{"id":"https://openalex.org/W4416851486","doi":"https://doi.org/10.1145/3733800.3763268","title":"Safety Assessment of 3D Generation Models in AR/VR Applications","display_name":"Safety Assessment of 3D Generation Models in AR/VR Applications","publication_year":2025,"publication_date":"2025-10-13","ids":{"openalex":"https://openalex.org/W4416851486","doi":"https://doi.org/10.1145/3733800.3763268"},"language":null,"primary_location":{"id":"doi:10.1145/3733800.3763268","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3733800.3763268","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3733800.3763268","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 Workshop on Large AI Systems and Models with Privacy and Security Analysis","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3733800.3763268","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111459810","display_name":"Xi Tang","orcid":"https://orcid.org/0009-0007-2066-8218"},"institutions":[{"id":"https://openalex.org/I57093077","display_name":"Swinburne University of Technology","ror":"https://ror.org/031rekg67","country_code":"AU","type":"education","lineage":["https://openalex.org/I57093077"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Xi Tang","raw_affiliation_strings":["Swinburne University of Technology, Melbourne, Australia"],"raw_orcid":"https://orcid.org/0009-0007-2066-8218","affiliations":[{"raw_affiliation_string":"Swinburne University of Technology, Melbourne, Australia","institution_ids":["https://openalex.org/I57093077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011383481","display_name":"Wanlun Ma","orcid":"https://orcid.org/0000-0002-6305-1740"},"institutions":[{"id":"https://openalex.org/I57093077","display_name":"Swinburne University of Technology","ror":"https://ror.org/031rekg67","country_code":"AU","type":"education","lineage":["https://openalex.org/I57093077"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Wanlun Ma","raw_affiliation_strings":["Swinburne University of Technology, Melbourne, Australia"],"raw_orcid":"https://orcid.org/0000-0002-6305-1740","affiliations":[{"raw_affiliation_string":"Swinburne University of Technology, Melbourne, Australia","institution_ids":["https://openalex.org/I57093077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110203019","display_name":"Yunfan Bao","orcid":"https://orcid.org/0009-0000-0737-0926"},"institutions":[{"id":"https://openalex.org/I57093077","display_name":"Swinburne University of Technology","ror":"https://ror.org/031rekg67","country_code":"AU","type":"education","lineage":["https://openalex.org/I57093077"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yinwei Bao","raw_affiliation_strings":["Swinburne University of Technology, Melbourne, Australia"],"raw_orcid":"https://orcid.org/0009-0000-0737-0926","affiliations":[{"raw_affiliation_string":"Swinburne University of Technology, Melbourne, Australia","institution_ids":["https://openalex.org/I57093077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060360009","display_name":"Minhui Xue","orcid":"https://orcid.org/0000-0001-5411-5039"},"institutions":[{"id":"https://openalex.org/I1292875679","display_name":"Commonwealth Scientific and Industrial Research Organisation","ror":"https://ror.org/03qn8fb07","country_code":"AU","type":"government","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4387156119"]},{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Minhui Xue","raw_affiliation_strings":["CSIRO's Data61, Adelaide, Australia"],"raw_orcid":"https://orcid.org/0000-0001-5411-5039","affiliations":[{"raw_affiliation_string":"CSIRO's Data61, Adelaide, Australia","institution_ids":["https://openalex.org/I1292875679","https://openalex.org/I42894916"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076576641","display_name":"Sheng Wen","orcid":"https://orcid.org/0000-0003-0655-666X"},"institutions":[{"id":"https://openalex.org/I57093077","display_name":"Swinburne University of Technology","ror":"https://ror.org/031rekg67","country_code":"AU","type":"education","lineage":["https://openalex.org/I57093077"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Sheng Wen","raw_affiliation_strings":["Swinburne University of Technology, Melbourne, Australia"],"raw_orcid":"https://orcid.org/0000-0003-0655-666X","affiliations":[{"raw_affiliation_string":"Swinburne University of