{"id":"https://openalex.org/W4388118099","doi":"https://doi.org/10.23919/eusipco58844.2023.10290127","title":"Quantitative Evaluation of Video Explainability Methods via Anomaly Localization","display_name":"Quantitative Evaluation of Video Explainability Methods via Anomaly Localization","publication_year":2023,"publication_date":"2023-09-04","ids":{"openalex":"https://openalex.org/W4388118099","doi":"https://doi.org/10.23919/eusipco58844.2023.10290127"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco58844.2023.10290127","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco58844.2023.10290127","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 31st European Signal Processing Conference (EUSIPCO)","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/A5100319962","display_name":"Xinyue Zhang","orcid":"https://orcid.org/0000-0002-4243-083X"},"institutions":[{"id":"https://openalex.org/I13469542","display_name":"Vrije Universiteit Brussel","ror":"https://ror.org/006e5kg04","country_code":"BE","type":"education","lineage":["https://openalex.org/I13469542"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"Xinyue Zhang","raw_affiliation_strings":["Vrije Universiteit Brussel,Department of Electronics and Informatics,Brussels,Belgium,B-1050"],"affiliations":[{"raw_affiliation_string":"Vrije Universiteit Brussel,Department of Electronics and Informatics,Brussels,Belgium,B-1050","institution_ids":["https://openalex.org/I13469542"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072533463","display_name":"Boris Joukovsky","orcid":"https://orcid.org/0000-0002-2881-2727"},"institutions":[{"id":"https://openalex.org/I4210114974","display_name":"IMEC","ror":"https://ror.org/02kcbn207","country_code":"BE","type":"nonprofit","lineage":["https://openalex.org/I4210114974"]},{"id":"https://openalex.org/I13469542","display_name":"Vrije Universiteit Brussel","ror":"https://ror.org/006e5kg04","country_code":"BE","type":"education","lineage":["https://openalex.org/I13469542"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Boris Joukovsky","raw_affiliation_strings":["Vrije Universiteit Brussel,Department of Electronics and Informatics,Brussels,Belgium,B-1050","imec, Leuven, Belgium"],"affiliations":[{"raw_affiliation_string":"Vrije Universiteit Brussel,Department of Electronics and Informatics,Brussels,Belgium,B-1050","institution_ids":["https://openalex.org/I13469542"]},{"raw_affiliation_string":"imec, Leuven, Belgium","institution_ids":["https://openalex.org/I4210114974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043511500","display_name":"Nikos Deligiannis","orcid":"https://orcid.org/0000-0001-9300-5860"},"institutions":[{"id":"https://openalex.org/I13469542","display_name":"Vrije Universiteit Brussel","ror":"https://ror.org/006e5kg04","country_code":"BE","type":"education","lineage":["https://openalex.org/I13469542"]},{"id":"https://openalex.org/I4210114974","display_name":"IMEC","ror":"https://ror.org/02kcbn207","country_code":"BE","type":"nonprofit","lineage":["https://openalex.org/I4210114974"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Nikos Deligiannis","raw_affiliation_strings":["Vrije Universiteit Brussel,Department of Electronics and Informatics,Brussels,Belgium,B-1050","imec, Leuven, Belgium"],"affiliations":[{"raw_affiliation_string":"Vrije Universiteit Brussel,Department of Electronics and Informatics,Brussels,Belgium,B-1050","institution_ids":["https://openalex.org/I13469542"]},{"raw_affiliation_string":"imec, Leuven, Belgium","institution_ids":["https://openalex.org/I4210114974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100319962"],"corresponding_institution_ids":["https://openalex.org/I13469542"],"apc_list":null,"apc_paid":null,"fwci":0.1737,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.5801252,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1235","last_page":"1239"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9900000095367432,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9837999939918518,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.8010629415512085},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.7815508246421814},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7750712633132935},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5878229141235352},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.5821484327316284},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5805652141571045},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5422576069831848},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5228943228721619},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4234165847301483},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.373640775680542},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3526277542114258},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.21478679776191711}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8010629415512085},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.7815508246421814},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