{"id":"https://openalex.org/W4406859963","doi":"https://doi.org/10.1109/apsipaasc63619.2025.10849009","title":"NeRF-FCM: Feature Calibration Mechanisms for NeRF-based 3D Object Detection","display_name":"NeRF-FCM: Feature Calibration Mechanisms for NeRF-based 3D Object Detection","publication_year":2024,"publication_date":"2024-12-03","ids":{"openalex":"https://openalex.org/W4406859963","doi":"https://doi.org/10.1109/apsipaasc63619.2025.10849009"},"language":"en","primary_location":{"id":"doi:10.1109/apsipaasc63619.2025.10849009","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc63619.2025.10849009","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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/A5114412527","display_name":"Hana Lebeta Goshu","orcid":"https://orcid.org/0009-0001-1680-3348"},"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":true,"raw_author_name":"Hana Lebeta Goshu","raw_affiliation_strings":["The Hong Kong Polytechnic University,Hong Kong"],"affiliations":[{"raw_affiliation_string":"The Hong Kong Polytechnic University,Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012943082","display_name":"Jun Xiao","orcid":"https://orcid.org/0000-0002-4935-7866"},"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":"Jun Xiao","raw_affiliation_strings":["The Hong Kong Polytechnic University,Hong Kong"],"affiliations":[{"raw_affiliation_string":"The Hong Kong Polytechnic University,Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103501599","display_name":"K. S. Chan","orcid":"https://orcid.org/0000-0003-3524-8017"},"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":"Kin-Chung Chan","raw_affiliation_strings":["The Hong Kong Polytechnic University,Hong Kong"],"affiliations":[{"raw_affiliation_string":"The Hong Kong Polytechnic University,Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100438377","display_name":"Cong Zhang","orcid":"https://orcid.org/0000-0002-2071-329X"},"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":"Cong Zhang","raw_affiliation_strings":["The Hong Kong Polytechnic University,Hong Kong"],"affiliations":[{"raw_affiliation_string":"The Hong Kong Polytechnic University,Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036538571","display_name":"Mulugeta Tegegn Gemeda","orcid":"https://orcid.org/0000-0003-3258-5085"},"institutions":[{"id":"https://openalex.org/I1443707","display_name":"Jimma University","ror":"https://ror.org/05eer8g02","country_code":"ET","type":"education","lineage":["https://openalex.org/I1443707"]}],"countries":["ET"],"is_corresponding":false,"raw_author_name":"Mulugeta Tegegn Gemeda","raw_affiliation_strings":["Jimma Institute of Technology,Ethiopia"],"affiliations":[{"raw_affiliation_string":"Jimma Institute of Technology,Ethiopia","institution_ids":["https://openalex.org/I1443707"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019678322","display_name":"Kin\u2010Man Lam","orcid":"https://orcid.org/0000-0002-0422-8454"},"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":"Kin-Man Lam","raw_affiliation_strings":["The Hong Kong Polytechnic University,Hong Kong"],"affiliations":[{"raw_affiliation_string":"The Hong Kong Polytechnic University,Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5114412527"],"corresponding_institution_ids":["https://openalex.org/I14243506"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27389701,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9815000295639038,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9815000295639038,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9556000232696533,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.7545689940452576},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7421896457672119},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6398224234580994},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6106763482093811},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.586372971534729},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.551134467124939},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5464734435081482},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40478453040122986},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.19360792636871338}],"concepts":[{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.7545689940452576},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7421896457672119},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6398224234580994},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6106763482093811},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.586372971534729},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.551134467124939},