{"id":"https://openalex.org/W4414883543","doi":"https://doi.org/10.3390/info16100867","title":"HE-DMDeception: Adversarial Attack Network for 3D Object Detection Based on Human Eye and Deep Learning Model Deception","display_name":"HE-DMDeception: Adversarial Attack Network for 3D Object Detection Based on Human Eye and Deep Learning Model Deception","publication_year":2025,"publication_date":"2025-10-07","ids":{"openalex":"https://openalex.org/W4414883543","doi":"https://doi.org/10.3390/info16100867"},"language":"en","primary_location":{"id":"doi:10.3390/info16100867","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16100867","pdf_url":"https://www.mdpi.com/2078-2489/16/10/867/pdf?version=1759817107","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2078-2489/16/10/867/pdf?version=1759817107","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Pin Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Pin Zhang","raw_affiliation_strings":["Army Engineering University of PLA, Nanjing 210007, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Army Engineering University of PLA, Nanjing 210007, China","institution_ids":["https://openalex.org/I4210163363"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100686869","display_name":"Yawen Liu","orcid":"https://orcid.org/0000-0002-0890-7649"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yawen Liu","raw_affiliation_strings":["Army Engineering University of PLA, Nanjing 210007, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Army Engineering University of PLA, Nanjing 210007, China","institution_ids":["https://openalex.org/I4210163363"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100753323","display_name":"Heng Liu","orcid":"https://orcid.org/0000-0001-7563-2676"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heng Liu","raw_affiliation_strings":["Army Engineering University of PLA, Nanjing 210007, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Army Engineering University of PLA, Nanjing 210007, China","institution_ids":["https://openalex.org/I4210163363"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yichao Teng","orcid":"https://orcid.org/0009-0000-4263-4683"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yichao Teng","raw_affiliation_strings":["National University of Defense Technology, Changsha 410022, China"],"raw_orcid":"https://orcid.org/0009-0000-4263-4683","affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha 410022, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029407848","display_name":"Jiazheng Ni","orcid":null},"institutions":[{"id":"https://openalex.org/I4210140386","display_name":"PLA Navy General Hospital","ror":"https://ror.org/036dyz052","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210140386"]},{"id":"https://openalex.org/I4402554106","display_name":"Naval Research Academy","ror":"https://ror.org/02t42bb94","country_code":null,"type":"education","lineage":["https://openalex.org/I4402554106"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiazheng Ni","raw_affiliation_strings":["Naval Research Institute of PLA, Beijing 100161, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Naval Research Institute of PLA, Beijing 100161, China","institution_ids":["https://openalex.org/I4210140386","https://openalex.org/I4402554106"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030995015","display_name":"Zhuansun Xiaobo","orcid":null},"institutions":[{"id":"https://openalex.org/I4210140386","display_name":"PLA Navy General Hospital","ror":"https://ror.org/036dyz052","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210140386"]},{"id":"https://openalex.org/I4402554106","display_name":"Naval Research Academy","ror":"https://ror.org/02t42bb94","country_code":null,"type":"education","lineage":["https://openalex.org/I4402554106"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuansun Xiaobo","raw_affiliation_strings":["Naval Research Institute of PLA, Beijing 100161, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Naval Research Institute of PLA, Beijing 100161, China","institution_ids":["https://openalex.org/I4210140386","https://openalex.org/I4402554106"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029402556","display_name":"Jiajia Wang","orcid":"https://orcid.org/0000-0002-4666-5652"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiajia Wang","raw_affiliation_strings":["Army Engineering University of PLA, Nanjing 210007, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Army Engineering University of PLA, Nanjing 210007, China","institution_ids":["https://openalex.org/I4210163363"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210163363"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13276295,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"16","issue":"10","first_page":"867","last_page":"867"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9994999766349792,"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":0.9994999766349792,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.9846000075340271,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.965499997138977,"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/camouflage","display_name":"Camouflage","score":0.7742999792098999},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7432000041007996},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6316999793052673},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6187999844551086},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6154999732971191},{"id":"https://openalex.org/keywords/deception","display_name":"Deception","score":0.5825999975204468},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.47609999775886536},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4323999881744385},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.38350000977516174}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7885000109672546},{"id":"https://openalex.org/C2776196576","wikidata":"https://www.wikidata.org/wiki/Q196113","display_name":"Camouflage","level":2,"score":0.7742999792098999},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7617999