{"id":"https://openalex.org/W4405786484","doi":"https://doi.org/10.1109/iros58592.2024.10802512","title":"Enhanced Model Robustness to Input Corruptions by Per-corruption Adaptation of Normalization Statistics","display_name":"Enhanced Model Robustness to Input Corruptions by Per-corruption Adaptation of Normalization Statistics","publication_year":2024,"publication_date":"2024-10-14","ids":{"openalex":"https://openalex.org/W4405786484","doi":"https://doi.org/10.1109/iros58592.2024.10802512"},"language":"en","primary_location":{"id":"doi:10.1109/iros58592.2024.10802512","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros58592.2024.10802512","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/html/2407.06450","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007161861","display_name":"Elena Camuffo","orcid":"https://orcid.org/0000-0002-8351-4650"},"institutions":[{"id":"https://openalex.org/I4210117523","display_name":"Samsung (United Kingdom)","ror":"https://ror.org/01w6gjq94","country_code":"GB","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210117523"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Elena Camuffo","raw_affiliation_strings":["Samsung R&amp;D Institute UK (SRUK),United Kingdom"],"affiliations":[{"raw_affiliation_string":"Samsung R&amp;D Institute UK (SRUK),United Kingdom","institution_ids":["https://openalex.org/I4210117523"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075734012","display_name":"Umberto Michieli","orcid":"https://orcid.org/0000-0003-2666-4342"},"institutions":[{"id":"https://openalex.org/I4210117523","display_name":"Samsung (United Kingdom)","ror":"https://ror.org/01w6gjq94","country_code":"GB","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210117523"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Umberto Michieli","raw_affiliation_strings":["Samsung R&amp;D Institute UK (SRUK),United Kingdom"],"affiliations":[{"raw_affiliation_string":"Samsung R&amp;D Institute UK (SRUK),United Kingdom","institution_ids":["https://openalex.org/I4210117523"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023878224","display_name":"Simone Milani","orcid":"https://orcid.org/0000-0001-8266-5839"},"institutions":[{"id":"https://openalex.org/I138689650","display_name":"University of Padua","ror":"https://ror.org/00240q980","country_code":"IT","type":"education","lineage":["https://openalex.org/I138689650"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Simone Milani","raw_affiliation_strings":["University of Padova,Padova,Italy,35129"],"affiliations":[{"raw_affiliation_string":"University of Padova,Padova,Italy,35129","institution_ids":["https://openalex.org/I138689650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072414837","display_name":"Jijoong Moon","orcid":"https://orcid.org/0000-0003-0888-2143"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jijoong Moon","raw_affiliation_strings":["Samsung Research Korea, Seoul R&amp;D Campus,Seoul,Rep. of Korea"],"affiliations":[{"raw_affiliation_string":"Samsung Research Korea, Seoul R&amp;D Campus,Seoul,Rep. of Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054882290","display_name":"Mete \u00d6zay","orcid":"https://orcid.org/0000-0002-7189-7260"},"institutions":[{"id":"https://openalex.org/I4210117523","display_name":"Samsung (United Kingdom)","ror":"https://ror.org/01w6gjq94","country_code":"GB","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210117523"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mete Ozay","raw_affiliation_strings":["Samsung R&amp;D Institute UK (SRUK),United Kingdom"],"affiliations":[{"raw_affiliation_string":"Samsung R&amp;D Institute UK (SRUK),United Kingdom","institution_ids":["https://openalex.org/I4210117523"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5007161861"],"corresponding_institution_ids":["https://openalex.org/I4210117523"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21590517,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"11558","last_page":"11565"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.7778000235557556,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.7778000235557556,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.6837999820709229,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10007","display_name":"Monetary Policy and Economic Impact","score":0.6802999973297119,"subfield":{"id":"https://openalex.org/subfields/2000","display_name":"General Economics, Econometrics and Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7351453900337219},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.7204199433326721},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6699861288070679},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.5222828388214111},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4652918577194214},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20333188772201538}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7351453900337219},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.7204199433326721},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6699861288070679},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5222828388214111},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4652918577194214},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20333188772201538},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","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/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iros58592.2024.10802512","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros58592.2024.10802512","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},{"id":"pmh:oai:www.research.unipd.it:11577/3548355","is_oa":true,"landing_page_url":"https://arxiv.org/html/2407.06450","pdf_url":null,"source":{"id":"https://openalex.org/S4306402547","display_name":"Padua