Technology, Melbourne, Australia","institution_ids":["https://openalex.org/I57093077"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100666554","display_name":"Yang Xiang","orcid":"https://orcid.org/0000-0001-5252-0831"},"institutions":[{"id":"https://openalex.org/I57093077","display_name":"Swinburne University of Technology","ror":"https://ror.org/031rekg67","country_code":"AU","type":"education","lineage":["https://openalex.org/I57093077"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yang Xiang","raw_affiliation_strings":["Digital Capability Research Platform, Swinburne University of Technology, Melbourne, Australia"],"raw_orcid":"https://orcid.org/0000-0001-5252-0831","affiliations":[{"raw_affiliation_string":"Digital Capability Research Platform, Swinburne University of Technology, Melbourne, Australia","institution_ids":["https://openalex.org/I57093077"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.43282993,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"30","last_page":"38"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.423799991607666,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.423799991607666,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.23000000417232513,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.029899999499320984,"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/workflow","display_name":"Workflow","score":0.5224000215530396},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.46299999952316284},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.3671000003814697},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.36419999599456787},{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.3617999851703644},{"id":"https://openalex.org/keywords/virtual-reality","display_name":"Virtual reality","score":0.3215000033378601},{"id":"https://openalex.org/keywords/3d-model","display_name":"3d model","score":0.3156000077724457}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7177000045776367},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.5224000215530396},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4986000061035156},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.46299999952316284},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3725000023841858},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.3671000003814697},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.36419999599456787},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.3617999851703644},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3562999963760376},{"id":"https://openalex.org/C194969405","wikidata":"https://www.wikidata.org/wiki/Q170519","display_name":"Virtual reality","level":2,"score":0.3215000033378601},{"id":"https://openalex.org/C3019007443","wikidata":"https://www.wikidata.org/wiki/Q568742","display_name":"3d model","level":2,"score":0.3156000077724457},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.3098999857902527},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.29910001158714294},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.2639999985694885},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2630999982357025},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.25369998812675476},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.25270000100135803},{"id":"https://openalex.org/C153715457","wikidata":"https://www.wikidata.org/wiki/Q254183","display_name":"Augmented reality","level":2,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3733800.3763268","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3733800.3763268","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3733800.3763268","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 Workshop on Large AI Systems and Models with Privacy and Security Analysis","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3733800.3763268","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3733800.3763268","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3733800.3763268","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 Workshop on Large AI Systems and Models with Privacy and Security Analysis","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320386","display_name":"Commonwealth Scientific and Industrial Research Organisation","ror":"https://ror.org/03qn8fb07"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416851486.pdf","grobid_xml":"https://content.openalex.org/works/W4416851486.