{"id":"https://openalex.org/W7169811322","doi":"https://doi.org/10.48550/arxiv.2607.15401","title":"GS-RealBlur: A Flexible Data Acquisition Framework for Real-World Image Deblurring","display_name":"GS-RealBlur: A Flexible Data Acquisition Framework for Real-World Image Deblurring","publication_year":2026,"publication_date":"2026-07-16","ids":{"openalex":"https://openalex.org/W7169811322","doi":"https://doi.org/10.48550/arxiv.2607.15401"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.15401","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.15401","pdf_url":null,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.15401","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5141215174","display_name":"Mingyang Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Mingyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5141177136","display_name":"Zhilu Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Zhilu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5141183274","display_name":"Honglei Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Honglei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5141173330","display_name":"Renlong Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Renlong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090578536","display_name":"X . Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Xiaohe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5141184548","display_name":"Wangmeng Zuo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zuo, Wangmeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9909999966621399,"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":0.9909999966621399,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.004000000189989805,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.0006000000284984708,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/deblurring","display_name":"Deblurring","score":0.9380000233650208},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4876999855041504},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.482699990272522},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.40290001034736633},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.3578000068664551},{"id":"https://openalex.org/keywords/data-acquisition","display_name":"Data acquisition","score":0.35499998927116394},{"id":"https://openalex.org/keywords/centroid","display_name":"Centroid","score":0.35010001063346863}],"concepts":[{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.9380000233650208},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8095999956130981},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.774399995803833},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.755299985408783},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4876999855041504},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.482699990272522},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.40290001034736633},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3578000068664551},{"id":"https://openalex.org/C163985040","wikidata":"https://www.wikidata.org/wiki/Q1172399","display_name":"Data acquisition","level":2,"score":0.35499998927116394},{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.35010001063346863},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.34049999713897705},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.3208000063896179},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.3165999948978424},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2791999876499176},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.271699994802475},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.2549000084400177}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.15401","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.15401","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.15401","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.15401","pdf_url":null,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"High-quality,":[0],"large-scale":[1],"paired":[2],"data":[3,36],"is":[4],"essential":[5],"for":[6,39],"training":[7],"learning-based":[8],"image":[9,41,94,113],"deblurring":[10,151,164],"models.":[11],"However,":[12],"synthetic":[13,172],"blurry":[14,58,88,116],"images":[15,22,68,80],"generally":[16],"lack":[17],"realism,":[18],"while":[19],"real-world":[20,40,163,174],"captured":[21],"require":[23],"complex":[24],"and":[25,47,60,81,133,143,173,178],"inflexible":[26],"camera":[27,55,84],"systems.":[28],"In":[29],"this":[30,91,97],"work,":[31],"we":[32,51,118,139],"propose":[33],"GS-RealBlur,":[34,138],"a":[35,53,62,120,141,150],"acquisition":[37,48],"framework":[38],"deblurring,":[42],"achieving":[43],"both":[44],"blur":[45],"realism":[46],"flexibility.":[49],"Specifically,":[50],"use":[52],"handheld":[54],"to":[56,64,100],"capture":[57,66],"images,":[59],"deploy":[61],"gimbal":[63],"densely":[65],"sharp":[67,79,106],"of":[69,78,86],"the":[70,75,83,101,105,111,115,128],"same":[71],"scene.":[72],"We":[73],"reconstruct":[74],"3D":[76,98],"representation":[77],"calibrate":[82],"pose":[85,102,129],"each":[87],"frame":[89],"within":[90],"3D.":[92],"The":[93,176],"rendered":[95,112],"from":[96],"according":[99],"serves":[103],"as":[104],"counterpart.":[107],"To":[108],"better":[109],"align":[110],"with":[114],"image,":[117],"introduce":[119],"Blur-aware":[121],"Pose":[122],"Refinement":[123],"(BPR)":[124],"module":[125],"that":[126,149],"refines":[127],"using":[130],"appearance":[131],"consistency":[132],"centroid":[134],"alignment":[135],"constraints.":[136],"Leveraging":[137],"construct":[140],"high-quality":[142],"diverse":[144],"dataset.":[145],"Extensive":[146],"experiments":[147],"demonstrate":[148],"model":[152],"trained":[153,169],"on":[154,170],"our":[155],"dataset":[156,179],"achieves":[157],"superior":[158],"generalization":[159],"performance":[160],"across":[161],"various":[162],"benchmarks,":[165],"consistently":[166],"outperforming":[167],"models":[168],"existing":[171],"datasets.":[175],"code":[177],"will":[180],"be":[181],"made":[182],"publicly":[183],"available.":[184]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-21T00:00:00"}