{"id":"https://openalex.org/W7128606193","doi":"https://doi.org/10.1109/tmm.2025.3632645","title":"Multi-Clue Sliding Window Attention for Camouflaged Object Detection","display_name":"Multi-Clue Sliding Window Attention for Camouflaged Object Detection","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7128606193","doi":"https://doi.org/10.1109/tmm.2025.3632645"},"language":null,"primary_location":{"id":"doi:10.1109/tmm.2025.3632645","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2025.3632645","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-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/A5125655385","display_name":"Xiaogang Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaogang Song","raw_affiliation_strings":["School of Computer Science and Engineering, Xi&#x2019;an University of Technology, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0001-9841-9624","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Xi&#x2019;an University of Technology, Xi&#x2019;an, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124430200","display_name":"Haoyu Yuan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haoyu Yuan","raw_affiliation_strings":["School of Computer Science and Engineering, Xi&#x2019;an University of Technology, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0009-0005-8956-7461","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Xi&#x2019;an University of Technology, Xi&#x2019;an, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125633475","display_name":"Xiaofeng Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaofeng Lu","raw_affiliation_strings":["School of Computer Science and Engineering, Xi&#x2019;an University of Technology, Xi&#x2019;an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Xi&#x2019;an University of Technology, Xi&#x2019;an, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057162998","display_name":"Xinhong Hei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xinhong Hei","raw_affiliation_strings":["School of Computer Science and Engineering, Xi&#x2019;an University of Technology, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0002-6394-0492","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Xi&#x2019;an University of Technology, Xi&#x2019;an, China","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Rongrong Liu","orcid":"https://orcid.org/0009-0000-1130-506X"},"institutions":[{"id":"https://openalex.org/I4210158926","display_name":"Xijing Hospital","ror":"https://ror.org/05cqe9350","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210158926"]},{"id":"https://openalex.org/I9916479","display_name":"Air Force Medical University","ror":"https://ror.org/00ms48f15","country_code":"CN","type":"education","lineage":["https://openalex.org/I9916479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rongrong Liu","raw_affiliation_strings":["Department of Dermatology, Xijing Hospital, Fourth Military Medical University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0009-0000-1130-506X","affiliations":[{"raw_affiliation_string":"Department of Dermatology, Xijing Hospital, Fourth Military Medical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I4210158926","https://openalex.org/I9916479"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17861914,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"28","issue":null,"first_page":"1037","last_page":"1051"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9666000008583069,"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":0.9666000008583069,"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/T11094","display_name":"Face Recognition and Perception","score":0.003100000089034438,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"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/T10997","display_name":"Ocular Surface and Contact Lens","score":0.0024999999441206455,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sliding-window-protocol","display_name":"Sliding window protocol","score":0.7516000270843506},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.7095999717712402},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6626999974250793},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5837000012397766},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5525000095367432},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.5288000106811523},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.45809999108314514},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.44620001316070557}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8614000082015991},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.7516000270843506},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7095999717712402},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7062000036239624},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6626999974250793},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6358000040054321},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5837000012397766},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5525000095367432},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.5288000106811523},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.45809999108314514},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.44620001316070557},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4458000063896179},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.43700000643730164},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.39320001006126404},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3684000074863434},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3465999960899353},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3377000093460083},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.3294000029563904},{"id":"https://openalex.org/C173414695","wikidata":"https://www.wikidata.org/wiki/Q5510276","display_name":"Fusion