{"id":"https://openalex.org/W7151519821","doi":"https://doi.org/10.48550/arxiv.2604.04658","title":"Synthesis4AD: Synthetic Anomalies are All You Need for 3D Anomaly Detection","display_name":"Synthesis4AD: Synthetic Anomalies are All You Need for 3D Anomaly Detection","publication_year":2026,"publication_date":"2026-04-06","ids":{"openalex":"https://openalex.org/W7151519821","doi":"https://doi.org/10.48550/arxiv.2604.04658"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.04658","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.04658","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.04658","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133078762","display_name":"Yihan Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Yihan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133065269","display_name":"Yuqi Cheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, Yuqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133146098","display_name":"Junjie Zu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zu, Junjie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132804868","display_name":"Yuxiang Tan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tan, Yuxiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133130664","display_name":"Guoyang Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Guoyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133071183","display_name":"Yucheng Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yucheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133115423","display_name":"Yunkang Cao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cao, Yunkang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133111151","display_name":"Weiming Shen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Weiming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.8151999711990356,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.8151999711990356,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.012900000438094139,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10763","display_name":"Digital Transformation in Industry","score":0.010099999606609344,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6194000244140625},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6140000224113464},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5461999773979187},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.460099995136261},{"id":"https://openalex.org/keywords/debugging","display_name":"Debugging","score":0.39910000562667847},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.3962000012397766},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.35760000348091125},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.33570000529289246},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.33559998869895935},{"id":"https://openalex.org/keywords/undersampling","display_name":"Undersampling","score":0.3325999975204468}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.701200008392334},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6194000244140625},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6140000224113464},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5461999773979187},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.460099995136261},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4595000147819519},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45159998536109924},{"id":"https://openalex.org/C168065819","wikidata":"https://www.wikidata.org/wiki/Q845566","display_name":"Debugging","level":2,"score":0.39910000562667847},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.3962000012397766},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.35760000348091125},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.33570000529289246},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.33559998869895935},{"id":"https://openalex.org/C136536468","wikidata":"https://www.wikidata.org/wiki/Q1225894","display_name":"Undersampling","level":2,"score":0.3325999975204468},{"id":"https://openalex.org/C61423126","wikidata":"https://www.wikidata.org/wiki/Q187432","display_name":"Scripting language","level":2,"score":0.3147999942302704},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3142000138759613},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.31349998712539673},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.29789999127388},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.29269999265670776},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.28679999709129333},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.27880001068115234},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.272599995136261},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.2703000009059906},{"id":"https://openalex.org/C56288433","wikidata":"https://www.wikidata.org/wiki/Q58673","display_name":"Data manipulation language","level":2,"score":0.26499998569488525},{"id":"https://openalex.org/C149810388","wikidata":"https://www.wikidata.org/wiki/Q5374873","display_name":"Emulation","level":2,"score":0.2612000107765198},{"id":"https://openalex.org/C2777874068","wikidata":"https://www.wikidata.org/wiki/Q220676","display_name":"Thiirane","level":3,"score":0.25920000672340393},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C137524506","wikidata":"https://www.wikidata.org/wiki/Q2247688","display_name":"Anomaly-based intrusion detection system","level":3,"score":0.25519999861717224},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.2547000050544739},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.2533999979496002},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.04658","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.04658","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.04658","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.04658","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.669124960899353,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Industrial":[0],"3D":[1,39],"anomaly":[2,40,74,96],"detection":[3],"performance":[4,157],"is":[5,47],"fundamentally":[6],"constrained":[7],"by":[8,65],"the":[9,43,54,108,113,136,173],"scarcity":[10],"and":[11,90,101,110,130,145,161,172],"long-tailed":[12],"distribution":[13],"of":[14,45,112,138],"abnormal":[15],"samples.":[16],"To":[17,106],"address":[18],"this":[19],"challenge,":[20],"we":[21],"propose":[22],"Synthesis4AD,":[23],"an":[24],"end-to-end":[25],"paradigm":[26],"that":[27],"leverages":[28],"large-scale,":[29],"high-fidelity":[30],"synthetic":[31],"anomalies":[32],"to":[33,85,142],"learn":[34],"more":[35],"discriminative":[36],"representations":[37],"for":[38],"detection.":[41],"At":[42],"core":[44],"Synthesis4AD":[46,77,120],"3D-DefectStudio,":[48],"a":[49,79,123,162],"software":[50],"platform":[51],"built":[52],"upon":[53],"controllable":[55],"synthesis":[56,97,169],"engine":[57],"MPAS,":[58],"which":[59,134],"injects":[60],"geometrically":[61],"realistic":[62,150],"defects":[63],"guided":[64],"higher-dimensional":[66],"support":[67],"primitives":[68],"while":[69],"simultaneously":[70],"generating":[71],"accurate":[72],"point-wise":[73],"masks.":[75],"Furthermore,":[76],"incorporates":[78],"multimodal":[80],"large":[81],"language":[82],"model":[83],"(MLLM)":[84],"interpret":[86],"product":[87],"design":[88],"information":[89],"automatically":[91],"translate":[92],"it":[93],"into":[94],"executable":[95],"instructions,":[98],"enabling":[99],"scalable":[100],"knowledge-driven":[102],"anomalous":[103],"data":[104,132,151],"generation.":[105],"improve":[107],"robustness":[109],"generalization":[111],"downstream":[114],"detector":[115],"on":[116,127,158],"unstructured":[117],"point":[118],"clouds,":[119],"further":[121],"introduces":[122],"training":[124],"pipeline":[125],"based":[126],"spatial-distribution":[128],"normalization":[129],"geometry-faithful":[131],"augmentations,":[133],"alleviates":[135],"sensitivity":[137],"Point":[139],"Transformer":[140],"architectures":[141],"absolute":[143],"coordinates":[144],"improves":[146],"feature":[147],"learning":[148],"under":[149],"variations.":[152],"Extensive":[153],"experiments":[154],"demonstrate":[155],"state-of-the-art":[156],"Real3D-AD,":[159],"MulSen-AD,":[160],"real-world":[163],"industrial":[164],"parts":[165],"dataset.":[166],"The":[167],"proposed":[168],"method":[170],"MPAS":[171],"interactive":[174],"system":[175],"3D-DefectStudio":[176],"will":[177],"be":[178],"publicly":[179],"released":[180],"at":[181],"https://github.com/hustCYQ/Synthesis4AD.":[182]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-08T00:00:00"}