{"id":"https://openalex.org/W4285601297","doi":"https://doi.org/10.24963/ijcai.2022/186","title":"Boundary-Guided Camouflaged Object Detection","display_name":"Boundary-Guided Camouflaged Object Detection","publication_year":2022,"publication_date":"2022-07-01","ids":{"openalex":"https://openalex.org/W4285601297","doi":"https://doi.org/10.24963/ijcai.2022/186"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2022/186","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/186","pdf_url":"https://www.ijcai.org/proceedings/2022/0186.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2022/0186.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100934924","display_name":"Yujia Sun","orcid":"https://orcid.org/0009-0006-6322-4935"},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yujia Sun","raw_affiliation_strings":["Inner Mongolia University","School of Computer Science, Inner Mongolia University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inner Mongolia University","institution_ids":["https://openalex.org/I2722730"]},{"raw_affiliation_string":"School of Computer Science, Inner Mongolia University, China","institution_ids":["https://openalex.org/I2722730"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100400130","display_name":"Shuo Wang","orcid":"https://orcid.org/0000-0001-7851-3824"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Shuo Wang","raw_affiliation_strings":["ETH Zurich","ETH Zurich, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ETH Zurich","institution_ids":["https://openalex.org/I35440088"]},{"raw_affiliation_string":"ETH Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030724247","display_name":"Chenglizhao Chen","orcid":"https://orcid.org/0000-0001-9982-5667"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenglizhao Chen","raw_affiliation_strings":["China University of Petroleum","College of Computer Science and Technology, China University of Petroleum, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China University of Petroleum","institution_ids":["https://openalex.org/I204553293"]},{"raw_affiliation_string":"College of Computer Science and Technology, China University of Petroleum, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085828297","display_name":"Tian-Zhu Xiang","orcid":"https://orcid.org/0000-0002-3321-1993"},"institutions":[{"id":"https://openalex.org/I4210116052","display_name":"Inception Institute of Artificial Intelligence","ror":"https://ror.org/02664zk40","country_code":"AE","type":"facility","lineage":["https://openalex.org/I4210116052"]}],"countries":["AE"],"is_corresponding":true,"raw_author_name":"Tian-Zhu Xiang","raw_affiliation_strings":["Inception Institute of Artificial Intelligence","Inception Institute of Artificial Intelligence, UAE"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inception Institute of Artificial Intelligence","institution_ids":["https://openalex.org/I4210116052"]},{"raw_affiliation_string":"Inception Institute of Artificial Intelligence, UAE","institution_ids":["https://openalex.org/I4210116052"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5085828297"],"corresponding_institution_ids":["https://openalex.org/I4210116052"],"apc_list":null,"apc_paid":null,"fwci":23.8463,"has_fulltext":false,"cited_by_count":305,"citation_normalized_percentile":{"value":0.99549975,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1335","last_page":"1341"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9882000088691711,"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":0.9732000231742859,"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":0.769845724105835},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7216757535934448},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7131369113922119},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.7069761753082275},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.7022244334220886},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6341655254364014},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.6187727451324463},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5438372492790222},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5374887585639954},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5096631050109863},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5037068724632263},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.46444231271743774},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4375479519367218},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.4342033267021179},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3547176718711853},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08917608857154846},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0841069221496582},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.06932607293128967}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.769845724105835},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7216757535934448},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7131369113922119},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.7069761753082275},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7022244334220886},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6341655254364014},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.6187727451324463},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5438372492790222},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5374887585639954},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5096631050109863},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5037068724632263},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.46444231271743774},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4375479519367218},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.4342033267021179},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3547176718711853},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08917608857154846},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0841069221496582},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.06932607293128967},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.24963/ijcai.2022/186","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/186","pdf_url":"https://www.ijcai.org/proceedings/2022/0186.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2207.00794","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2207.00794","pdf_url":"https://arxiv.org/pdf/2207.00794","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2022/186","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/186","pdf_url":"https://www.ijcai.org/proceedings/2022/0186.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4285601297.pdf","grobid_xml":"https://content.openalex.org/works/W4285601297.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1982075130","https://openalex.org/W1994922096","https://openalex.org/W2051624325","https://openalex.org/W2150587757","https://openalex.org/W2928165649","https://openalex.org/W2939217524","https://openalex.org/W2943545929","https://openalex.org/W2945469194","https://openalex.org/W2963032190","https://openalex.org/W2987701848","https://openalex.org/W2990984982","https://openalex.org/W2998449272","https://openalex.org/W3034552520","https://openalex.org/W3034684132","https://openalex.org/W3035290198","https://openalex.org/W3035422681","https://openalex.org/W3035633116","https://openalex.org/W3092344722","https://openalex.org/W3095586648","https://openalex.org/W3097053213","https://openalex.org/W3109623941","https://openalex.org/W3109733326","https://openalex.org/W3119337483","https://openalex.org/W3164098653","https://openalex.org/W3168112135","https://openalex.org/W3173782971","https://openalex.org/W3176152216","https://openalex.org/W3179443972","https://openalex.org/W3190335749","https://openalex.org/W3199914841","https://openalex.org/W3203700770","https://openalex.org/W4221151441","https://openalex.org/W4312258849"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W4246352526","https://openalex.org/W2121910908","https://openalex.org/W915438175","https://openalex.org/W4390721878"],"abstract_inverted_index":{"Camouflaged":[0],"object":[1,32,37,54,80,85],"detection":[2,86],"(COD),":[3],"segmenting":[4],"objects":[5],"that":[6,78,99],"are":[7],"elegantly":[8],"blended":[9],"into":[10,24],"their":[11],"surroundings,":[12],"is":[13,116],"a":[14,47],"valuable":[15,59],"yet":[16],"challenging":[17,95],"task.":[18],"Existing":[19],"deep-learning":[20],"methods":[21,108],"often":[22],"fall":[23],"the":[25,30,73,104],"difficulty":[26],"of":[27,69,87],"accurately":[28],"identifying":[29],"camouflaged":[31,53,84],"with":[33],"complete":[34],"and":[35,60],"fine":[36],"structure.":[38],"To":[39],"this":[40,43],"end,":[41],"in":[42],"paper,":[44],"we":[45],"propose":[46],"novel":[48],"boundary-guided":[49],"network":[50],"(BGNet)":[51],"for":[52],"detection.":[55],"Our":[56,114],"method":[57],"explores":[58],"extra":[61],"object-related":[62],"edge":[63],"semantics":[64],"to":[65,75],"guide":[66],"representation":[67],"learning":[68],"COD,":[70],"which":[71],"forces":[72],"model":[74],"generate":[76],"features":[77],"highlight":[79],"structure,":[81],"thereby":[82],"promoting":[83],"accurate":[88],"boundary":[89],"localization.":[90],"Extensive":[91],"experiments":[92],"on":[93],"three":[94],"benchmark":[96],"datasets":[97],"demonstrate":[98],"our":[100],"BGNet":[101],"significantly":[102],"outperforms":[103],"existing":[105],"18":[106],"state-of-the-art":[107],"under":[109],"four":[110],"widely-used":[111],"evaluation":[112],"metrics.":[113],"code":[115],"publicly":[117],"available":[118],"at:":[119],"https://github.com/thograce/BGNet.":[120]},"counts_by_year":[{"year":2026,"cited_by_count":47},{"year":2025,"cited_by_count":112},{"year":2024,"cited_by_count":101},{"year":2023,"cited_by_count":44},{"year":2022,"cited_by_count":1}],"updated_date":"2026-08-08T01:25:22.217667","created_date":"2025-10-10T00:00:00"}
