{"id":"https://openalex.org/W7131622971","doi":"https://doi.org/10.48550/arxiv.2602.22073","title":"AdaSpot: Spend Resolution Where It Matters for Precise Event Spotting","display_name":"AdaSpot: Spend Resolution Where It Matters for Precise Event Spotting","publication_year":2026,"publication_date":"2026-02-25","ids":{"openalex":"https://openalex.org/W7131622971","doi":"https://doi.org/10.48550/arxiv.2602.22073"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.22073","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085424296","display_name":"Artur Xarles","orcid":"https://orcid.org/0000-0002-0800-0270"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xarles, Artur","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126931712","display_name":"Sergio Escalera","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Escalera, Sergio","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126886385","display_name":"Thomas B. Moeslund","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Moeslund, Thomas B.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5126863742","display_name":"Albert Clap\u00e9s","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Clap\u00e9s, Albert","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":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2425229,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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":0.9088000059127808,"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":0.9088000059127808,"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":0.011500000022351742,"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":0.010999999940395355,"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/spotting","display_name":"Spotting","score":0.6899999976158142},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.6294000148773193},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5407999753952026},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.48159998655319214},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.4805000126361847},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.47760000824928284},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.46059998869895935},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.44519999623298645},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.42399999499320984}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7954999804496765},{"id":"https://openalex.org/C2779506182","wikidata":"https://www.wikidata.org/wiki/Q7580141","display_name":"Spotting","level":2,"score":0.6899999976158142},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.6294000148773193},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5407999753952026},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5209000110626221},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.48159998655319214},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.4805000126361847},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.47760000824928284},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.46059998869895935},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.44519999623298645},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.42399999499320984},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4081999957561493},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3978999853134155},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.39309999346733093},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.3910999894142151},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36390000581741333},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3379000127315521},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.3366999924182892},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3165000081062317},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.31459999084472656},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.29030001163482666},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.28600001335144043},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.2809999883174896},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.2786000072956085},{"id":"https://openalex.org/C2781213101","wikidata":"https://www.wikidata.org/wiki/Q6398558","display_name":"Keyword spotting","level":2,"score":0.26030001044273376},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.2531999945640564},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.2526000142097473},{"id":"https://openalex.org/C2776544517","wikidata":"https://www.wikidata.org/wiki/Q189447","display_name":"Unexpected events","level":2,"score":0.2524000108242035},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.25060001015663147}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.22073","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.22073","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.22073","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"pmh:doi:10.48550/arxiv.2602.22073","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Precise":[0],"Event":[1],"Spotting":[2],"aims":[3],"to":[4,45,86,140],"localize":[5],"fast-paced":[6],"actions":[7],"or":[8],"events":[9],"in":[10,21,40,98],"videos":[11,85],"with":[12,134],"high":[13],"temporal":[14],"precision,":[15],"a":[16,77,135],"key":[17],"task":[18],"for":[19,67,101],"applications":[20],"sports":[22],"analytics,":[23],"robotics,":[24],"and":[25,119,169,175],"autonomous":[26],"systems.":[27],"Existing":[28],"methods":[29],"typically":[30],"process":[31],"all":[32],"frames":[33,118,172],"uniformly,":[34],"overlooking":[35],"the":[36,94,121],"inherent":[37],"spatio-temporal":[38,115],"redundancy":[39],"video":[41],"data.":[42],"This":[43,127],"leads":[44],"redundant":[46],"computation":[47],"on":[48,153,173],"non-informative":[49],"regions":[50],"while":[51,91,143,177],"limiting":[52],"overall":[53],"efficiency.":[54],"To":[55,70],"remain":[56],"tractable,":[57],"they":[58],"often":[59],"spatially":[60],"downsample":[61],"inputs,":[62],"losing":[63],"fine-grained":[64,131],"details":[65],"crucial":[66],"precise":[68],"localization.":[69],"address":[71],"these":[72],"limitations,":[73],"we":[74],"propose":[75],"\\textbf{AdaSpot},":[76],"simple":[78],"yet":[79],"effective":[80],"framework":[81],"that":[82,113,158],"processes":[83],"low-resolution":[84],"extract":[87],"global":[88],"task-relevant":[89],"features":[90],"adaptively":[92],"selecting":[93],"most":[95],"informative":[96],"region-of-interest":[97],"each":[99],"frame":[100],"high-resolution":[102,150],"processing.":[103,151],"The":[104],"selection":[105],"is":[106,186],"performed":[107],"via":[108],"an":[109],"unsupervised,":[110],"task-aware":[111],"strategy":[112],"maintains":[114],"consistency":[116],"across":[117],"avoids":[120],"training":[122],"instability":[123],"of":[124],"learnable":[125],"alternatives.":[126],"design":[128],"preserves":[129],"essential":[130],"visual":[132],"cues":[133],"marginal":[136],"computational":[137],"overhead":[138],"compared":[139],"low-resolution-only":[141],"baselines,":[142],"remaining":[144],"far":[145],"more":[146],"efficient":[147],"than":[148],"uniform":[149],"Experiments":[152],"standard":[154],"PES":[155],"benchmarks":[156],"demonstrate":[157],"\\textbf{AdaSpot}":[159],"achieves":[160],"state-of-the-art":[161],"performance":[162],"under":[163,182],"strict":[164],"evaluation":[165],"metrics":[166],"(\\eg,":[167],"$+3.96$":[168],"$+2.26$":[170],"mAP$@0$":[171],"Tennis":[174],"FineDiving),":[176],"also":[178],"maintaining":[179],"strong":[180],"results":[181],"looser":[183],"metrics.":[184],"Code":[185],"available":[187],"at:":[188],"\\href{https://github.com/arturxe2/AdaSpot}{https://github.com/arturxe2/AdaSpot}.":[189]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2026-02-27T00:00:00"}