{"id":"https://openalex.org/W7140286037","doi":"https://doi.org/10.48550/arxiv.2603.22998","title":"VQ-Jarvis: Retrieval-Augmented Video Restoration Agent with Sharp Vision and Fast Thought","display_name":"VQ-Jarvis: Retrieval-Augmented Video Restoration Agent with Sharp Vision and Fast Thought","publication_year":2026,"publication_date":"2026-03-24","ids":{"openalex":"https://openalex.org/W7140286037","doi":"https://doi.org/10.48550/arxiv.2603.22998"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.22998","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.22998","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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.2603.22998","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130621570","display_name":"Xuanyu Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xuanyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130609858","display_name":"Weiqi Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Weiqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081482765","display_name":"Qunliang Xing","orcid":"https://orcid.org/0000-0002-3007-716X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xing, Qunliang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083393024","display_name":"Jingfen Xie","orcid":"https://orcid.org/0000-0002-3547-6725"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Jingfen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130610520","display_name":"Bin Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Bin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130610852","display_name":"Junlin Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Junlin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130616590","display_name":"Li Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130578414","display_name":"Jian Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Jian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130623409","display_name":"Shijie Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Shijie","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/T11165","display_name":"Image and Video Quality Assessment","score":0.3986000120639801,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.3986000120639801,"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":0.1436000019311905,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.12319999933242798,"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/scheduling","display_name":"Scheduling (production processes)","score":0.5453000068664551},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4341000020503998},{"id":"https://openalex.org/keywords/video-quality","display_name":"Video quality","score":0.421999990940094},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.4219000041484833},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.41769999265670776},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.3986000120639801},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.3515999913215637}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.70169997215271},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.5453000068664551},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5034000277519226},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4341000020503998},{"id":"https://openalex.org/C103910844","wikidata":"https://www.wikidata.org/wiki/Q2631256","display_name":"Video quality","level":3,"score":0.421999990940094},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4219000041484833},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.41769999265670776},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.3986000120639801},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3776000142097473},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.3515999913215637},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.349700003862381},{"id":"https://openalex.org/C55416958","wikidata":"https://www.wikidata.org/wiki/Q6206757","display_name":"Job shop scheduling","level":3,"score":0.3425999879837036},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.32679998874664307},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3018999993801117},{"id":"https://openalex.org/C2779679103","wikidata":"https://www.wikidata.org/wiki/Q5251805","display_name":"Degradation (telecommunications)","level":2,"score":0.2969000041484833},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.2906000018119812},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.2752000093460083},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2745000123977661},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.2655999958515167},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.2515999972820282}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.22998","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.22998","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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.2603.22998","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.22998","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":[{"id":"https://metadata.un.org/sdg/11","score":0.5699432492256165,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Video":[0],"restoration":[1,31,51,71,77,148],"in":[2,152],"real-world":[3],"scenarios":[4],"is":[5,60,169],"challenged":[6],"by":[7,35],"heterogeneous":[8],"degradations,":[9],"where":[10],"static":[11],"architectures":[12],"and":[13,39,56,66,104,119,174],"fixed":[14],"inference":[15],"pipelines":[16],"often":[17],"fail":[18],"to":[19,62,124,141,171],"generalize.":[20],"Recent":[21],"agent-based":[22],"approaches":[23],"offer":[24],"dynamic":[25],"decision":[26],"making,":[27],"yet":[28],"existing":[29,183],"video":[30,50,89,142],"agents":[32],"remain":[33],"limited":[34],"insufficient":[36],"quality":[37],"perception":[38,122],"inefficient":[40],"search":[41,168],"strategies.":[42],"We":[43],"propose":[44],"VQ-Jarvis,":[45],"a":[46,114,120,134,153,157,165],"retrieval-augmented,":[47],"all-in-one":[48],"intelligent":[49],"agent":[52,126],"with":[53,93],"sharper":[54],"vision":[55],"faster":[57],"thought.":[58],"VQ-Jarvis":[59,180],"designed":[61],"accurately":[63],"perceive":[64],"degradations":[65],"subtle":[67],"differences":[68],"among":[69],"paired":[70,90],"results,":[72],"while":[73],"efficiently":[74],"discovering":[75],"optimal":[76,147],"trajectories.":[78],"To":[79,128],"enable":[80],"sharp":[81],"vision,":[82],"we":[83,112,132],"construct":[84],"VSR-Compare,":[85],"the":[86],"first":[87],"large-scale":[88],"enhancement":[91,102],"dataset":[92],"20K":[94],"comparison":[95],"pairs":[96],"covering":[97],"7":[98],"degradation":[99,121],"types,":[100],"11":[101],"operators,":[103],"diverse":[105],"content":[106],"domains.":[107],"Based":[108],"on":[109,185],"this":[110],"dataset,":[111],"train":[113],"multiple":[115],"operator":[116,136],"judge":[117],"model":[118,123],"guide":[125],"decisions.":[127],"achieve":[129],"fast":[130],"thought,":[131],"introduce":[133],"hierarchical":[135],"scheduling":[137],"strategy":[138],"that":[139,179],"adapts":[140],"difficulty:":[143],"for":[144,162],"easy":[145],"cases,":[146,164],"trajectories":[149],"are":[150],"retrieved":[151],"one-step":[154],"manner":[155],"from":[156],"retrieval-augmented":[158],"generation":[159],"(RAG)":[160],"library;":[161],"harder":[163],"step-by-step":[166],"greedy":[167],"performed":[170],"balance":[172],"efficiency":[173],"accuracy.":[175],"Extensive":[176],"experiments":[177],"demonstrate":[178],"consistently":[181],"outperforms":[182],"methods":[184],"complex":[186],"degraded":[187],"videos.":[188]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-26T00:00:00"}