911308289},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7432000041007996},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6316999793052673},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6187999844551086},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6154999732971191},{"id":"https://openalex.org/C2779267917","wikidata":"https://www.wikidata.org/wiki/Q170028","display_name":"Deception","level":2,"score":0.5825999975204468},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.47609999775886536},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4323999881744385},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42730000615119934},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40689998865127563},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.38350000977516174},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.32829999923706055},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.3240000009536743},{"id":"https://openalex.org/C97385483","wikidata":"https://www.wikidata.org/wiki/Q16954980","display_name":"Deep belief network","level":3,"score":0.3091999888420105},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.2890999913215637},{"id":"https://openalex.org/C160086991","wikidata":"https://www.wikidata.org/wiki/Q5939193","display_name":"Human visual system model","level":3,"score":0.28519999980926514},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.27649998664855957},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C2778403875","wikidata":"https://www.wikidata.org/wiki/Q20312394","display_name":"Adversarial machine learning","level":3,"score":0.2711000144481659},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.27000001072883606},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2685999870300293},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.26570001244544983},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C158495155","wikidata":"https://www.wikidata.org/wiki/Q2369151","display_name":"Visual search","level":2,"score":0.2531000077724457}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/info16100867","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16100867","pdf_url":"https://www.mdpi.com/2078-2489/16/10/867/pdf?version=1759817107","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:da1a8be9ddcb4a3eb63db9d17e584f66","is_oa":true,"landing_page_url":"https://doaj.org/article/da1a8be9ddcb4a3eb63db9d17e584f66","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Information, Vol 16, Iss 10, p 867 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/info16100867","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16100867","pdf_url":"https://www.mdpi.com/2078-2489/16/10/867/pdf?version=1759817107","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4414883543.pdf","grobid_xml":"https://content.openalex.org/works/W4414883543.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2133665775","https://openalex.org/W2183341477","https://openalex.org/W2193145675","https://openalex.org/W2194775991","https://openalex.org/W2765793020","https://openalex.org/W2958109694","https://openalex.org/W2962785568","https://openalex.org/W2962793481","https://openalex.org/W2962858109","https://openalex.org/W2963068442","https://openalex.org/W2963150697","https://openalex.org/W2963446712","https://openalex.org/W2963527086","https://openalex.org/W3017485054","https://openalex.org/W3096750792","https://openalex.org/W3106250896","https://openalex.org/W3185095134","https://openalex.org/W3200450146","https://openalex.org/W4390874575","https://openalex.org/W4402754006"],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"HE-DMDeception,":[3,178],"a":[4,47,58,102],"novel":[5],"adversarial":[6,186],"attack":[7,74],"network":[8,50],"that":[9,72,115],"integrates":[10],"human":[11],"visual":[12,77,164],"deception":[13,17,60],"with":[14,166],"deep":[15,33],"model":[16,98],"to":[18,38,51],"enhance":[19],"the":[20,81,93,116,167,173],"security":[21],"of":[22,83,177],"3D":[23,183],"object":[24,184],"detection.":[25],"Existing":[26],"patch-based":[27],"and":[28,66,76,109,152,175],"camouflage":[29,49],"methods":[30],"can":[31],"mislead":[32],"learning":[34],"models":[35],"but":[36],"struggle":[37],"generate":[39,52],"visually":[40],"imperceptible,":[41],"high-quality":[42],"textures.":[43],"Our":[44],"framework":[45],"employs":[46],"CycleGAN-based":[48],"highly":[53],"camouflaged":[54],"background":[55],"textures,":[56],"while":[57,161],"dedicated":[59],"module":[61,90],"disrupts":[62],"non-maximum":[63],"suppression":[64],"(NMS)":[65],"attention":[67],"mechanisms":[68],"through":[69],"optimized":[70],"constraints":[71],"balance":[73],"efficacy":[75],"fidelity.":[78],"To":[79],"overcome":[80],"scarcity":[82],"annotated":[84],"vehicle":[85],"data,":[86],"an":[87],"image":[88],"segmentation":[89],"based":[91],"on":[92],"pre-trained":[94],"Segment":[95],"Anything":[96],"(SAM)":[97],"is":[99],"introduced,":[100],"leveraging":[101],"two-stage":[103],"training":[104],"strategy":[105],"combining":[106],"semi-supervised":[107],"self-training":[108],"supervised":[110],"fine-tuning.":[111],"Experimental":[112],"results":[113],"show":[114],"minimum":[117],"P@0.5":[118],"values":[119],"(50%,":[120],"55%,":[121],"20%,":[122],"25%,":[123],"25%)":[124],"were":[125],"achieved":[126],"by":[127],"HE-DMDeception":[128],"across":[129],"You":[130],"Only":[131],"Look":[132],"Once":[133],"version":[134],"8":[135],"(YOLOv8),":[136],"Real-Time":[137],"Detection":[138],"Transformer":[139],"(RT-DETR),":[140],"Fast":[141],"Region-based":[142],"Convolutional":[143,154],"Neural":[144,155],"Network":[145,156],"(Faster-RCNN),":[146],"Single":[147],"Shot":[148],"MultiBox":[149],"Detector":[150],"(SSD),":[151],"MaskRegion-based":[153],"(Mask":[157],"RCNN)":[158],"detection":[159,185],"models,":[160],"maintaining":[162],"high":[163],"consistency":[165],"original":[168],"camouflage.":[169],"These":[170],"findings":[171],"demonstrate":[172],"robustness":[174],"practicality":[176],"offering":[179],"new":[180],"insights":[181],"into":[182],"attacks.":[187]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}