{"id":"https://openalex.org/W4206416562","doi":"https://doi.org/10.1109/vcip53242.2021.9675437","title":"Plug-and-Play Deblurring for Robust Object Detection","display_name":"Plug-and-Play Deblurring for Robust Object Detection","publication_year":2021,"publication_date":"2021-12-05","ids":{"openalex":"https://openalex.org/W4206416562","doi":"https://doi.org/10.1109/vcip53242.2021.9675437"},"language":"en","primary_location":{"id":"doi:10.1109/vcip53242.2021.9675437","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip53242.2021.9675437","pdf_url":null,"source":{"id":"https://openalex.org/S4363608378","display_name":"2021 International Conference on Visual Communications and Image Processing (VCIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Visual Communications and Image Processing (VCIP)","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/A5009471663","display_name":"Gerald Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I75421653","display_name":"University of Missouri\u2013Kansas City","ror":"https://ror.org/01w0d5g70","country_code":"US","type":"education","lineage":["https://openalex.org/I75421653"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Gerald Xie","raw_affiliation_strings":["University of Missouri, Kansas City"],"affiliations":[{"raw_affiliation_string":"University of Missouri, Kansas City","institution_ids":["https://openalex.org/I75421653"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100380625","display_name":"Zhu Li","orcid":"https://orcid.org/0000-0002-8246-177X"},"institutions":[{"id":"https://openalex.org/I75421653","display_name":"University of Missouri\u2013Kansas City","ror":"https://ror.org/01w0d5g70","country_code":"US","type":"education","lineage":["https://openalex.org/I75421653"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhu Li","raw_affiliation_strings":["University of Missouri, Kansas City"],"affiliations":[{"raw_affiliation_string":"University of Missouri, Kansas City","institution_ids":["https://openalex.org/I75421653"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038036261","display_name":"Shuvra S. Bhattacharyya","orcid":"https://orcid.org/0000-0001-7719-1106"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shuvra Bhattacharyya","raw_affiliation_strings":["University of Maryland, College Park"],"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083067091","display_name":"Asif Mehmood","orcid":"https://orcid.org/0000-0002-3019-9191"},"institutions":[{"id":"https://openalex.org/I1280414376","display_name":"United States Air Force Research Laboratory","ror":"https://ror.org/02e2egq70","country_code":"US","type":"facility","lineage":["https://openalex.org/I1280414376","https://openalex.org/I1330347796","https://openalex.org/I4210102105","https://openalex.org/I4389425425"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Asif Mehmood","raw_affiliation_strings":["Air Force Research Laboratory"],"affiliations":[{"raw_affiliation_string":"Air Force Research Laboratory","institution_ids":["https://openalex.org/I1280414376"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5009471663"],"corresponding_institution_ids":["https://openalex.org/I75421653"],"apc_list":null,"apc_paid":null,"fwci":0.3267,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.70190092,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"41","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998000264167786,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998000264167786,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/deblurring","display_name":"Deblurring","score":0.9779489040374756},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7825787663459778},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7638663649559021},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7485989928245544},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.7023949027061462},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5781437158584595},{"id":"https://openalex.org/keywords/motion-blur","display_name":"Motion blur","score":0.5706961154937744},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5367753505706787},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5027856826782227},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.4726986885070801},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3422713279724121},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.3366996645927429},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.29555466771125793},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.2726444602012634},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09531262516975403}],"concepts":[{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.9779489040374756},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7825787663459778},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7638663649559021},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7485989928245544},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7023949027061462},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5781437158584595},{"id":"https://openalex.org/C2777708103","wikidata":"https://www.wikidata.org/wiki/Q852589","display_name":"Motion