{"id":"https://openalex.org/W4416960206","doi":"https://doi.org/10.48550/arxiv.2512.01427","title":"Language-Guided Open-World Anomaly Segmentation","display_name":"Language-Guided Open-World Anomaly Segmentation","publication_year":2025,"publication_date":"2025-12-01","ids":{"openalex":"https://openalex.org/W4416960206","doi":"https://doi.org/10.48550/arxiv.2512.01427"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2512.01427","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.01427","pdf_url":"https://arxiv.org/pdf/2512.01427","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2512.01427","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5003564228","display_name":"Klara Reichard","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Reichard, Klara","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002741094","display_name":"Nikolas Brasch","orcid":"https://orcid.org/0000-0002-8906-8946"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Brasch, Nikolas","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046896448","display_name":"Nassir Navab","orcid":"https://orcid.org/0000-0002-6032-5611"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Navab, Nassir","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5041092666","display_name":"Federico Tombari","orcid":"https://orcid.org/0000-0001-5598-5212"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tombari, Federico","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5003564228"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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":0.9794999957084656,"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":0.9794999957084656,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.003800000064074993,"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":0.0027000000700354576,"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/interpretability","display_name":"Interpretability","score":0.8238999843597412},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7821000218391418},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6528000235557556},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5734000205993652},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.48260000348091125},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.46869999170303345},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46459999680519104}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8238999843597412},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7821000218391418},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6718000173568726},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6686000227928162},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6528000235557556},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5734000205993652},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.48260000348091125},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.46869999170303345},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46459999680519104},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.4345000088214874},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.3919000029563904},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.34369999170303345},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.30799999833106995},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.305400013923645},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.30469998717308044},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.3010999858379364},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2624000012874603},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.25110000371932983}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2512.01427","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.01427","pdf_url":"https://arxiv.org/pdf/2512.01427","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2512.01427","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2512.01427","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2512.01427","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.01427","pdf_url":"https://arxiv.org/pdf/2512.01427","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416960206.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Open-world":[0],"and":[1,13,17,35,37,62,83,98,110,133,158],"anomaly":[2,69,84,152],"segmentation":[3,47,70,85,153],"methods":[4,25,48],"seek":[5],"to":[6,11,32,53,68,105,114],"enable":[7],"autonomous":[8,88],"driving":[9],"systems":[10],"detect":[12],"segment":[14,107],"both":[15,106],"known":[16],"unknown":[18,33,41,72,108],"objects":[19,109],"in":[20,51,144],"real-world":[21],"scenes.":[22],"However,":[23],"existing":[24],"do":[26],"not":[27],"assign":[28,111],"semantically":[29],"meaningful":[30],"labels":[31],"regions,":[34],"distinguishing":[36],"learning":[38],"representations":[39],"for":[40,87,161],"classes":[42,73],"remains":[43],"difficult.":[44],"While":[45],"open-vocabulary":[46,117],"show":[49],"promise":[50],"generalizing":[52],"novel":[54],"classes,":[55],"they":[56],"require":[57],"a":[58],"fixed":[59],"inference":[60,126],"vocabulary":[61,124],"thus":[63],"cannot":[64],"be":[65],"directly":[66],"applied":[67],"where":[71],"are":[74],"unconstrained.":[75],"We":[76],"propose":[77],"Clipomaly,":[78],"the":[79],"first":[80],"CLIP-based":[81],"open-world":[82],"method":[86],"driving.":[89],"Our":[90],"zero-shot":[91],"approach":[92],"requires":[93],"no":[94],"anomaly-specific":[95],"training":[96],"data":[97],"leverages":[99],"CLIP's":[100],"shared":[101],"image-text":[102],"embedding":[103],"space":[104],"human-interpretable":[112],"names":[113],"them.":[115],"Unlike":[116],"methods,":[118],"our":[119],"model":[120],"dynamically":[121],"extends":[122],"its":[123],"at":[125],"time":[127],"without":[128],"retraining,":[129],"enabling":[130],"robust":[131],"detection":[132],"naming":[134],"of":[135],"anomalies":[136],"beyond":[137],"common":[138],"class":[139],"definitions":[140],"such":[141],"as":[142],"those":[143],"Cityscapes.":[145],"Clipomaly":[146],"achieves":[147],"state-of-the-art":[148],"performance":[149],"on":[150],"established":[151],"benchmarks":[154],"while":[155],"providing":[156],"interpretability":[157],"flexibility":[159],"essential":[160],"practical":[162],"deployment.":[163]},"counts_by_year":[],"updated_date":"2026-03-11T14:59:36.786465","created_date":"2025-12-03T00:00:00"}