mechanism","level":4,"score":0.323199987411499},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.31630000472068787},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.27970001101493835},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.26170000433921814}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2025.3632645","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2025.3632645","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2679547656","display_name":null,"funder_award_id":"52372418","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G792986176","display_name":null,"funder_award_id":"62076201","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":84,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1982075130","https://openalex.org/W2008359794","https://openalex.org/W2021088830","https://openalex.org/W2044712054","https://openalex.org/W2100470808","https://openalex.org/W2142767788","https://openalex.org/W2143100961","https://openalex.org/W2285968993","https://openalex.org/W2884436604","https://openalex.org/W2888407265","https://openalex.org/W2919115771","https://openalex.org/W2943545929","https://openalex.org/W2963868681","https://openalex.org/W2995059005","https://openalex.org/W2997286550","https://openalex.org/W2997891449","https://openalex.org/W2998449272","https://openalex.org/W3027763298","https://openalex.org/W3034684132","https://openalex.org/W3122006940","https://openalex.org/W3131500599","https://openalex.org/W3138516171","https://openalex.org/W3164098653","https://openalex.org/W3168112135","https://openalex.org/W3173370190","https://openalex.org/W3173782971","https://openalex.org/W3173857070","https://openalex.org/W3174857663","https://openalex.org/W3175515048","https://openalex.org/W3176152216","https://openalex.org/W3179443972","https://openalex.org/W3190335749","https://openalex.org/W3199914841","https://openalex.org/W3203700770","https://openalex.org/W3204520143","https://openalex.org/W3210073375","https://openalex.org/W4214561053","https://openalex.org/W4223894216","https://openalex.org/W4225257078","https://openalex.org/W4283813802","https://openalex.org/W4285259878","https://openalex.org/W4285601297","https://openalex.org/W4285728607","https://openalex.org/W4299652825","https://openalex.org/W4306830744","https://openalex.org/W4308180443","https://openalex.org/W4310332935","https://openalex.org/W4312258849","https://openalex.org/W4312806903","https://openalex.org/W4312880622","https://openalex.org/W4313023779","https://openalex.org/W4313535374","https://openalex.org/W4315490105","https://openalex.org/W4319300005","https://openalex.org/W4321021814","https://openalex.org/W4322706642","https://openalex.org/W4323891945","https://openalex.org/W4365801667","https://openalex.org/W4382450131","https://openalex.org/W4382450914","https://openalex.org/W4384159664","https://openalex.org/W4385154014","https://openalex.org/W4385245566","https://openalex.org/W4385413672","https://openalex.org/W4385809408","https://openalex.org/W4385976169","https://openalex.org/W4386066009","https://openalex.org/W4386066015","https://openalex.org/W4386075673","https://openalex.org/W4386076039","https://openalex.org/W4387835104","https://openalex.org/W4387968022","https://openalex.org/W4387968615","https://openalex.org/W4387969595","https://openalex.org/W4390492164","https://openalex.org/W4390871785","https://openalex.org/W4390873221","https://openalex.org/W4391407087","https://openalex.org/W4399923948","https://openalex.org/W4401163468","https://openalex.org/W4401328675","https://openalex.org/W4405844996","https://openalex.org/W4406657538"],"related_works":[],"abstract_inverted_index":{"The":[0],"aim":[1],"of":[2,65,105,141,149,155,215,247],"camouflaged":[3,66,156],"object":[4],"detection":[5,64,154,213],"(COD)":[6],"is":[7,30,201],"to":[8,16,22,61,94,145,175,203,224],"discern":[9],"concealed":[10],"objects":[11,67,157],"within":[12],"the":[13,23,63,80,88,106,122,125,153,163,177,181,185,212,219,241],"background.":[14],"Due":[15],"issues":[17],"such":[18,226],"as":[19,227],"high":[20,245],"similarity":[21],"surrounding":[24],"environment,":[25],"small":[26],"size,":[27],"occlusions,":[28],"COD":[29,43,192,206],"considered":[31],"a":[32,41],"highly":[33],"challenging":[34],"task.":[35],"In":[36,208],"this":[37,75],"paper,":[38],"we":[39,77,161,210],"propose":[40],"novel":[42],"framework,":[44],"named":[45],"multi-clue":[46],"sliding":[47,70],"window":[48,71],"attention":[49,72,166],"network":[50],"(MCSWA-Net),":[51],"stressing":[52],"in":[53],"utilizing":[54],"prior":[55,111,135,150,173],"knowledge":[56],"at":[57,118,158],"different":[58],"semantic":[59],"levels":[60],"guide":[62],"via":[68,180],"multi-scale":[69,164],"(MSWA).":[73],"To":[74],"end,":[76],"first":[78],"devise":[79],"dynamic":[81],"local":[82,97,110],"detail":[83],"capture":[84],"(DLC)":[85],"module":[86,93,108,127,169],"and":[87,98,170,184,195,234],"global":[89,99,134],"interactive":[90],"decoder":[91],"(GID)":[92],"generate":[95],"both":[96],"guidance":[100,165],"clues.":[101],"Particularly,":[102],"each":[103,119],"block":[104],"DLC":[107],"produces":[109],"clue":[112,136],"by":[113,137],"processing":[114],"corresponding":[115],"image":[116,178],"features":[117,140,179],"stage":[120],"from":[121],"encoder.":[123],"And":[124],"GID":[126],"fuses":[128],"all":[129],"adjacent":[130],"encoder":[131],"features,":[132],"generates":[133],"combining":[138],"fusion":[139,167,183],"multi-semantic":[142,159],"levels.":[143],"Further,":[144],"make":[146],"full":[147],"use":[148,171],"clues":[151,174],"guiding":[152],"levels,":[160],"design":[162],"(MAF)":[168],"two":[172],"refine":[176],"group":[182],"MSWA":[186],"separately.":[187],"Experiments":[188],"conducted":[189],"on":[190],"four":[191],"benchmark":[193],"datasets,":[194],"results":[196,239],"demonstrate":[197],"that":[198],"our":[199,216],"MCSWA-Net":[200,217],"superior":[202],"state-of-the-art":[204],"(SOTA)":[205],"methods.":[207],"addition,":[209],"explore":[211],"capabilities":[214],"for":[218],"downstream":[220],"vision":[221],"tasks":[222],"related":[223],"COD,":[225],"polyp":[228],"segmentation,":[229,233],"COVID-19":[230],"lung":[231],"infection":[232],"industrial":[235],"defect":[236],"detection.":[237],"Experimental":[238],"show":[240],"proposed":[242],"method":[243],"has":[244],"degree":[246],"generality.":[248]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-12T00:00:00"}
