{"id":"https://openalex.org/W4320843386","doi":"https://doi.org/10.48550/arxiv.2302.05753","title":"DaliID: Distortion-Adaptive Learned Invariance for Identification Models","display_name":"DaliID: Distortion-Adaptive Learned Invariance for Identification Models","publication_year":2023,"publication_date":"2023-02-11","ids":{"openalex":"https://openalex.org/W4320843386","doi":"https://doi.org/10.48550/arxiv.2302.05753"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2302.05753","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2302.05753","pdf_url":"https://arxiv.org/pdf/2302.05753","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2302.05753","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089225887","display_name":"Wes Robbins","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Robbins, Wes","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049011757","display_name":"Gabriel Bertocco","orcid":"https://orcid.org/0000-0002-7701-7420"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bertocco, Gabriel","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5049661026","display_name":"Terrance E. Boult","orcid":"https://orcid.org/0000-0001-5007-2529"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Boult, Terrance E.","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5089225887"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":2,"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/T11448","display_name":"Face recognition and analysis","score":0.9994999766349792,"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/T11448","display_name":"Face recognition and analysis","score":0.9994999766349792,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9822999835014343,"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/T10828","display_name":"Biometric Identification and Security","score":0.9743000268936157,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/robustness","display_name":"Robustness (evolution)","score":0.7677553296089172},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7123556733131409},{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.6807770729064941},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6534181237220764},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.5775381922721863},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4960959851741791},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.4796038866043091},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4582672715187073},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4180002808570862},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23981863260269165}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7677553296089172},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7123556733131409},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.6807770729064941},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6534181237220764},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.5775381922721863},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4960959851741791},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.4796038866043091},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4582672715187073},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4180002808570862},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23981863260269165},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2302.05753","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2302.05753","pdf_url":"https://arxiv.org/pdf/2302.05753","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2302.05753","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2302.05753","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:2302.05753","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2302.05753","pdf_url":"https://arxiv.org/pdf/2302.05753","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4320843386.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2062399876","https://openalex.org/W2607795551","https://openalex.org/W3155117723","https://openalex.org/W1991429770","https://openalex.org/W1983892167","https://openalex.org/W2281134365","https://openalex.org/W2180954594","https://openalex.org/W4310746709","https://openalex.org/W2052835778","https://openalex.org/W4306309518"],"abstract_inverted_index":{"In":[0],"unconstrained":[1,93],"scenarios,":[2,26],"face":[3,122,155],"recognition":[4,123],"and":[5,88,124,135,149],"person":[6,125],"re-identification":[7,126],"are":[8],"subject":[9],"to":[10,52,86,92,107],"distortions":[11,87],"such":[12],"as":[13],"motion":[14],"blur,":[15],"atmospheric":[16],"turbulence,":[17],"or":[18],"upsampling":[19],"artifacts.":[20],"To":[21],"improve":[22],"robustness":[23,109],"in":[24,60],"these":[25],"we":[27,97,138],"propose":[28],"a":[29,53,69,99,144],"methodology":[30],"called":[31],"Distortion-Adaptive":[32],"Learned":[33],"Invariance":[34],"for":[35,120],"Identification":[36],"(DaliID)":[37],"models.":[38],"We":[39],"contend":[40],"that":[41],"distortion":[42,71],"augmentations,":[43],"which":[44],"degrade":[45],"image":[46],"quality,":[47],"can":[48],"be":[49],"successfully":[50],"leveraged":[51],"greater":[54],"degree":[55],"than":[56],"has":[57],"been":[58],"shown":[59],"the":[61,111],"literature.":[62],"Aided":[63],"by":[64],"an":[65],"adaptive":[66],"weighting":[67],"schedule,":[68],"novel":[70],"augmentation":[72],"is":[73],"applied":[74],"at":[75,143],"severe":[76],"levels":[77],"during":[78],"training.":[79],"This":[80],"training":[81],"strategy":[82],"increases":[83],"feature-level":[84],"invariance":[85],"decreases":[89],"domain":[90],"shift":[91],"scenarios.":[94],"At":[95],"inference,":[96],"use":[98],"magnitude-weighted":[100],"fusion":[101],"of":[102,113,146],"features":[103],"from":[104],"parallel":[105],"models":[106,116],"retain":[108],"across":[110],"range":[112],"images.":[114],"DaliID":[115],"achieve":[117],"state-of-the-art":[118],"(SOTA)":[119],"both":[121],"on":[127,152],"seven":[128],"benchmark":[129],"datasets,":[130],"including":[131],"IJB-S,":[132],"TinyFace,":[133],"DeepChange,":[134],"MSMT17.":[136],"Additionally,":[137],"provide":[139],"recaptured":[140],"evaluation":[141],"data":[142],"distance":[145],"750+":[147],"meters":[148],"further":[150],"validate":[151],"real":[153],"long-distance":[154],"imagery.":[156]},"counts_by_year":[{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}
