{"id":"https://openalex.org/W4415540307","doi":"https://doi.org/10.1145/3746027.3758294","title":"MCOD: The First Challenging Benchmark for Multispectral Camouflaged Object Detection","display_name":"MCOD: The First Challenging Benchmark for Multispectral Camouflaged Object Detection","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415540307","doi":"https://doi.org/10.1145/3746027.3758294"},"language":null,"primary_location":{"id":"doi:10.1145/3746027.3758294","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3758294","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012917959","display_name":"Yang Li","orcid":"https://orcid.org/0009-0003-4653-7030"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yang Li","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019242095","display_name":"Tingfa Xu","orcid":"https://orcid.org/0000-0001-5452-2662"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tingfa Xu","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112475206","display_name":"Shaowei Bai","orcid":"https://orcid.org/0009-0001-3897-691X"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"ShuYan Bai","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056239970","display_name":"Peifu Liu","orcid":"https://orcid.org/0000-0003-4018-1478"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peifu Liu","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100448292","display_name":"Jianan Li","orcid":"https://orcid.org/0000-0002-6936-9485"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianan Li","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5012917959"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.30732728,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"13339","last_page":"13345"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9998999834060669,"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":0.9998999834060669,"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/T10971","display_name":"Olfactory and Sensory Function Studies","score":0.9843999743461609,"subfield":{"id":"https://openalex.org/subfields/2809","display_name":"Sensory Systems"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9739000201225281,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/multispectral-image","display_name":"Multispectral image","score":0.9406999945640564},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.849399983882904},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6854000091552734},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5983999967575073},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4316999912261963},{"id":"https://openalex.org/keywords/multispectral-pattern-recognition","display_name":"Multispectral pattern recognition","score":0.42260000109672546},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.38449999690055847}],"concepts":[{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.9406999945640564},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.849399983882904},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7473999857902527},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6854000091552734},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6506999731063843},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5983999967575073},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4316999912261963},{"id":"https://openalex.org/C104541649","wikidata":"https://www.wikidata.org/wiki/Q6935090","display_name":"Multispectral pattern recognition","level":3,"score":0.42260000109672546},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41530001163482666},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.38449999690055847},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3625999987125397},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3508000075817108},{"id":"https://openalex.org/C123403432","wikidata":"https://www.wikidata.org/wiki/Q654068","display_name":"Visibility","level":2,"score":0.34209999442100525},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.32030001282691956},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.305400013923645},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.2994999885559082},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2987000048160553},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2718000113964081},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2612999975681305},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.26030001044273376}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746027.3758294","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3758294","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W2100470808","https://openalex.org/W2789621390","https://openalex.org/W2796975587","https://openalex.org/W2938719104","https://openalex.org/W2963868681","https://openalex.org/W2989161706","https://openalex.org/W3011744394","https://openalex.org/W3034684132","https://openalex.org/W3164098653","https://openalex.org/W3176152216","https://openalex.org/W3188168404","https://openalex.org/W4285310685","https://openalex.org/W4313267411","https://openalex.org/W4313535374","https://openalex.org/W4376273993","https://openalex.org/W4385809408","https://openalex.org/W4386930566","https://openalex.org/W4387968022","https://openalex.org/W4388767024","https://openalex.org/W4390492164","https://openalex.org/W4390871785","https://openalex.org/W4393159738","https://openalex.org/W4402727868"],"related_works":[],"abstract_inverted_index":{"Camouflaged":[0],"Object":[1],"Detection":[2],"(COD)":[3],"aims":[4],"to":[5,120,157],"identify":[6],"objects":[7],"that":[8],"blend":[9],"seamlessly":[10],"into":[11],"natural":[12,118],"scenes.":[13],"Although":[14],"RGB-based":[15],"methods":[16,148],"have":[17],"advanced,":[18],"their":[19],"performance":[20,154],"remains":[21],"limited":[22],"under":[23],"challenging":[24,70],"conditions.":[25],"Multispectral":[26],"imagery,":[27],"providing":[28],"rich":[29],"spectral":[30,173],"information,":[31],"offers":[32],"a":[33,114,152,184],"promising":[34],"alternative":[35],"for":[36,51,75,187],"enhanced":[37],"foreground-background":[38],"discrimination.":[39],"However,":[40],"existing":[41],"COD":[42,105,147],"benchmark":[43,71,144],"datasets":[44],"are":[45],"exclusively":[46],"RGB-based,":[47],"lacking":[48],"essential":[49],"support":[50],"multispectral":[52,76,163,191],"approaches,":[53],"which":[54],"has":[55],"impeded":[56],"progress":[57],"in":[58,104,175,190],"this":[59,63,167],"area.":[60],"To":[61],"address":[62],"gap,":[64],"we":[65],"introduce":[66],"MCOD,":[67,150],"the":[68,170],"first":[69],"dataset":[72,112,196],"specifically":[73],"designed":[74],"camouflaged":[77,192],"object":[78,96,136,193],"detection.":[79,194],"MCOD":[80,181],"features":[81],"three":[82],"key":[83],"advantages:":[84],"(i)":[85],"Comprehensive":[86],"challenge":[87,140],"attributes:":[88],"It":[89],"captures":[90],"real-world":[91,109],"difficulties":[92],"such":[93],"as":[94],"small":[95],"sizes":[97],"and":[98,138],"extreme":[99],"lighting":[100],"conditions":[101],"commonly":[102],"encountered":[103],"tasks.":[106],"(ii)":[107],"Diverse":[108],"scenarios:":[110],"The":[111,195],"spans":[113],"wide":[115],"range":[116],"of":[117,172],"environments":[119],"better":[121],"reflect":[122],"practical":[123],"applications.":[124],"(iii)":[125],"High-quality":[126],"pixel-level":[127],"annotations:":[128],"Each":[129],"image":[130],"is":[131,197],"manually":[132],"annotated":[133],"with":[134],"precise":[135],"masks":[137],"corresponding":[139],"attribute":[141],"labels.":[142],"We":[143,179],"eleven":[145],"representative":[146],"on":[149],"observing":[151],"consistent":[153],"drop":[155],"due":[156],"increased":[158],"task":[159],"difficulty.":[160],"Notably,":[161],"integrating":[162],"modalities":[164],"substantially":[165],"alleviates":[166],"degradation,":[168],"highlighting":[169],"value":[171],"information":[174],"enhancing":[176],"detection":[177],"robustness.":[178],"anticipate":[180],"will":[182],"provide":[183],"strong":[185],"foundation":[186],"future":[188],"research":[189],"publicly":[198],"accessible":[199],"at":[200],"https://github.com/yl2900260-bit/MCOD.":[201]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-25T00:00:00"}