{"id":"https://openalex.org/W4402352212","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651185","title":"Boundary-Guided Fusion of Multi-Level Features Network for Camouflaged Object Detection","display_name":"Boundary-Guided Fusion of Multi-Level Features Network for Camouflaged Object Detection","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402352212","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651185"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10651185","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10651185","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","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/A5012575786","display_name":"Songlin Li","orcid":"https://orcid.org/0009-0008-6793-5624"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Songlin Li","raw_affiliation_strings":["Xinjiang University,School of Computer Science and Technology,Urumqi,China"],"affiliations":[{"raw_affiliation_string":"Xinjiang University,School of Computer Science and Technology,Urumqi,China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100356635","display_name":"Zhe Li","orcid":"https://orcid.org/0000-0002-0519-7434"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Zhe Li","raw_affiliation_strings":["Hong Kong Polytechnic University,Department of Electrical and Electronic Engineering,HongKong,China,999077"],"affiliations":[{"raw_affiliation_string":"Hong Kong Polytechnic University,Department of Electrical and Electronic Engineering,HongKong,China,999077","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108029779","display_name":"Boyuan Li","orcid":"https://orcid.org/0009-0001-2402-060X"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Boyuan Li","raw_affiliation_strings":["Xinjiang University,School of Computer Science and Technology,Urumqi,China"],"affiliations":[{"raw_affiliation_string":"Xinjiang University,School of Computer Science and Technology,Urumqi,China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100663885","display_name":"Xiuhong Li","orcid":"https://orcid.org/0000-0002-5327-0907"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuhong Li","raw_affiliation_strings":["Xinjiang University,School of Computer Science and Technology,Urumqi,China"],"affiliations":[{"raw_affiliation_string":"Xinjiang University,School of Computer Science and Technology,Urumqi,China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032356055","display_name":"Jiabao Sheng","orcid":"https://orcid.org/0000-0002-7731-8688"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Jiabao Sheng","raw_affiliation_strings":["Hong Kong Polytechnic University,Department of Electrical and Electronic Engineering,HongKong,China,999077"],"affiliations":[{"raw_affiliation_string":"Hong Kong Polytechnic University,Department of Electrical and Electronic Engineering,HongKong,China,999077","institution_ids":["https://openalex.org/I14243506"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5012575786"],"corresponding_institution_ids":["https://openalex.org/I96908189"],"apc_list":null,"apc_paid":null,"fwci":0.5248,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.6556199,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"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/T11019","display_name":"Image Enhancement Techniques","score":0.9962000250816345,"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":0.9894000291824341,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6427557468414307},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.6323575377464294},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5965008735656738},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5423378348350525},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5143809914588928},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.47007089853286743},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4510752558708191},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3562443256378174},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16928553581237793}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6427557468414307},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.6323575377464294},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5965008735656738},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5423378348350525},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5143809914588928},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47007089853286743},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4510752558708191},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3562443256378174},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16928553581237793},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10651185","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10651185","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"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":29,"referenced_works":["https://openalex.org/W1982075130","https://openalex.org/W1994922096","https://openalex.org/W2099342763","https://openalex.org/W2296153970","https://openalex.org/W2943545929","https://openalex.org/W2963112696","https://openalex.org/W2963868681","https://openalex.org/W2990984982","https://openalex.org/W2998449272","https://openalex.org/W3034684132","https://openalex.org/W3035633116","https://openalex.org/W3092344722","https://openalex.org/W3109733326","https://openalex.org/W3164098653","https://openalex.org/W3168112135","https://openalex.org/W3173782971","https://openalex.org/W3175515048","https://openalex.org/W3176152216","https://openalex.org/W3179443972","https://openalex.org/W3190335749","https://openalex.org/W3199914841","https://openalex.org/W4213181610","https://openalex.org/W4283813802","https://openalex.org/W4285310685","https://openalex.org/W4285601297","https://openalex.org/W4308180443","https://openalex.org/W4315490105","https://openalex.org/W4386075673","https://openalex.org/W6757817989"],"related_works":["https://openalex.org/W2737719445","https://openalex.org/W2099421762","https://openalex.org/W2530546662","https://openalex.org/W4239098401","https://openalex.org/W2967030268","https://openalex.org/W2185253430","https://openalex.org/W4210345652","https://openalex.org/W1984178488","https://openalex.org/W4292830139","https://openalex.org/W4319309705"],"abstract_inverted_index":{"Camouflaged":[0],"objects,":[1],"exhibiting":[2],"high":[3],"similarity":[4],"with":[5],"their":[6],"surroundings,":[7],"pose":[8],"a":[9,47,84,95,100,106,120],"substantial":[10],"challenge":[11],"for":[12,26,56,83,149,170],"both":[13],"humans":[14],"and":[15,79,105,122,162],"machines":[16],"to":[17,60,68,158],"detect":[18],"when":[19],"concealed":[20],"within":[21],"the":[22,35,70,74,138,164,171],"environment.":[23],"Existing":[24],"methods":[25],"camouflage":[27,178],"object":[28,142],"detection":[29],"(COD)":[30],"struggle":[31],"in":[32,73],"accurately":[33],"segmenting":[34],"overall":[36],"structure":[37],"of":[38,51,88,94,140,166],"camouflaged":[39,141,151],"objects.":[40],"To":[41],"address":[42],"this":[43],"issue,":[44],"we":[45,64],"propose":[46],"novel":[48],"boundary-guided":[49,62,101],"fusion":[50,108],"multi-level":[52,147],"features":[53,130,148],"network":[54],"(BGFM-Net)":[55],"COD.":[57],"In":[58],"contrast":[59],"existing":[61],"methods,":[63],"pay":[65],"more":[66,85],"attention":[67],"addressing":[69],"significant":[71],"imbalance":[72],"pixel":[75],"quantities":[76],"between":[77],"boundary":[78,89,143],"background":[80,135],"features,":[81,136],"allowing":[82],"comprehensive":[86],"representation":[87],"features.":[90],"BGFM-Net":[91,183],"primarily":[92],"consists":[93],"multi-scale":[96],"aggregation":[97],"module":[98,103,109],"(MSAM),":[99],"feature":[102,124],"(BFM),":[104],"cross-Level":[107],"(CLFM).":[110],"MSAM":[111],"effectively":[112],"integrates":[113,146],"contextual":[114],"semantics":[115],"at":[116],"different":[117],"scales,":[118],"achieving":[119],"powerful":[121],"efficient":[123],"representation.":[125,144],"BFM":[126],"adeptly":[127],"combines":[128],"edge":[129],"while":[131,153],"constraining":[132],"interference":[133],"from":[134],"guiding":[137],"learning":[139],"CLFM":[145],"predicting":[150],"objects":[152],"adaptively":[154],"adjusting":[155],"channel":[156],"weights":[157],"emphasize":[159],"important":[160],"channels":[161,169],"diminish":[163],"impact":[165],"less":[167],"relevant":[168],"task.":[172],"Extensive":[173],"experiments":[174],"on":[175],"three":[176],"benchmark":[177],"datasets":[179],"demonstrate":[180],"that":[181],"our":[182],"outperforms":[184],"other":[185],"state-of-the-art":[186],"COD":[187],"models.":[188]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}