Research Archive (University of Padova)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I138689650","host_organization_name":"University of Padua","host_organization_lineage":["https://openalex.org/I138689650"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:www.research.unipd.it:11577/3548355","is_oa":true,"landing_page_url":"https://arxiv.org/html/2407.06450","pdf_url":null,"source":{"id":"https://openalex.org/S4306402547","display_name":"Padua Research Archive (University of Padova)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I138689650","host_organization_name":"University of Padua","host_organization_lineage":["https://openalex.org/I138689650"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7799999713897705}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2340897893","https://openalex.org/W2549139847","https://openalex.org/W2949736877","https://openalex.org/W2963163009","https://openalex.org/W2963527685","https://openalex.org/W2963622213","https://openalex.org/W2963766909","https://openalex.org/W2964137095","https://openalex.org/W2982083293","https://openalex.org/W3000172657","https://openalex.org/W3034716173","https://openalex.org/W3037492894","https://openalex.org/W3042011474","https://openalex.org/W3089740767","https://openalex.org/W3114677757","https://openalex.org/W3116074996","https://openalex.org/W3118707261","https://openalex.org/W3193940683","https://openalex.org/W3207649350","https://openalex.org/W3207933706","https://openalex.org/W4296187605","https://openalex.org/W4312761717","https://openalex.org/W4312897837","https://openalex.org/W4313025443","https://openalex.org/W4383108796","https://openalex.org/W4385801109","https://openalex.org/W4386071516","https://openalex.org/W4386075942","https://openalex.org/W4389665817","https://openalex.org/W4389665851","https://openalex.org/W4389667410","https://openalex.org/W4389667643","https://openalex.org/W4390075103","https://openalex.org/W4390874516","https://openalex.org/W4392904447","https://openalex.org/W4394881903","https://openalex.org/W6638667902","https://openalex.org/W6640425456","https://openalex.org/W6730323794","https://openalex.org/W6741768038","https://openalex.org/W6757555829","https://openalex.org/W6758857762","https://openalex.org/W6763136721","https://openalex.org/W6764990469","https://openalex.org/W6766313662","https://openalex.org/W6770979763","https://openalex.org/W6780128236","https://openalex.org/W6780666095","https://openalex.org/W6788125050","https://openalex.org/W6797574089","https://openalex.org/W6803227292","https://openalex.org/W6803414501","https://openalex.org/W6811147225","https://openalex.org/W6811250682","https://openalex.org/W6846159801","https://openalex.org/W6850568775"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2591697403","https://openalex.org/W2944728705","https://openalex.org/W2904022177","https://openalex.org/W2359348847","https://openalex.org/W3011538607","https://openalex.org/W4294432981","https://openalex.org/W4321441197"],"abstract_inverted_index":{"Developing":[0],"a":[1,6,84,120],"reliable":[2,23],"vision":[3,86,111,162],"system":[4],"is":[5],"fundamental":[7],"challenge":[8],"for":[9,156],"robotic":[10],"technologies":[11],"(e.g.,":[12,34,40,46,178],"indoor":[13],"service":[14],"robots":[15],"and":[16,49,137],"outdoor":[17],"autonomous":[18],"robots)":[19],"which":[20],"can":[21,50,149],"ensure":[22],"navigation":[24],"even":[25],"in":[26,54,159,202],"challenging":[27,173],"environments":[28],"such":[29],"as":[30],"adverse":[31],"weather":[32],"conditions":[33,39],"fog,":[35],"rain),":[36],"poor":[37],"lighting":[38],"over/under":[41],"exposure),":[42],"or":[43,71],"sensor":[44],"degradation":[45],"blurring,":[47],"noise),":[48],"guarantee":[51],"high":[52],"performance":[53,170],"safety-critical":[55],"functions.":[56],"Current":[57],"solutions":[58,187],"proposed":[59],"to":[60,105,145,189],"improve":[61],"model":[62,108,155],"robustness":[63,109],"usually":[64],"rely":[65],"on":[66,82,133,172,199],"generic":[67],"data":[68],"augmentation":[69],"techniques":[70],"employ":[72],"costly":[73],"test-time":[74],"adaptation":[75],"methods.":[76],"In":[77,94,164],"addition,":[78],"most":[79,183],"approaches":[80],"focus":[81],"addressing":[83],"single":[85],"task":[87],"(typically,":[88],"image":[89,176],"recognition)":[90],"utilising":[91],"synthetic":[92,200],"data.":[93,147],"this":[95],"paper,":[96],"we":[97],"introduce":[98],"Per-corruption":[99],"Adaptation":[100],"of":[101,110,128,141,184],"Normalization":[102],"statistics":[103,131,143],"(PAN)":[104],"enhance":[106],"the":[107,185,194],"systems.":[112],"Our":[113],"approach":[114],"entails":[115],"three":[116],"key":[117],"components:":[118],"(i)":[119],"corruption":[121,135],"type":[122],"identification":[123],"module,":[124],"(ii)":[125],"dynamic":[126],"adjustment":[127],"normalization":[129],"layer":[130],"based":[132],"identified":[134],"type,":[136],"(iii)":[138],"real-time":[139],"update":[140],"these":[142],"according":[144],"input":[146],"PAN":[148,167,192],"integrate":[150],"seamlessly":[151],"with":[152],"any":[153],"convolutional":[154],"enhanced":[157],"accuracy":[158],"several":[160],"robot":[161],"tasks.":[163,205],"our":[165],"experiments,":[166],"obtains":[168],"robust":[169],"improvement":[171],"real-world":[174],"corrupted":[175],"datasets":[177],"OpenLoris,":[179],"ExDark,":[180],"ACDC),":[181],"where":[182],"current":[186],"tend":[188],"fail.":[190],"Moreover,":[191],"outperforms":[193],"baseline":[195],"models":[196],"by":[197],"20-30%":[198],"benchmarks":[201],"object":[203],"recognition":[204]},"counts_by_year":[],"updated_date":"2026-04-17T18:11:37.981687","created_date":"2025-10-10T00:00:00"}
