{"id":"https://openalex.org/W3200923879","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534067","title":"Hiding All Labels for Multi-label Images: An Empirical Study of Adversarial Examples","display_name":"Hiding All Labels for Multi-label Images: An Empirical Study of Adversarial Examples","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3200923879","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534067","mag":"3200923879"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9534067","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534067","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","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/A5112724994","display_name":"Nan Zhou","orcid":"https://orcid.org/0009-0004-9674-3518"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Nan Zhou","raw_affiliation_strings":["School of Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001184471","display_name":"Wenjian Luo","orcid":"https://orcid.org/0000-0002-8357-1655"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjian Luo","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, Guangdong, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100417632","display_name":"Jiajia Zhang","orcid":"https://orcid.org/0000-0001-6611-2046"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiajia Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, Guangdong, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029027632","display_name":"Linghao Kong","orcid":"https://orcid.org/0000-0003-4077-5671"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linghao Kong","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, Guangdong, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063940168","display_name":"Hongwei Zhang","orcid":"https://orcid.org/0000-0002-8818-0207"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongwei Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, Guangdong, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5112724994"],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":1.4956,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.85764658,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9997000098228455,"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":0.9997000098228455,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9606999754905701,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9526000022888184,"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/adversarial-system","display_name":"Adversarial system","score":0.9328928589820862},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7401156425476074},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5920740962028503},{"id":"https://openalex.org/keywords/nothing","display_name":"Nothing","score":0.5658950805664062},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.558495819568634},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5152271389961243},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.5059437155723572},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16396024823188782},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06059911847114563}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.9328928589820862},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7401156425476074},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5920740962028503},{"id":"https://openalex.org/C136815107","wikidata":"https://www.wikidata.org/wiki/Q154242","display_name":"Nothing","level":2,"score":0.5658950805664062},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.558495819568634},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5152271389961243},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.5059437155723572},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16396024823188782},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06059911847114563},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9534067","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534067","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1647000430","display_name":null,"funder_award_id":"2020YFB2104003","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8760170119","display_name":null,"funder_award_id":"61573327","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":57,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W1632601927","https://openalex.org/W1673923490","https://openalex.org/W1861492603","https://openalex.org/W1945616565","https://openalex.org/W2007972815","https://openalex.org/W2031489346","https://openalex.org/W2064675550","https://openalex.org/W2180612164","https://openalex.org/W2243397390","https://openalex.org/W2250539671","https://openalex.org/W2460937040","https://openalex.org/W2503523779","https://openalex.org/W2519887557","https://openalex.org/W2736688973","https://openalex.org/W2765424254","https://openalex.org/W2774644650","https://openalex.org/W2810192346","https://openalex.org/W2916286792","https://openalex.org/W2932399282","https://openalex.org/W2943671295","https://openalex.org/W2951527505","https://openalex.org/W2962711307","https://openalex.org/W2963207607","https://openalex.org/W2963306618","https://openalex.org/W2963351448","https://openalex.org/W2963355098","https://openalex.org/W2963745697","https://openalex.org/W2963857521","https://openalex.org/W2964015378","https://openalex.org/W2964153729","https://openalex.org/W2964253222","https://openalex.org/W2964321699","https://openalex.org/W2970971581","https://openalex.org/W3090578762","https://openalex.org/W3090605776","https://openalex.org/W3103557498","https://openalex.org/W3118608800","https://openalex.org/W4214673031","https://openalex.org/W4293846201","https://openalex.org/W4295312788","https://openalex.org/W4298312696","https://openalex.org/W4300511536","https://openalex.org/W4300725094","https://openalex.org/W6637162671","https://openalex.org/W6639102338","https://openalex.org/W6640425456","https://openalex.org/W6682137061","https://openalex.org/W6719080892","https://openalex.org/W6720006811","https://openalex.org/W6725195833","https://openalex.org/W6726873649","https://openalex.org/W6739868092","https://openalex.org/W6741440215","https://openalex.org/W6752946794","https://openalex.org/W6759204839","https://openalex.org/W6766978945"],"related_works":["https://openalex.org/W2216420239","https://openalex.org/W3011492772","https://openalex.org/W2499122376","https://openalex.org/W2800570524","https://openalex.org/W2808813869","https://openalex.org/W2109915140","https://openalex.org/W2315519183","https://openalex.org/W2103493327","https://openalex.org/W4380075502","https://openalex.org/W4366307084"],"abstract_inverted_index":{"Adversarial":[0],"examples":[1,17,145,184],"about":[2,66],"deep":[3,61,76],"learning":[4,62,77],"models":[5,63,78,122],"have":[6],"been":[7],"paid":[8],"much":[9],"attention":[10],"in":[11,42,54,171],"recent":[12],"years,":[13],"including":[14],"single-label":[15],"adversarial":[16,20,36,144,183],"and":[18,117,119,124,132],"multi-label":[19,35,44,56,101,149,182],"examples.":[21],"In":[22,93],"this":[23,172],"paper,":[24],"for":[25,126],"the":[26,67,85,94,134,138,143,155,177],"first":[27],"time,":[28],"an":[29],"empirical":[30,95],"study":[31,179],"of":[32,50,73,140,142,180],"generating":[33,181],"a":[34,43,55,159],"example":[37,45,57],"to":[38,59,176],"hide":[39],"all":[40,52],"labels":[41,53],"is":[46,58,70,82,167,174],"presented.":[47],"The":[48,169],"objective":[49],"hiding":[51],"make":[60],"know":[64],"nothing":[65],"environments.":[68],"That":[69],"very":[71],"worthy":[72],"studying":[74],"because":[75],"will":[79],"say":[80],"there":[81],"nothing,":[83],"although":[84],"real":[86],"input":[87],"has":[88],"more":[89],"than":[90],"one":[91],"label.":[92],"study,":[96],"we":[97],"use":[98],"five":[99],"state-of-the-art":[100,148],"attack":[102,135,150,156],"algorithms,":[103],"i.e.,":[104,113],"ML-CW,":[105],"ML-DP,":[106],"FGSM,":[107],"MI-FGSM,":[108],"MLA-LP,":[109],"four":[110],"popular":[111],"datasets,":[112],"VOC2007,":[114],"VOC2012,":[115],"NUS-WIDE":[116],"COCO,":[118],"two":[120],"typical":[121,160],"ML-GCN":[123],"ASL":[125],"evaluation.":[127],"We":[128,152],"conduct":[129],"extensive":[130],"experiments":[131],"report":[133,154],"success":[136],"rates,":[137],"amount":[139],"perturbations":[141],"generated":[146],"by":[147],"algorithms.":[151],"also":[153],"performance":[157],"when":[158],"defending":[161,188],"algorithm":[162],"based":[163],"on":[164],"JPEG":[165],"compression":[166],"used.":[168],"work":[170],"paper":[173],"beneficial":[175],"future":[178],"as":[185,187],"well":[186],"them.":[189]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
