{"id":"https://openalex.org/W4416361311","doi":"https://doi.org/10.1109/wacv61042.2026.00250","title":"RobustGait: Robustness Analysis for Appearance Based Gait Recognition","display_name":"RobustGait: Robustness Analysis for Appearance Based Gait Recognition","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W4416361311","doi":"https://doi.org/10.1109/wacv61042.2026.00250"},"language":null,"primary_location":{"id":"doi:10.1109/wacv61042.2026.00250","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00250","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2511.13065","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033519128","display_name":"Reeshoon Sayera","orcid":null},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Reeshoon Sayera","raw_affiliation_strings":["University of Central Florida"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Central Florida","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100755285","display_name":"Akash Kumar","orcid":"https://orcid.org/0000-0001-7125-1737"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Akash Kumar","raw_affiliation_strings":["University of Central Florida"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Central Florida","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020975134","display_name":"Sirshapan Mitra","orcid":null},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sirshapan Mitra","raw_affiliation_strings":["University of Central Florida"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Central Florida","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092676336","display_name":"Prudvi Kamtam","orcid":null},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Prudvi Kamtam","raw_affiliation_strings":["University of Central Florida"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Central Florida","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002721667","display_name":"Yogesh Singh Rawat","orcid":"https://orcid.org/0000-0003-4052-6798"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yogesh S Rawat","raw_affiliation_strings":["University of Central Florida"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Central Florida","institution_ids":["https://openalex.org/I106165777"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5033519128"],"corresponding_institution_ids":["https://openalex.org/I106165777"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00266253,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2451","last_page":"2552"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10114","display_name":"Balance, Gait, and Falls Prevention","score":0.0007999999797903001,"subfield":{"id":"https://openalex.org/subfields/3612","display_name":"Physical Therapy, Sports Therapy and Rehabilitation"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.0007999999797903001,"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/silhouette","display_name":"Silhouette","score":0.8737999796867371},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.748199999332428},{"id":"https://openalex.org/keywords/gait","display_name":"Gait","score":0.47519999742507935},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.39340001344680786},{"id":"https://openalex.org/keywords/freak","display_name":"FREAK","score":0.3856000006198883},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.36640000343322754},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35269999504089355}],"concepts":[{"id":"https://openalex.org/C58103923","wikidata":"https://www.wikidata.org/wiki/Q2286025","display_name":"Silhouette","level":2,"score":0.8737999796867371},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.748199999332428},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6322000026702881},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5943999886512756},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49950000643730164},{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.47519999742507935},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.39340001344680786},{"id":"https://openalex.org/C2776717989","wikidata":"https://www.wikidata.org/wiki/Q19410276","display_name":"FREAK","level":2,"score":0.3856000006198883},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.36640000343322754},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35269999504089355},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.33070001006126404},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.3041999936103821},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.29269999265670776},{"id":"https://openalex.org/C173906292","wikidata":"https://www.wikidata.org/wiki/Q1493441","display_name":"Gait analysis","level":3,"score":0.2906000018119812},{"id":"https://openalex.org/C177918212","wikidata":"https://www.wikidata.org/wiki/Q803623","display_name":"Perturbation (astronomy)","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.25360000133514404}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/wacv61042.2026.00250","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00250","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2511.13065","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2511.13065","pdf_url":"https://arxiv.org/pdf/2511.13065","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:doi:10.48550/arxiv.2511.13065","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"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":"Article"},{"id":"doi:10.48550/arxiv.2511.13065","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.13065","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:2511.13065","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2511.13065","pdf_url":"https://arxiv.org/pdf/2511.13065","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Appearance-based":[0],"gait":[1,35,63,94,124,128],"recognition":[2,36,64,125],"has":[3],"achieved":[4],"strong":[5],"performance":[6,171],"on":[7,88,148],"controlled":[8],"datasets,":[9],"yet":[10],"systematic":[11],"evaluation":[12,32,39],"of":[13,33,45,62,141,152],"its":[14],"robustness":[15,31,145],"to":[16,121,133],"real-world":[17,111],"corruptions":[18],"and":[19,56,66,83,90,113,154,167,172],"silhouette":[20,52,119,134],"variability":[21],"remains":[22],"lacking.":[23],"We":[24,96],"present":[25],"RobustGait,":[26],"a":[27],"framework":[28],"for":[29],"fine-grained":[30],"appearance-based":[34],"systems.":[37,95,126,176],"RobustGait":[38],"spans":[40],"four":[41],"dimensions:":[42],"the":[43,51,59,106,122,150,155],"type":[44,151],"perturbation":[46,153],"(digital,":[47],"environmental,":[48],"temporal,":[49],"occlusion),":[50],"extraction":[53,120],"method":[54],"(segmentation":[55],"parsing":[57],"networks),":[58],"architectural":[60,156],"capacities":[61],"models,":[65],"various":[67],"deployment":[68],"scenarios.":[69],"The":[70],"benchmark":[71,142],"introduces":[72],"15":[73],"corruption":[74],"types":[75],"at":[76,105],"5":[77],"severity":[78],"levels":[79],"across":[80,98],"CASIA-B,":[81],"CCPG,":[82],"SUSTech1K,":[84],"with":[85],"in-the-wild":[86],"validation":[87],"MEVID,":[89],"evaluates":[91],"six":[92],"state-of-the-art":[93],"came":[97],"several":[99],"exciting":[100],"insights.":[101],"First,":[102],"applying":[103],"noise":[104],"RGB":[107],"level":[108],"better":[109],"reflects":[110],"degradation,":[112],"reveals":[114],"how":[115],"distortions":[116],"propagate":[117],"through":[118],"downstream":[123],"Second,":[127],"accuracy":[129],"is":[130,146],"highly":[131],"sensitive":[132],"extractor":[135],"biases,":[136],"revealing":[137],"an":[138],"overlooked":[139],"source":[140],"bias.":[143],"Third,":[144],"dependent":[147],"both":[149],"design.":[157],"Finally,":[158],"we":[159],"explore":[160],"robustness-enhancing":[161],"strategies,":[162],"showing":[163],"that":[164],"noise-aware":[165],"training":[166],"knowledge":[168],"distillation":[169],"improve":[170],"move":[173],"toward":[174],"deployment-ready":[175]},"counts_by_year":[],"updated_date":"2026-05-07T06:04:25.777469","created_date":"2025-11-19T00:00:00"}