7750712633132935},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5878229141235352},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.5821484327316284},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5805652141571045},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5422576069831848},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5228943228721619},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4234165847301483},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.373640775680542},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3526277542114258},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.21478679776191711},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.23919/eusipco58844.2023.10290127","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco58844.2023.10290127","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 31st European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"},{"id":"pmh:oai:vubissmart:VUBISSMART:2000:176617","is_oa":false,"landing_page_url":"https://biblio.vub.ac.be/vubir/quantitative-evaluation-of-video-explainability-methods-via-anomaly-localization(ee5f6288-e73f-46c2-93e0-6e79d6c39292).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306402573","display_name":"VUBIR (Vrije Universiteit Brussel)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I13469542","host_organization_name":"Vrije Universiteit Brussel","host_organization_lineage":["https://openalex.org/I13469542"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"publishedVersion"},{"id":"pmh:oai:vubissmart:VUBISSMART:2000:187499","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306402573","display_name":"VUBIR (Vrije Universiteit Brussel)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I13469542","host_organization_name":"Vrije Universiteit Brussel","host_organization_lineage":["https://openalex.org/I13469542"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1849277567","https://openalex.org/W1967456674","https://openalex.org/W1983364832","https://openalex.org/W2097117768","https://openalex.org/W2123045220","https://openalex.org/W2128687617","https://openalex.org/W2150165932","https://openalex.org/W2342662179","https://openalex.org/W2516809705","https://openalex.org/W2594633041","https://openalex.org/W2766042998","https://openalex.org/W2951183276","https://openalex.org/W2953073956","https://openalex.org/W2962862931","https://openalex.org/W2963524571","https://openalex.org/W2963795951","https://openalex.org/W2973150034","https://openalex.org/W3015115644","https://openalex.org/W3034238521","https://openalex.org/W3085380432","https://openalex.org/W3116286104","https://openalex.org/W3173849000","https://openalex.org/W4293861706","https://openalex.org/W4300235091","https://openalex.org/W4320495618","https://openalex.org/W4321786089","https://openalex.org/W6639204139","https://openalex.org/W6642206748","https://openalex.org/W6677995690","https://openalex.org/W6681608319","https://openalex.org/W6734194636","https://openalex.org/W6737947904","https://openalex.org/W6739575509","https://openalex.org/W6752170072","https://openalex.org/W6754669440","https://openalex.org/W6767937666","https://openalex.org/W6810555789","https://openalex.org/W6850131024"],"related_works":["https://openalex.org/W1667647204","https://openalex.org/W2404647514","https://openalex.org/W4247536566","https://openalex.org/W2018477250","https://openalex.org/W3119814709","https://openalex.org/W4241418540","https://openalex.org/W1508895727","https://openalex.org/W2725786787","https://openalex.org/W1875930651","https://openalex.org/W1590965489"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,18,66],"study":[4],"of":[5,30,44],"explainable":[6],"AI":[7],"methods":[8,25,82,103,112],"applied":[9],"to":[10,22,37,64,85,97],"video":[11,74,98],"anomaly":[12,39],"detection.":[13],"Specifically,":[14],"we":[15,62],"put":[16],"forward":[17],"multidimensional":[19],"evaluation":[20],"protocol":[21],"evaluate":[23,51],"attribution":[24],"by":[26],"considering":[27],"the":[28,31,42,88,92],"correctness":[29],"explanations,":[32],"their":[33],"plausibility":[34],"with":[35],"respect":[36],"ground-truth":[38],"data,":[40],"and":[41,57,91],"robustness":[43,106],"explanations":[45],"across":[46,107],"multiple":[47,108],"time":[48],"frames.":[49],"We":[50],"these":[52],"metrics":[53],"on":[54,72],"common":[55],"gradient-based":[56,102],"perturbation-based":[58],"explanation":[59,89],"techniques,":[60],"which":[61],"use":[63],"explain":[65],"3D":[67],"convolutional":[68],"neural":[69],"network":[70],"trained":[71],"real":[73],"data.":[75,99],"Our":[76],"results":[77],"show":[78],"that":[79],"using":[80],"specific":[81],"generally":[83],"leads":[84],"trade-offs":[86],"between":[87],"performance":[90],"higher":[93,105,114],"computational":[94],"cost":[95],"related":[96],"In":[100],"particular,":[101],"achieve":[104,113],"frames,":[109],"whereas":[110],"perturbation":[111],"model":[115],"fidelity":[116],"scores.":[117]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}