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5464734435081482},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40478453040122986},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.19360792636871338},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/apsipaasc63619.2025.10849009","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc63619.2025.10849009","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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":37,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W2565639579","https://openalex.org/W2594519801","https://openalex.org/W2752782242","https://openalex.org/W2780829839","https://openalex.org/W2795321555","https://openalex.org/W2884585870","https://openalex.org/W2963727135","https://openalex.org/W2964979676","https://openalex.org/W2968296999","https://openalex.org/W2982363097","https://openalex.org/W2982770724","https://openalex.org/W2988715931","https://openalex.org/W2999947750","https://openalex.org/W3010454265","https://openalex.org/W3034429258","https://openalex.org/W3034552520","https://openalex.org/W3096387236","https://openalex.org/W3096754345","https://openalex.org/W3097660860","https://openalex.org/W3109428934","https://openalex.org/W3109585842","https://openalex.org/W3171032126","https://openalex.org/W3183392001","https://openalex.org/W3215100485","https://openalex.org/W3215207332","https://openalex.org/W4214625308","https://openalex.org/W4221151978","https://openalex.org/W4312508629","https://openalex.org/W4313154783","https://openalex.org/W4367182782","https://openalex.org/W4383503807","https://openalex.org/W4386075506","https://openalex.org/W4386433016","https://openalex.org/W4390873153","https://openalex.org/W6620707391","https://openalex.org/W6637242042"],"related_works":["https://openalex.org/W3147584709","https://openalex.org/W2737719445","https://openalex.org/W2898210368","https://openalex.org/W4239098401","https://openalex.org/W2977677679","https://openalex.org/W1992327129","https://openalex.org/W2381986121","https://openalex.org/W2382480268","https://openalex.org/W4292830139","https://openalex.org/W4319309705"],"abstract_inverted_index":{"With":[0],"the":[1,29,79,98,119,124,130,136,140,149,163,176],"fast":[2],"development":[3],"of":[4,32,81,100,139,154],"3D":[5,7,39,42,84,101,120,185,189],"vision,":[6],"object":[8],"detection":[9,43,102],"based":[10,104,134],"on":[11,105,135,162],"posed":[12,46,106],"RGB":[13,47,107],"images":[14,48,108],"has":[15],"become":[16],"increasingly":[17],"popular":[18],"and":[19,65,127,159,166],"attracted":[20],"significant":[21],"attention":[22],"from":[23,62,123],"researchers":[24],"in":[25,37,188,208],"recent":[26,41],"years.":[27],"Given":[28],"remarkable":[30],"performance":[31,80,99],"Neural":[33],"Radiance":[34],"Field":[35],"(NeRF)":[36],"modeling":[38],"scenes,":[40],"methods":[44],"utilizing":[45],"generated":[49],"by":[50,110,197],"NeRF":[51,111,198],"models":[52,59,103],"have":[53],"achieved":[54],"promising":[55],"results.":[56],"However,":[57],"NeRF-based":[58,83],"often":[60],"suffer":[61],"poor":[63],"generalization":[64],"are":[66,194],"prone":[67],"to":[68,96],"generating":[69],"inconsistent":[70],"image":[71],"content":[72],"for":[73,132],"unseen":[74],"views,":[75],"which":[76],"inevitably":[77],"degrades":[78],"existing":[82],"detectors.":[85],"In":[86],"this":[87],"paper,":[88],"we":[89],"propose":[90],"an":[91],"effective":[92],"feature":[93],"calibration":[94],"method":[95,116,146,180],"enhance":[97],"produced":[109],"models.":[112],"Specifically,":[113],"our":[114,145,179],"proposed":[115],"efficiently":[117],"recalibrates":[118],"features":[121],"extracted":[122],"backbone":[125],"network,":[126],"adaptively":[128],"computes":[129],"weights":[131],"fusion":[133],"statistical":[137],"properties":[138],"features.":[141],"Experiments":[142],"show":[143],"that":[144],"significantly":[147],"outperforms":[148],"baseline":[150,177],"model,":[151,178],"achieving":[152],"improvement":[153],"+8.6":[155],"AP@0.5,":[156,158],"+5.5":[157],"+5.1":[160],"AP@0.5":[161],"Hypersim,":[164],"3D-FRONT,":[165],"ScanNet":[167],"benchmarks,":[168],"respectively,":[169],"with":[170,175,204],"anchor-free":[171],"heads.":[172],"Particularly,":[173],"compared":[174],"can":[181],"more":[182],"accurately":[183],"predict":[184],"bounding":[186],"boxes":[187],"space,":[190],"even":[191],"when":[192],"objects":[193],"poorly":[195],"reconstructed":[196],"while":[199],"keeping":[200],"low":[201],"computational":[202],"costs":[203],"a":[205],"minimal":[206],"increase":[207],"model":[209],"complexity.":[210]},"counts_by_year":[],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}
