{"id":"https://openalex.org/W4297330561","doi":"https://doi.org/10.1145/3552469.3555715","title":"Adversarial Attacks Against Blind Image Quality Assessment Models","display_name":"Adversarial Attacks Against Blind Image Quality Assessment Models","publication_year":2022,"publication_date":"2022-09-27","ids":{"openalex":"https://openalex.org/W4297330561","doi":"https://doi.org/10.1145/3552469.3555715"},"language":"en","primary_location":{"id":"doi:10.1145/3552469.3555715","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3552469.3555715","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd Workshop on Quality of Experience in Visual Multimedia Applications","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/A5103007977","display_name":"Jari Korhonen","orcid":"https://orcid.org/0000-0003-4354-5310"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jari Korhonen","raw_affiliation_strings":["Shenzhen University, Shenzhen , China"],"affiliations":[{"raw_affiliation_string":"Shenzhen University, Shenzhen , China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052816488","display_name":"Junyong You","orcid":"https://orcid.org/0000-0002-4288-5244"},"institutions":[{"id":"https://openalex.org/I4210107808","display_name":"NORCE Norwegian Research Centre","ror":"https://ror.org/02gagpf75","country_code":"NO","type":"facility","lineage":["https://openalex.org/I4210107808"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Junyong You","raw_affiliation_strings":["Norwegian Research Centre, Bergen, Norway"],"affiliations":[{"raw_affiliation_string":"Norwegian Research Centre, Bergen, Norway","institution_ids":["https://openalex.org/I4210107808"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5103007977"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":1.5099,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.83807003,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9988999962806702,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9988999962806702,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9972000122070312,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9961000084877014,"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/robustness","display_name":"Robustness (evolution)","score":0.7777645587921143},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7238345742225647},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6995078325271606},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5928632020950317},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5533478260040283},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.5324360728263855},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3948121666908264},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36056315898895264},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3573530912399292},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12797164916992188},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.06800535321235657}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7777645587921143},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7238345742225647},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6995078325271606},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5928632020950317},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5533478260040283},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.5324360728263855},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3948121666908264},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36056315898895264},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3573530912399292},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12797164916992188},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.06800535321235657},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3552469.3555715","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3552469.3555715","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd Workshop on Quality of Experience in Visual Multimedia Applications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Gender equality","score":0.5699999928474426,"id":"https://metadata.un.org/sdg/5"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1982471090","https://openalex.org/W2102166818","https://openalex.org/W2125527601","https://openalex.org/W2148848374","https://openalex.org/W2286686646","https://openalex.org/W2603172850","https://openalex.org/W2749468216","https://openalex.org/W2902011469","https://openalex.org/W2997532515","https://openalex.org/W3002992380","https://openalex.org/W3021151504","https://openalex.org/W3036239693","https://openalex.org/W3091249416","https://openalex.org/W3100404621","https://openalex.org/W3102733987","https://openalex.org/W3206968390"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W4246396837","https://openalex.org/W2482350142","https://openalex.org/W3176240006","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4288019534","https://openalex.org/W4310988119"],"abstract_inverted_index":{"Several":[0],"deep":[1,52],"models":[2,29,85,102],"for":[3,62],"blind":[4],"image":[5,22],"quality":[6,23,121],"assessment":[7],"(BIQA)":[8],"have":[9],"been":[10],"proposed":[11],"during":[12],"the":[13,31,48,117],"past":[14],"few":[15],"years,":[16],"with":[17,103,107],"promising":[18],"results":[19,56,97],"on":[20,124],"standard":[21,32],"datasets.":[24],"However,":[25],"generalization":[26],"of":[27,50,112,119],"BIQA":[28,53,66,84,101],"beyond":[30],"content":[33],"remains":[34],"a":[35,63,104],"challenge.":[36],"In":[37],"this":[38],"paper,":[39],"we":[40],"study":[41],"basic":[42,93],"adversarial":[43,59,108],"attack":[44],"techniques":[45],"to":[46,77],"assess":[47],"robustness":[49,111],"representative":[51],"models.":[54],"Our":[55,96],"show":[57],"that":[58,99],"images":[60,109],"created":[61],"simple":[64],"substitute":[65],"model":[67],"(i.e.":[68,86],"white-box":[69],"scenario)":[70],"are":[71],"transferable":[72],"as":[73],"such":[74],"and":[75],"able":[76],"deceive":[78],"also":[79,90],"several":[80,113],"other":[81],"more":[82],"complex":[83],"black-box":[87],"scenario).":[88],"We":[89],"investigated":[91],"some":[92],"defense":[94],"mechanisms.":[95],"indicate":[98],"re-training":[100],"dataset":[105],"augmented":[106],"improves":[110],"models,":[114],"but":[115],"at":[116],"cost":[118],"decreased":[120],"prediction":[122],"accuracy":[123],"genuine":[125],"images.":[126]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
