{"id":"https://openalex.org/W4402916933","doi":"https://doi.org/10.1109/icip51287.2024.10647664","title":"Towards Robust Person Re-Identification Via Efficient and Generalized Adversarial Training","display_name":"Towards Robust Person Re-Identification Via Efficient and Generalized Adversarial Training","publication_year":2024,"publication_date":"2024-09-27","ids":{"openalex":"https://openalex.org/W4402916933","doi":"https://doi.org/10.1109/icip51287.2024.10647664"},"language":"en","primary_location":{"id":"doi:10.1109/icip51287.2024.10647664","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip51287.2024.10647664","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":"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/A5029128743","display_name":"Huiwang Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Huiwang Liu","raw_affiliation_strings":["Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101550628","display_name":"Yan Huang","orcid":"https://orcid.org/0000-0002-8239-7229"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Huang","raw_affiliation_strings":["Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101316414","display_name":"Linlin Zeng","orcid":null},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linlin Zeng","raw_affiliation_strings":["Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110683071","display_name":"Ya Li","orcid":"https://orcid.org/0009-0004-3095-3707"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ya Li","raw_affiliation_strings":["Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I37987034"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5029128743"],"corresponding_institution_ids":["https://openalex.org/I37987034"],"apc_list":null,"apc_paid":null,"fwci":0.2624,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.54167756,"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":"568","last_page":"574"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9872000217437744,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9872000217437744,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9646999835968018,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.961899995803833,"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":0.8993527293205261},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.678506076335907},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.6681041717529297},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6228960156440735},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5114015936851501},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.43837589025497437},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3521937429904938}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8993527293205261},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.678506076335907},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6681041717529297},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6228960156440735},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5114015936851501},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.43837589025497437},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3521937429904938},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip51287.2024.10647664","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip51287.2024.10647664","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":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2096733369","https://openalex.org/W2204750386","https://openalex.org/W2511791013","https://openalex.org/W2543927648","https://openalex.org/W2810967842","https://openalex.org/W2963047834","https://openalex.org/W2963842104","https://openalex.org/W2990827756","https://openalex.org/W2997502936","https://openalex.org/W2998792609","https://openalex.org/W3036280328","https://openalex.org/W3093070413","https://openalex.org/W3136038792","https://openalex.org/W3191741720","https://openalex.org/W4214736485","https://openalex.org/W4291653584","https://openalex.org/W4313050726","https://openalex.org/W6640425456","https://openalex.org/W6739868092","https://openalex.org/W6746255304","https://openalex.org/W6761100157","https://openalex.org/W6762775584"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W4394050964","https://openalex.org/W3211393740","https://openalex.org/W3208049411","https://openalex.org/W3022908591","https://openalex.org/W4285706568","https://openalex.org/W2551249631"],"abstract_inverted_index":{"Person":[0],"re-identification":[1],"(ReID)":[2],"is":[3,17,125],"a":[4],"particular":[5],"cross-camera":[6],"person":[7],"retrieval":[8],"problem":[9],"that":[10,89],"involves":[11],"non-overlapping":[12],"cameras.":[13],"Adversarial":[14],"training":[15,77,123,130,145,166,186],"(AT)":[16],"known":[18],"to":[19,82,91],"dramatically":[20],"increase":[21],"the":[22,30,39,45,63,87,92,106,129,141,146,153,181,184,191,197],"robustness":[23,95,192],"of":[24,33,41,94,96,132,143,155,183,196],"deep":[25],"neural":[26],"network-based":[27],"ReID.":[28],"Unfortunately,":[29],"high":[31],"cost":[32,142],"adversarial":[34,55,76,101,122,136,144,176],"samples":[35,56,164],"generation":[36],"process":[37],"makes":[38],"application":[40],"AT":[42,49],"impractical.":[43],"Moreover,":[44],"model":[46,64,171,185],"trained":[47,60],"by":[48,58,127,174],"has":[50],"poor":[51],"generalization.":[52],"For":[53],"unfamiliar":[54],"generated":[57],"non-AT":[59],"attack":[61,102],"methods,":[62],"may":[65],"recognize":[66],"them":[67],"incorrectly.":[68],"In":[69,151],"this":[70,109],"work,":[71],"we":[72],"proposed":[73,126],"an":[74,120],"efficient":[75,121],"method":[78,124,131],"for":[79,108,158,165],"ReID":[80,98],"tasks":[81],"address":[83],"these":[84],"issues.":[85],"Firstly,":[86],"factors":[88],"lead":[90],"lack":[93],"current":[97],"models":[99],"under":[100],"are":[103,111,167],"explored,":[104],"and":[105,114,160,193],"reasons":[107],"phenomenon":[110],"experimentally":[112],"analyzed":[113],"discussed.":[115],"Based":[116],"on":[117],"our":[118],"explorations,":[119],"combining":[128],"Free-AT":[133],"with":[134],"universal":[135],"perturbation":[137],"(UAP),":[138],"while":[139],"keeping":[140],"same":[147],"as":[148,188,190],"normal":[149],"training.":[150],"addition,":[152],"strategies":[154],"random":[156],"restart":[157],"UAP":[159],"partially":[161],"retaining":[162],"clean":[163],"proposed,":[168],"which":[169],"improve":[170],"generalization":[172,194],"ability":[173,195],"diversifying":[175],"samples.":[177],"Extensive":[178],"experiments":[179],"demonstrate":[180],"efficiency":[182],"process,":[187],"well":[189],"model.":[198]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}