{"id":"https://openalex.org/W4390970253","doi":"https://doi.org/10.1109/tmm.2024.3355630","title":"Motion Deblur by Learning Residual From Events","display_name":"Motion Deblur by Learning Residual From Events","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4390970253","doi":"https://doi.org/10.1109/tmm.2024.3355630"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2024.3355630","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2024.3355630","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/A5073729569","display_name":"Kang Chen","orcid":"https://orcid.org/0009-0001-2161-0364"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kang Chen","raw_affiliation_strings":["School of Electronic Information, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Information, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100736935","display_name":"Lei Yu","orcid":"https://orcid.org/0000-0002-7329-4631"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Yu","raw_affiliation_strings":["School of Electronic Information, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Information, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5073729569"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":3.5187,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.9359542,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"26","issue":null,"first_page":"6632","last_page":"6647"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9969000220298767,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9769999980926514,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/deblurring","display_name":"Deblurring","score":0.8786471486091614},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8215186595916748},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8186168670654297},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.7570510506629944},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7189687490463257},{"id":"https://openalex.org/keywords/motion-blur","display_name":"Motion blur","score":0.6218255162239075},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.5348393321037292},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.5063165426254272},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4708064794540405},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.4252760708332062},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.41114872694015503},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3543604016304016},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.3433228135108948},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.24544763565063477},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.20680347084999084},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1231774389743805}],"concepts":[{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.8786471486091614},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8215186595916748},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8186168670654297},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.7570510506629944},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7189687490463257},{"id":"https://openalex.org/C2777708103","wikidata":"https://www.wikidata.org/wiki/Q852589","display_name":"Motion blur","level":3,"score":0.6218255162239075},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.5348393321037292},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.5063165426254272},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4708064794540405},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.4252760708332062},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.41114872694015503},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3543604016304016},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.3433228135108948},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.24544763565063477},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.20680347084999084},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1231774389743805},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2024.3355630","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2024.3355630","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/G4493179999","display_name":null,"funder_award_id":"62271354","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7830843176","display_name":null,"funder_award_id":"61871297","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":51,"referenced_works":["https://openalex.org/W206948248","https://openalex.org/W1901129140","https://openalex.org/W1980178290","https://openalex.org/W2132870234","https://openalex.org/W2560533888","https://openalex.org/W2594491944","https://openalex.org/W2948208276","https://openalex.org/W2962785568","https://openalex.org/W2963091558","https://openalex.org/W2970672284","https://openalex.org/W2998281665","https://openalex.org/W3031696893","https://openalex.org/W3034789174","https://openalex.org/W3040838455","https://openalex.org/W3048875473","https://openalex.org/W3097097310","https://openalex.org/W3097900310","https://openalex.org/W3110052477","https://openalex.org/W3146017629","https://openalex.org/W3173857070","https://openalex.org/W3177211876","https://openalex.org/W3202040256","https://openalex.org/W3203854346","https://openalex.org/W3209159014","https://openalex.org/W3212386989","https://openalex.org/W4214638086","https://openalex.org/W4221155341","https://openalex.org/W4226453196","https://openalex.org/W4289752563","https://openalex.org/W4292259411","https://openalex.org/W4292829037","https://openalex.org/W4304014386","https://openalex.org/W4304086149","https://openalex.org/W4312238950","https://openalex.org/W4312280868","https://openalex.org/W4312383539","https://openalex.org/W4312608394","https://openalex.org/W4312623579","https://openalex.org/W4312938066","https://openalex.org/W4313130451","https://openalex.org/W4313166393","https://openalex.org/W4321231530","https://openalex.org/W4321505055","https://openalex.org/W4380053099","https://openalex.org/W4382457774","https://openalex.org/W4385245566","https://openalex.org/W4385801024","https://openalex.org/W4385801682","https://openalex.org/W4385805087","https://openalex.org/W4385832628","https://openalex.org/W6755494875"],"related_works":["https://openalex.org/W4224288641","https://openalex.org/W4382450485","https://openalex.org/W4229459996","https://openalex.org/W2232201529","https://openalex.org/W2066613488","https://openalex.org/W2031788393","https://openalex.org/W2558246008","https://openalex.org/W4293737289","https://openalex.org/W4391468564","https://openalex.org/W2041468730"],"abstract_inverted_index":{"Conventional":[0],"cameras":[1],"face":[2],"challenges":[3],"when":[4],"capturing":[5],"motion":[6,18,52,113],"information":[7],"during":[8,85],"the":[9,17,50,58,69,74,78,86,89,92,99,104,109,117,141,159,173],"exposure":[10],"due":[11],"to":[12,67,102,139],"their":[13],"physical":[14,110],"design,":[15],"rendering":[16],"deblurring":[19],"task":[20],"ill-posed.":[21],"To":[22,115],"this":[23],"end,":[24],"we":[25,128],"propose":[26,129],"a":[27,40,44,61,130],"Two-stage":[28],"Residual-based":[29],"Motion":[30],"Deblurring":[31],"(TRMD)":[32],"framework":[33],"for":[34,125],"an":[35],"event":[36,123,176],"camera,":[37],"which":[38,72],"converts":[39],"blurry":[41,100],"image":[42,101,121],"into":[43],"sequence":[45,106],"of":[46,112,120,145],"sharp":[47],"images,":[48],"leveraging":[49],"abundant":[51],"features":[53,144],"encoded":[54],"in":[55],"events.":[56],"In":[57,88],"first":[59],"stage,":[60,91],"residual":[62,70,126],"estimation":[63],"network":[64],"is":[65],"trained":[66],"estimate":[68],"sequence,":[71],"measures":[73],"intensity":[75],"difference":[76],"between":[77],"intermediate":[79],"frame":[80],"and":[81,122,163,170],"other":[82],"frames":[83],"sampled":[84],"exposure.":[87],"subsequent":[90],"previously":[93],"estimated":[94],"residuals":[95],"are":[96],"combined":[97],"with":[98,167],"reconstruct":[103],"deblurred":[105],"based":[107,134],"on":[108,135,158,172],"model":[111],"blur.":[114],"facilitate":[116],"efficient":[118],"integration":[119],"modalities":[124],"estimation,":[127],"cross-modal":[131],"fusion":[132],"module":[133],"spatial-channel":[136],"attention,":[137],"aiming":[138],"fuse":[140],"complementary":[142],"spatial-temporal":[143],"two":[146],"modalities.":[147],"Extensive":[148],"experiments":[149],"demonstrate":[150],"that":[151],"our":[152],"method":[153],"outperforms":[154],"current":[155],"state-of-the-art":[156],"approaches":[157],"synthetic":[160],"dataset":[161,177],"GOPRO":[162],"produces":[164],"superior":[165],"visualization":[166],"less":[168],"noise":[169],"artifacts":[171],"real":[174],"blur":[175],"REBlur.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-26T15:22:09.906841","created_date":"2025-10-10T00:00:00"}