{"id":"https://openalex.org/W4402917101","doi":"https://doi.org/10.1109/icip51287.2024.10648147","title":"SegGuard: Defending Scene Segmentation Against Adversarial Patch Attack","display_name":"SegGuard: Defending Scene Segmentation Against Adversarial Patch Attack","publication_year":2024,"publication_date":"2024-09-27","ids":{"openalex":"https://openalex.org/W4402917101","doi":"https://doi.org/10.1109/icip51287.2024.10648147"},"language":"en","primary_location":{"id":"doi:10.1109/icip51287.2024.10648147","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icip51287.2024.10648147","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5003556490","display_name":"Thomas Gittings","orcid":"https://orcid.org/0000-0003-3405-9185"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Thomas Gittings","raw_affiliation_strings":["University of Surrey,Centre for Vision Speech and Signal Processing (CVSSP),UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Surrey,Centre for Vision Speech and Signal Processing (CVSSP),UK","institution_ids":["https://openalex.org/I28290843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000838833","display_name":"Steve Schneider","orcid":"https://orcid.org/0000-0001-8365-6993"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Steve Schneider","raw_affiliation_strings":["University of Surrey,Centre for Vision Speech and Signal Processing (CVSSP),UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Surrey,Centre for Vision Speech and Signal Processing (CVSSP),UK","institution_ids":["https://openalex.org/I28290843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024767797","display_name":"John Collomosse","orcid":"https://orcid.org/0000-0003-3580-4685"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"John Collomosse","raw_affiliation_strings":["University of Surrey,Centre for Vision Speech and Signal Processing (CVSSP),UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Surrey,Centre for Vision Speech and Signal Processing (CVSSP),UK","institution_ids":["https://openalex.org/I28290843"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I28290843"],"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":"794","last_page":"800"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9994000196456909,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9994000196456909,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9908000230789185,"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":0.9857000112533569,"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/adversarial-system","display_name":"Adversarial system","score":0.8105918169021606},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7080982327461243},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6289752721786499},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5308042168617249},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5204301476478577},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4707891345024109},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.4577341377735138}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8105918169021606},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7080982327461243},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6289752721786499},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5308042168617249},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5204301476478577},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4707891345024109},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.4577341377735138}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip51287.2024.10648147","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icip51287.2024.10648147","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3834807067","display_name":null,"funder_award_id":"EP/T022485/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W2243397390","https://openalex.org/W2340897893","https://openalex.org/W2618043096","https://openalex.org/W2798302089","https://openalex.org/W2886934227","https://openalex.org/W2890883923","https://openalex.org/W2902867332","https://openalex.org/W2952688212","https://openalex.org/W2963302614","https://openalex.org/W2963542245","https://openalex.org/W2964082701","https://openalex.org/W2964217532","https://openalex.org/W3106679781","https://openalex.org/W3157070795","https://openalex.org/W3196107314","https://openalex.org/W6637162671","https://openalex.org/W6640425456","https://openalex.org/W6729756640","https://openalex.org/W6748204703","https://openalex.org/W6748475379","https://openalex.org/W6751839145","https://openalex.org/W6754363872","https://openalex.org/W6764650336","https://openalex.org/W6766301176","https://openalex.org/W6789654255"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4310988119","https://openalex.org/W4285226279","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Adversarial":[0],"Patch":[1],"Attacks":[2],"(APAs)":[3],"induce":[4],"prediction":[5],"errors":[6],"by":[7,84],"inserting":[8],"carefully":[9],"crafted":[10],"regions":[11],"into":[12],"images.":[13],"This":[14],"paper":[15],"presents":[16],"the":[17,64,76,80,85,90,98],"first":[18],"defence":[19],"against":[20,109],"APAs":[21],"for":[22],"deep":[23],"networks":[24],"that":[25,33,103,113],"perform":[26],"semantic":[27],"segmentation":[28,65],"of":[29,69],"scenes.":[30],"We":[31,57,101],"show":[32,102],"a":[34,70],"conditional":[35],"generator":[36,61,91],"can":[37],"be":[38],"trained":[39],"to":[40,78,92,96,117],"produce":[41,93],"patches":[42,82,95],"on":[43],"demand":[44],"targeting":[45],"specific":[46],"classes":[47],"and":[48,112],"achieving":[49],"superior":[50],"performance":[51],"versus":[52],"conventional":[53],"pixel-optimised":[54,119],"patch":[55],"attacks.":[56],"then":[58],"leverage":[59],"this":[60,114],"along":[62],"with":[63],"network":[66],"as":[67],"part":[68],"generative":[71],"adversarial":[72,81,110,120],"network,":[73],"which":[74],"trains":[75],"model":[77],"ignore":[79],"produced":[83],"generator,":[86],"while":[87],"simultaneously":[88],"training":[89],"updated":[94],"attack":[97],"fine-tuned":[99],"network.":[100],"our":[104],"process":[105],"confers":[106],"strong":[107],"protection":[108,115],"patches,":[111],"generalises":[116],"traditional":[118],"patches.":[121]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}