{"id":"https://openalex.org/W7162452951","doi":"https://doi.org/10.48550/arxiv.2605.25651","title":"Hierarchical Consistency Learning for Test-time Adaptation in Camouflage Perception","display_name":"Hierarchical Consistency Learning for Test-time Adaptation in Camouflage Perception","publication_year":2026,"publication_date":"2026-05-25","ids":{"openalex":"https://openalex.org/W7162452951","doi":"https://doi.org/10.48550/arxiv.2605.25651"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.25651","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.25651","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.25651","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045621730","display_name":"Mingfeng Zha","orcid":"https://orcid.org/0000-0003-0186-2940"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zha, Mingfeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137042924","display_name":"Tianyu Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Tianyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137076107","display_name":"Guoqing Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Guoqing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068488598","display_name":"Yunqiang Pei","orcid":"https://orcid.org/0000-0001-6778-4688"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pei, Yunqiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137024561","display_name":"Chaofan Qiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiao, Chaofan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137030678","display_name":"Jiening Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Jiening","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137034600","display_name":"Yang Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137037679","display_name":"Heng Tao Shen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Heng Tao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9165999889373779,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9165999889373779,"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/T11019","display_name":"Image Enhancement Techniques","score":0.023600000888109207,"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/T11996","display_name":"Random lasers and scattering media","score":0.004999999888241291,"subfield":{"id":"https://openalex.org/subfields/3102","display_name":"Acoustics and Ultrasonics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/camouflage","display_name":"Camouflage","score":0.7021999955177307},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6291999816894531},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5612000226974487},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5404000282287598},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5324000120162964},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.426800012588501},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.4203999936580658},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3709000051021576},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.358599990606308}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7239999771118164},{"id":"https://openalex.org/C2776196576","wikidata":"https://www.wikidata.org/wiki/Q196113","display_name":"Camouflage","level":2,"score":0.7021999955177307},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6840999722480774},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6291999816894531},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5612000226974487},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5404000282287598},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5324000120162964},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.426800012588501},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4203999936580658},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4154999852180481},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3709000051021576},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.358599990606308},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3560999929904938},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.35019999742507935},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.3467000126838684},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.3407000005245209},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3384999930858612},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.32910001277923584},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.314300000667572},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.2840000092983246},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.25839999318122864},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.25690001249313354},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.2547000050544739}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.25651","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.25651","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.25651","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.25651","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7602846026420593,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Camouflaged":[0],"object":[1,162],"detection":[2],"(COD)":[3],"aims":[4],"to":[5,36,70,104],"localize":[6],"targets":[7],"that":[8,148,169],"exhibit":[9],"minimal":[10],"perceptual":[11],"differences":[12],"from":[13,27],"backgrounds":[14],"through":[15],"physical":[16],"attributes.":[17],"Existing":[18],"methods,":[19],"constrained":[20],"by":[21,74],"the":[22,48,65,126],"static":[23],"train-then-freeze":[24],"paradigm,":[25],"suffer":[26],"domain":[28],"rigidity":[29],"and":[30,39,89,94,116,138,145,151,159,179],"annotation":[31],"dependency,":[32],"limiting":[33],"their":[34],"adaptability":[35],"scene":[37],"variations":[38],"unseen":[40],"camouflage":[41],"patterns.":[42],"To":[43,120],"overcome":[44],"these,":[45],"we":[46,63,124],"propose":[47],"hierarchical":[49,66,146],"consistency":[50,128],"learning":[51],"(HCL)":[52],"framework,":[53],"which":[54,131],"integrates":[55],"test-time":[56],"adaptation":[57],"for":[58],"dynamic":[59],"representation":[60,67,152],"recalibration.":[61],"Specifically,":[62],"design":[64],"reconstruction":[68,77],"(HRR)":[69],"alleviate":[71],"feature":[72],"entanglement":[73],"synergizing":[75],"spatial":[76],"with":[78],"dual-stream":[79],"frequency-domain":[80],"decomposition,":[81],"enhancing":[82],"robustness":[83,178],"against":[84],"appearance":[85],"homogenization.":[86],"The":[87],"pixel":[88],"spectrum":[90],"inference":[91],"provide":[92],"structural":[93],"contextual":[95],"priors.":[96],"We":[97],"further":[98],"introduce":[99],"task":[100,150],"affinity":[101],"guidance":[102],"(TAG)":[103],"propagate":[105],"knowledge":[106],"across":[107,156],"branches":[108],"via":[109],"channel-wise":[110],"affinity,":[111],"aligning":[112],"local":[113],"discriminative":[114],"cues":[115],"mitigating":[117],"semantic":[118,122],"drift.":[119],"ensure":[121],"invariance,":[123],"formulate":[125],"prototype":[127],"calibration":[129],"(PCC),":[130],"aggregates":[132],"region":[133],"features":[134],"into":[135],"compact":[136],"prototypes":[137],"establishes":[139],"prototype-feature":[140],"similarity.":[141],"This":[142],"imposes":[143],"implicit":[144],"constraints":[147],"bridge":[149],"gaps.":[153],"Extensive":[154],"experiments":[155],"four":[157,160],"camouflaged":[158],"underwater":[161],"benchmarks,":[163],"under":[164,181],"three":[165],"degradation":[166],"settings,":[167],"demonstrate":[168],"our":[170],"method":[171],"consistently":[172],"outperforms":[173],"state-of-the-art":[174],"approaches,":[175],"highlighting":[176],"its":[177],"generalization":[180],"distribution":[182],"shifts.":[183]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-27T00:00:00"}