blur","level":3,"score":0.5706961154937744},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5367753505706787},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5027856826782227},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.4726986885070801},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3422713279724121},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.3366996645927429},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.29555466771125793},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2726444602012634},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09531262516975403},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vcip53242.2021.9675437","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip53242.2021.9675437","pdf_url":null,"source":{"id":"https://openalex.org/S4363608378","display_name":"2021 International Conference on Visual Communications and Image Processing (VCIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Visual Communications and Image Processing (VCIP)","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":30,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1916935112","https://openalex.org/W2103913786","https://openalex.org/W2129987527","https://openalex.org/W2141115311","https://openalex.org/W2147298660","https://openalex.org/W2194775991","https://openalex.org/W2300657047","https://openalex.org/W2407521645","https://openalex.org/W2560533888","https://openalex.org/W2950800384","https://openalex.org/W2963037989","https://openalex.org/W2963289201","https://openalex.org/W2963312584","https://openalex.org/W2964030969","https://openalex.org/W2982795046","https://openalex.org/W2997058852","https://openalex.org/W2997747012","https://openalex.org/W3018757597","https://openalex.org/W3034789174","https://openalex.org/W3035484352","https://openalex.org/W3106250896","https://openalex.org/W3170697543","https://openalex.org/W4254979477","https://openalex.org/W6679461745","https://openalex.org/W6681807782","https://openalex.org/W6750596557","https://openalex.org/W6777046832","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W4224288641","https://openalex.org/W4382450485","https://openalex.org/W2557898294","https://openalex.org/W2031788393","https://openalex.org/W2232201529","https://openalex.org/W2558246008","https://openalex.org/W4293737289","https://openalex.org/W2359633702","https://openalex.org/W2033307681","https://openalex.org/W3153582293"],"abstract_inverted_index":{"Object":[0],"detection":[1,26,155,172],"is":[2,74],"a":[3,41,108,137],"classic":[4],"computer":[5],"vision":[6,70,93,120],"task,":[7],"which":[8,29,95],"learns":[9],"the":[10,62,68,88,92,104,118,124,128,147,153,164,167],"mapping":[11],"between":[12],"an":[13],"image":[14],"and":[15,66,144,146,170],"object":[16,25,47,154],"bounding":[17],"boxes":[18],"+":[19],"class":[20],"labels.":[21],"Many":[22],"applications":[23],"of":[24,79,82,91,99,166],"involve":[27],"images":[28,65],"are":[30,134],"prone":[31],"to":[32,51,60,126],"degradation":[33],"at":[34],"capture":[35],"time,":[36],"notably":[37],"motion":[38],"blur":[39,54,142],"from":[40,136],"moving":[42],"camera":[43],"like":[44],"UAVs":[45],"or":[46],"itself.":[48],"One":[49],"approach":[50],"handling":[52],"this":[53],"involves":[55],"using":[56],"common":[57],"deblurring":[58,115],"methods":[59,84],"recover":[61],"clean":[63],"pixel":[64],"then":[67,171],"apply":[69],"task.":[71],"This":[72],"task":[73,121,129],"typically":[75],"ill-posed.":[76],"On":[77],"top":[78],"this,":[80],"application":[81],"these":[83],"also":[85],"add":[86],"onto":[87],"inference":[89,159],"time":[90,160],"network,":[94],"can":[96],"hinder":[97],"performance":[98],"video":[100],"inputs.":[101],"To":[102],"address":[103],"issues,":[105],"we":[106],"propose":[107],"novel":[109],"plug-and-play":[110],"(PnP)":[111],"solution":[112],"that":[113],"insert":[114],"features":[116,133],"into":[117],"target":[119],"network":[122,140,156],"without":[123],"need":[125],"retrain":[127],"network.":[130],"The":[131],"deblur":[132,169],"learned":[135],"classification":[138],"loss":[139],"on":[141],"strength":[143],"directions,":[145],"PnP":[148],"scheme":[149],"works":[150],"well":[151],"with":[152,157,163],"minimum":[158],"complexity,":[161],"compared":[162],"state":[165],"art":[168],"solution.":[173]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}