{"id":"https://openalex.org/W3191777533","doi":"https://doi.org/10.24963/ijcai.2021/477","title":"Multi-Target Invisibly Trojaned Networks for Visual Recognition and Detection","display_name":"Multi-Target Invisibly Trojaned Networks for Visual Recognition and Detection","publication_year":2021,"publication_date":"2021-08-01","ids":{"openalex":"https://openalex.org/W3191777533","doi":"https://doi.org/10.24963/ijcai.2021/477","mag":"3191777533"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2021/477","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2021/477","pdf_url":"https://www.ijcai.org/proceedings/2021/0477.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2021/0477.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102328626","display_name":"Xinzhe Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinzhe Zhou","raw_affiliation_strings":["Peking University","Wangxuan Institute of Computer Technology, Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Wangxuan Institute of Computer Technology, Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024453719","display_name":"Wenhao Jiang","orcid":"https://orcid.org/0000-0002-0795-366X"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenhao Jiang","raw_affiliation_strings":["Tencent AI Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent AI Lab","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040032951","display_name":"Sheng Qi","orcid":"https://orcid.org/0000-0003-1872-9572"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sheng Qi","raw_affiliation_strings":["Peking University","Wangxuan Institute of Computer Technology, Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Wangxuan Institute of Computer Technology, Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028877572","display_name":"Yadong Mu","orcid":"https://orcid.org/0000-0001-7815-3750"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yadong Mu","raw_affiliation_strings":["Peking University","Wangxuan Institute of Computer Technology, Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Wangxuan Institute of Computer Technology, Peking University","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2799,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.63925368,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"3462","last_page":"3469"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998999834060669,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","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/T12357","display_name":"Digital Media Forensic Detection","score":0.9950000047683716,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9833999872207642,"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/computer-science","display_name":"Computer science","score":0.7790870666503906},{"id":"https://openalex.org/keywords/backdoor","display_name":"Backdoor","score":0.7159475088119507},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6361533403396606},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.5494241118431091},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5339257717132568},{"id":"https://openalex.org/keywords/merge","display_name":"Merge (version control)","score":0.5256040096282959},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46455830335617065},{"id":"https://openalex.org/keywords/watermark","display_name":"Watermark","score":0.4539298117160797},{"id":"https://openalex.org/keywords/steganography","display_name":"Steganography","score":0.4520846903324127},{"id":"https://openalex.org/keywords/trojan","display_name":"Trojan","score":0.43142417073249817},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.415961891412735},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.415056049823761},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.407296359539032},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.1527201235294342},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10333266854286194}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7790870666503906},{"id":"https://openalex.org/C2781045450","wikidata":"https://www.wikidata.org/wiki/Q254569","display_name":"Backdoor","level":2,"score":0.7159475088119507},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6361533403396606},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.5494241118431091},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5339257717132568},{"id":"https://openalex.org/C197129107","wikidata":"https://www.wikidata.org/wiki/Q1921621","display_name":"Merge (version control)","level":2,"score":0.5256040096282959},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46455830335617065},{"id":"https://openalex.org/C164112704","wikidata":"https://www.wikidata.org/wiki/Q7974348","display_name":"Watermark","level":3,"score":0.4539298117160797},{"id":"https://openalex.org/C108801101","wikidata":"https://www.wikidata.org/wiki/Q15032","display_name":"Steganography","level":3,"score":0.4520846903324127},{"id":"https://openalex.org/C174333608","wikidata":"https://www.wikidata.org/wiki/Q19635","display_name":"Trojan","level":2,"score":0.43142417073249817},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.415961891412735},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.415056049823761},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.407296359539032},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.1527201235294342},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10333266854286194},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2021/477","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2021/477","pdf_url":"https://www.ijcai.org/proceedings/2021/0477.