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W1975879668","https://openalex.org/W2728746687","https://openalex.org/W2891396148","https://openalex.org/W2920973181","https://openalex.org/W3109585842","https://openalex.org/W4221029209","https://openalex.org/W4281778915","https://openalex.org/W4312933868","https://openalex.org/W4318262370","https://openalex.org/W4385318467","https://openalex.org/W4386066536","https://openalex.org/W4388858734","https://openalex.org/W4400822286","https://openalex.org/W4401728013","https://openalex.org/W4405642326"],"related_works":[],"abstract_inverted_index":{"The":[0,165],"rapid":[1],"advancements":[2],"in":[3,124,228,246],"3D":[4,29,56,78,238,247,266],"generative":[5,248],"models":[6],"are":[7,117,168],"revolutionizing":[8],"content":[9,57,267],"creation":[10,268],"for":[11,25,178,237,260],"immersive":[12,275],"applications":[13],"like":[14],"Virtual":[15],"Reality":[16,20],"(VR)":[17],"and":[18,27,73,109,139,170,199,215,256,272],"Augmented":[19],"(AR),":[21],"offering":[22],"unprecedented":[23],"capabilities":[24],"complex":[26],"realistic":[28],"asset":[30],"generation.":[31,94],"However,":[32],"this":[33,82,251],"transformative":[34],"power":[35],"introduces":[36],"significant":[37],"safety":[38,90,101,134,179,207],"concerns,":[39],"particularly":[40],"regarding":[41],"the":[42,87,184,231,242,261],"unintentional":[43],"or":[44,52],"malicious":[45],"generation":[46,126],"of":[47,92,187,197,202,233,264],"unsafe":[48],"content.":[49],"Unlike":[50],"text":[51],"2D":[53],"image":[54,206],"models,":[55],"poses":[58],"unique":[59],"risks":[60],"due":[61],"to":[62,147,172],"its":[63],"immersive,":[64],"interactive":[65],"nature,":[66],"with":[67],"potential":[68],"implications":[69],"across":[70,99],"digital":[71],"environments":[72],"real-world":[74],"scenarios":[75],"such":[76,210],"as":[77,119,211],"printing.":[79],"To":[80],"confront":[81],"challenge,":[83],"we":[84,103],"carry":[85],"out":[86],"first":[88],"systematic":[89],"audit":[91],"text-to-3D":[93,107],"Using":[95],"6":[96],"137":[97],"prompts":[98],"five":[100],"suites,":[102],"sample":[104],"a":[105,131,144,155,173,257],"state-of-the-art":[106],"workflow":[108],"double-blind-annotate":[110],"every":[111],"output.":[112],"Alarmingly,":[113],"829":[114],"objects":[115],"(13.51%)":[116],"flagged":[118],"unsafe,":[120],"confirming":[121],"persistent":[122],"risk":[123],"current":[125],"workflows.":[127],"We":[128,142],"then":[129],"propose":[130],"novel":[132],"multimodal":[133,192,222],"classifier":[135,193],"that":[136,221],"fuses":[137],"geometric":[138],"visual":[140,156],"information.":[141],"use":[143],"MeshCNN":[145],"encoder":[146,157],"distill":[148],"shape":[149],"features":[150],"from":[151,162],"simplified":[152],"meshes,":[153],"while":[154],"captures":[158],"complementary":[159],"appearance":[160],"information":[161],"multi-view":[163],"renderings.":[164],"resulting":[166],"embeddings":[167],"fused":[169],"fed":[171],"residual":[174],"multilayer":[175],"perceptron":[176],"tuned":[177],"prediction.":[180],"Comprehensive":[181],"experiments":[182],"demonstrate":[183],"superior":[185],"efficacy":[186],"our":[188],"method.":[189],"Our":[190,277],"combined":[191],"achieves":[194],"an":[195,200],"accuracy":[196],"0.8784":[198],"AUC-ROC":[201],"0.8775,":[203],"surpassing":[204],"leading":[205],"classification":[208],"baselines,":[209],"Unsafe":[212],"Diffusion,":[213],"ShieldGemma2,":[214],"LlamaGuard4.":[216],"Additionally,":[217],"ablation":[218],"studies":[219],"confirm":[220],"fusion":[223],"consistently":[224],"outperforms":[225],"either":[226],"modality":[227],"isolation,":[229],"underscoring":[230],"value":[232],"joint":[234],"geometry\u2013image":[235],"reasoning":[236],"safety.":[239],"By":[240],"bridging":[241],"existing":[243],"research":[244],"gap":[245],"model":[249],"safety,":[250],"work":[252],"provides":[253],"actionable":[254],"insights":[255],"robust":[258],"framework":[259],"responsible":[262],"deployment":[263],"AI-driven":[265],"technologies,":[269],"ensuring":[270],"safer":[271],"more":[273],"trustworthy":[274],"experiences.":[276],"code":[278],"is":[279],"publicly":[280],"available":[281],"at":[282],"https://github.com/xitang2000/3D_safety_assessment.":[283]},"counts_by_year":[],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-12-01T00:00:00"}