tunai Porto","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5036029722","display_name":"Alexandra Branzan Albu","orcid":"https://orcid.org/0000-0001-8991-0999"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Albu, Alexandra Branzan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9758999943733215,"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":0.9758999943733215,"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":0.0071000000461936,"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":0.003599999938160181,"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/bounding-overwatch","display_name":"Bounding overwatch","score":0.6299999952316284},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.5546000003814697},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.42320001125335693},{"id":"https://openalex.org/keywords/temporal-logic","display_name":"Temporal logic","score":0.4147000014781952},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.4034000039100647},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.4027999937534332},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.3862000107765198},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.3806999921798706},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.3614000082015991}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.707099974155426},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.6299999952316284},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.5546000003814697},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5198000073432922},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.42320001125335693},{"id":"https://openalex.org/C25016198","wikidata":"https://www.wikidata.org/wiki/Q781833","display_name":"Temporal logic","level":2,"score":0.4147000014781952},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.4034000039100647},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.4027999937534332},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3862000107765198},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.3806999921798706},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.3614000082015991},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.353300005197525},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.35100001096725464},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.32179999351501465},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3183000087738037},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.313400000333786},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.304500013589859},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30309998989105225},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.29499998688697815},{"id":"https://openalex.org/C162670838","wikidata":"https://www.wikidata.org/wiki/Q6057295","display_name":"Interval temporal logic","level":3,"score":0.2944999933242798},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.2924000024795532},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.28940001130104065},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.27790001034736633},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2712000012397766},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C119666444","wikidata":"https://www.wikidata.org/wiki/Q5977280","display_name":"Temporal resolution","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.258899986743927},{"id":"https://openalex.org/C175291020","wikidata":"https://www.wikidata.org/wiki/Q1156822","display_name":"Offset (computer science)","level":2,"score":0.2574999928474426}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.04684","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.04684","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,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.04684","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.04684","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,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Spatio-temporal":[0],"action":[1,13,24,67,185],"detection":[2,68,186],"in":[3,9],"videos":[4],"requires":[5],"jointly":[6],"localizing":[7],"actors":[8],"space":[10],"and":[11,34,56,75,100,109,126,136,155,167,175],"identifying":[12],"boundaries":[14],"over":[15,98,159],"time.":[16],"A":[17],"common":[18],"challenge":[19],"is":[20],"constructing":[21],"temporally":[22],"stable":[23,72],"tubes,":[25],"as":[26,83,87],"frame-level":[27],"detectors":[28],"often":[29],"suffer":[30],"from":[31],"jitter,":[32],"fragmentation,":[33],"imprecise":[35],"temporal":[36,77,103,124,129,138,193],"localization.":[37],"Many":[38],"recent":[39],"approaches":[40],"address":[41],"this":[42],"by":[43,153],"introducing":[44],"heavy":[45],"spatio-temporal":[46,66,184],"transformers":[47],"or":[48],"optical-flow-based":[49],"pipelines,":[50],"leading":[51],"to":[52],"high":[53],"computational":[54],"cost":[55],"limited":[57],"scalability.":[58],"We":[59],"propose":[60],"TubeLite,":[61],"a":[62,84,88,95,127],"lightweight":[63,192],"framework":[64],"for":[65],"that":[69,182],"focuses":[70],"on":[71,164],"tube":[73],"construction":[74],"boundary-aware":[76],"modeling.":[78,194],"TubeLite":[79,144],"represents":[80],"each":[81],"actor":[82,97,116,119],"tube,":[85],"defined":[86],"sequence":[89],"of":[90],"bounding":[91],"boxes":[92],"associated":[93],"with":[94,171],"single":[96],"time,":[99],"explicitly":[101],"enforces":[102],"consistency":[104],"at":[105],"both":[106],"the":[107,160,165],"spatial":[108],"semantic":[110],"levels.":[111],"The":[112],"method":[113,163],"combines":[114],"low-jitter":[115],"detection,":[117],"Gaussian-weighted":[118],"feature":[120],"extraction,":[121],"efficient":[122],"short-term":[123],"propagation,":[125],"boundary-focused":[128],"prediction":[130],"head,":[131],"while":[132],"avoiding":[133],"optical":[134],"flow":[135],"large-scale":[137],"attention.":[139],"Despite":[140],"its":[141],"compact":[142],"design,":[143],"achieves":[145],"strong":[146],"video-level":[147],"localization":[148],"performance.":[149],"It":[150],"improves":[151],"Video-mAP@0.5":[152],"4.5":[154],"7.1":[156],"percentage":[157],"points":[158],"best":[161],"compared":[162],"MultiSports":[166],"UCF101-24":[168],"datasets,":[169],"respectively,":[170],"substantially":[172],"fewer":[173],"parameters":[174],"floating-point":[176],"operations":[177],"than":[178],"transformer-based":[179],"alternatives,":[180],"demonstrating":[181],"effective":[183],"can":[187],"be":[188],"obtained":[189],"through":[190],"principled,":[191]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-08T00:00:00"}