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2021/477","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2021/477","pdf_url":"https://www.ijcai.org/proceedings/2021/0477.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.41999998688697815,"display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G2492716755","display_name":null,"funder_award_id":"61772037","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320316083","display_name":"Tencent","ror":"https://ror.org/00hhjss72"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3191777533.pdf","grobid_xml":"https://content.openalex.org/works/W3191777533.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1821462560","https://openalex.org/W1861492603","https://openalex.org/W1901129140","https://openalex.org/W2031489346","https://openalex.org/W2047643928","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2543927648","https://openalex.org/W2748789698","https://openalex.org/W2753783305","https://openalex.org/W2771036112","https://openalex.org/W2774423163","https://openalex.org/W2807363941","https://openalex.org/W2810065831","https://openalex.org/W2934843808","https://openalex.org/W2952898583","https://openalex.org/W2963001136","https://openalex.org/W2964121744","https://openalex.org/W2970335439","https://openalex.org/W2996800219","https://openalex.org/W3034414373","https://openalex.org/W3042368254","https://openalex.org/W3044223678","https://openalex.org/W3081178496","https://openalex.org/W3106250896","https://openalex.org/W3107337211","https://openalex.org/W4287998266"],"related_works":["https://openalex.org/W4320031223","https://openalex.org/W4200629851","https://openalex.org/W4281902577","https://openalex.org/W3135176461","https://openalex.org/W3106646114","https://openalex.org/W4308244459","https://openalex.org/W4221166349","https://openalex.org/W4200628936","https://openalex.org/W4387929148","https://openalex.org/W4389518867"],"abstract_inverted_index":{"Visual":[0],"backdoor":[1],"attack":[2,89,105],"is":[3],"a":[4,13,22,26,35,50,56,103,118,125,133,143,159,165,223,241],"recently-emerging":[5],"task":[6],"which":[7],"aims":[8],"to":[9,21,39,149,192,222],"implant":[10],"trojans":[11],"in":[12,25,45,92,121,124],"deep":[14],"neural":[15],"model.":[16,167,185,225],"A":[17],"trojaned":[18,79,166],"model":[19,217],"responds":[20],"trojan-invoking":[23],"trigger":[24,109],"fully":[27],"predictable":[28],"manner":[29],"while":[30],"functioning":[31],"normally":[32],"otherwise.":[33],"As":[34],"key":[36],"motivating":[37],"fact":[38],"this":[40,66],"work,":[41,67],"most":[42],"triggers":[43,138],"adopted":[44],"existing":[46],"methods,":[47],"such":[48,203],"as":[49,74,111],"learned":[51],"patterned":[52],"block":[53],"that":[54,81,116,153,204],"overlays":[55],"benigh":[57],"image,":[58],"can":[59,87,139],"be":[60,140],"easily":[61],"noticed":[62],"by":[63],"human.":[64],"In":[65,131],"we":[68,107,157,189],"take":[69],"image":[70,113,120,123,146,178],"recognition":[71,179],"and":[72,86,127,147,214,235,240],"detection":[73,181],"the":[75,184,197,200,205,215,231,251],"demonstration":[76],"tasks,":[77],"building":[78],"networks":[80],"are":[82,99,169,228],"significantly":[83],"less":[84],"human-perceptible":[85],"simultaneously":[88],"multiple":[90],"targets":[91],"an":[93,112,150],"image.":[94],"The":[95],"main":[96],"technical":[97],"contributions":[98],"two-folds:":[100],"first,":[101],"under":[102],"relaxed":[104],"mode,":[106],"formulate":[108],"embedding":[110],"steganography-and-steganalysis":[114],"problem":[115],"conceals":[117],"secret":[119,145],"another":[122],"decipherable":[126],"almost":[128],"invisible":[129],"way.":[130],"specific,":[132],"variable":[134],"number":[135],"of":[136,199,243,253],"different":[137],"encoded":[141],"into":[142,171],"same":[144],"fed":[148],"encoder":[151],"module":[152],"does":[154],"steganography.":[155],"Secondly,":[156],"propose":[158,191],"generic":[160],"split-and-merge":[161],"scheme":[162],"for":[163,176],"training":[164],"Neurons":[168],"split":[170],"two":[172,206],"sets,":[173],"trained":[174],"either":[175],"normal":[177,201],"/":[180],"or":[182],"trojaning":[183],"To":[186],"merge":[187],"them,":[188],"novelly":[190],"hide":[193],"trojan":[194,257],"neurons":[195],"within":[196],"nullspace":[198],"ones,":[202],"sets":[207],"do":[208],"not":[209],"interfere":[210],"with":[211],"each":[212],"other":[213],"resultant":[216],"exhibits":[218],"similar":[219],"parameter":[220],"statistics":[221],"clean":[224],"Comprehensive":[226],"experiments":[227],"conducted":[229],"on":[230],"datasets":[232],"PASCAL":[233],"VOC":[234],"Microsoft":[236],"COCO":[237],"(for":[238,245],"detection)":[239],"subset":[242],"ImageNet":[244],"recognition).":[246],"All":[247],"results":[248],"clearly":[249],"demonstrate":[250],"effectiveness":[252],"our":[254],"proposed":[255],"visual":[256],"method.":[258]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}