{"id":"https://openalex.org/W7164828052","doi":"https://doi.org/10.1145/3805622.3810806","title":"SaF-AD: Saliency-Adaptive and Feature-Consistent Diffusion for Industrial Anomaly Detection","display_name":"SaF-AD: Saliency-Adaptive and Feature-Consistent Diffusion for Industrial Anomaly Detection","publication_year":2026,"publication_date":"2026-06-15","ids":{"openalex":"https://openalex.org/W7164828052","doi":"https://doi.org/10.1145/3805622.3810806"},"language":null,"primary_location":{"id":"doi:10.1145/3805622.3810806","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810806","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3805622.3810806","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100644814","display_name":"Ying Liu","orcid":"https://orcid.org/0000-0002-8951-2648"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yilong Liu","raw_affiliation_strings":["Southeast university, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0002-6927-8134","affiliations":[{"raw_affiliation_string":"Southeast university, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006557503","display_name":"Y Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanyang Zhang","raw_affiliation_strings":["Southeast university, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-8067-8414","affiliations":[{"raw_affiliation_string":"Southeast university, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138639564","display_name":"Zirui Luo","orcid":"https://orcid.org/0009-0005-0539-1180"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zirui Luo","raw_affiliation_strings":["Southeast university, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0005-0539-1180","affiliations":[{"raw_affiliation_string":"Southeast university, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100665809","display_name":"Ke Xu","orcid":"https://orcid.org/0000-0001-8669-3909"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaixi Xu","raw_affiliation_strings":["Southeast university, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0006-2210-0653","affiliations":[{"raw_affiliation_string":"Southeast university, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027459729","display_name":"Yan Xu","orcid":"https://orcid.org/0000-0003-0379-8866"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yining Xu","raw_affiliation_strings":["Southeast university, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0001-2472-3460","affiliations":[{"raw_affiliation_string":"Southeast university, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100704268","display_name":"Li Yao","orcid":"https://orcid.org/0000-0003-2930-8407"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Yao","raw_affiliation_strings":["Southeast university, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0003-2930-8407","affiliations":[{"raw_affiliation_string":"Southeast university, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.94806099,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"777","last_page":"786"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9036999940872192,"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":0.9036999940872192,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.03099999949336052,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.027499999850988388,"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/salient","display_name":"Salient","score":0.6568999886512756},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.5787000060081482},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.5498999953269958},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5485000014305115},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48339998722076416},{"id":"https://openalex.org/keywords/decoupling","display_name":"Decoupling (probability)","score":0.44339999556541443},{"id":"https://openalex.org/keywords/forcing","display_name":"Forcing (mathematics)","score":0.41850000619888306},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3986999988555908},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.3946000039577484}],"concepts":[{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.6568999886512756},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6444000005722046},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.5787000060081482},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.5498999953269958},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5485000014305115},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5221999883651733},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48339998722076416},{"id":"https://openalex.org/C205606062","wikidata":"https://www.wikidata.org/wiki/Q5249645","display_name":"Decoupling (probability)","level":2,"score":0.44339999556541443},{"id":"https://openalex.org/C197115733","wikidata":"https://www.wikidata.org/wiki/Q1003136","display_name":"Forcing (mathematics)","level":2,"score":0.41850000619888306},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3986999988555908},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39739999175071716},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.3946000039577484},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.365200012922287},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.3467999994754791},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.32409998774528503},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31630000472068787},{"id":"https://openalex.org/C17231256","wikidata":"https://www.wikidata.org/wiki/Q5156540","display_name":"Completeness (order theory)","level":2,"score":0.31200000643730164},{"id":"https://openalex.org/C177918212","wikidata":"https://www.wikidata.org/wiki/Q803623","display_name":"Perturbation (astronomy)","level":2,"score":0.29409998655319214},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.29170000553131104},{"id":"https://openalex.org/C43711488","wikidata":"https://www.wikidata.org/wiki/Q7534783","display_name":"Skew","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.27970001101493835},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.273499995470047},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.2671999931335449},{"id":"https://openalex.org/C131584629","wikidata":"https://www.wikidata.org/wiki/Q4308705","display_name":"Coupling (piping)","level":2,"score":0.2630000114440918},{"id":"https://openalex.org/C55128770","wikidata":"https://www.wikidata.org/wiki/Q5275440","display_name":"Diffusion map","level":4,"score":0.25459998846054077},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2524999976158142}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3805622.3810806","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810806","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3805622.3810806","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810806","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W3147184966","https://openalex.org/W3159481202","https://openalex.org/W3183588514","https://openalex.org/W4214694907","https://openalex.org/W4292851291","https://openalex.org/W4312605624","https://openalex.org/W4312772600","https://openalex.org/W4386065608","https://openalex.org/W4386065890","https://openalex.org/W4386113288","https://openalex.org/W4390872231","https://openalex.org/W4390872785","https://openalex.org/W4390872847","https://openalex.org/W4390875033","https://openalex.org/W4393147759","https://openalex.org/W4402716302","https://openalex.org/W4403662533","https://openalex.org/W4411631885","https://openalex.org/W4411631889","https://openalex.org/W4413144853","https://openalex.org/W4413155094","https://openalex.org/W4413156408","https://openalex.org/W4413157177","https://openalex.org/W4413157644","https://openalex.org/W4415536772","https://openalex.org/W4415540901","https://openalex.org/W4415797137","https://openalex.org/W7133227337","https://openalex.org/W7133232138","https://openalex.org/W7135018735","https://openalex.org/W7138126727","https://openalex.org/W7160038841","https://openalex.org/W7160071830","https://openalex.org/W7160106168","https://openalex.org/W7160324836"],"related_works":[],"abstract_inverted_index":{"Diffusion":[0],"models":[1],"have":[2],"recently":[3],"shown":[4],"strong":[5],"potential":[6],"for":[7],"reconstr-uction-based":[8],"unsupervised":[9],"anomaly":[10,168],"detection":[11,160],"(UAD).":[12],"However,":[13],"industrial":[14],"UAD":[15],"across":[16],"diverse":[17,123],"object":[18],"categories":[19],"remains":[20],"challenging:":[21],"subtle":[22],"defects":[23],"often":[24],"overlap":[25],"with":[26],"intrinsic":[27],"structural":[28],"details,":[29],"and":[30,51,64,113,152,162],"commonly":[31],"used":[32],"uniform":[33],"or":[34],"semantically":[35],"agnostic":[36],"perturbations":[37],"can":[38],"induce":[39],"two":[40],"failure":[41],"modes\u2014identity":[42],"shortcut":[43,115],"(copying":[44],"uncorrupted":[45],"content,":[46],"resulting":[47],"in":[48],"misleading":[49],"residuals)":[50],"semantic":[52,143],"drift":[53],"(over-smoothed":[54],"yet":[55],"structurally":[56],"inconsistent":[57],"restorations).":[58],"We":[59],"propose":[60],"SaF-AD,":[61],"a":[62,139],"saliency-adaptive":[63],"feature-consistent":[65],"diffusion":[66],"framework":[67],"to":[68,81,109],"mitigate":[69],"these":[70],"issues.":[71],"First,":[72],"Saliency-Adaptive":[73],"Perturbation":[74],"Masking":[75],"(SAPM)":[76],"applies":[77],"soft,":[78],"saliency-guided":[79],"masking":[80,105],"adaptively":[82],"corrupt":[83],"informative":[84],"regions":[85,137],"while":[86,145],"avoiding":[87],"hard":[88],"boundaries,":[89],"encouraging":[90],"structure-aware":[91],"reconstruction":[92,118],"instead":[93],"of":[94,119],"background":[95],"redundancy.":[96],"Second,":[97],"Progressive":[98],"Anchor":[99],"Decoupling":[100],"(PAD)":[101],"progressively":[102],"adjusts":[103],"the":[104],"preference":[106],"during":[107],"training":[108],"reduce":[110],"persistent":[111],"anchors":[112],"prevent":[114],"learning,":[116],"forcing":[117],"salient":[120],"structures":[121],"from":[122],"contextual":[124],"cues.":[125],"Third,":[126],"Hierarchical":[127],"Semantic":[128],"Feature":[129],"Consistency":[130],"(HSFC)":[131],"regularizes":[132],"multi-level":[133],"features":[134],"on":[135,150,166],"corrupted":[136],"using":[138],"frozen":[140],"backbone,":[141],"improving":[142],"coherence":[144],"preserving":[146],"fine-grained":[147],"details.":[148],"Experiments":[149],"MVTec-AD":[151],"VisA":[153],"show":[154],"that":[155],"SaF-AD":[156],"achieves":[157],"competitive":[158],"image-level":[159],"performance":[161],"more":[163],"consistent":[164],"gains":[165],"pixel-level":[167],"localization.":[169]},"counts_by_year":[],"updated_date":"2026-06-16T07:37:23.134862","created_date":"2026-06-16T00:00:00"}