{"id":"https://openalex.org/W4416507379","doi":"https://doi.org/10.1109/iccv51701.2025.01365","title":"VSRM: A Robust Mamba-Based Framework for Video Super-Resolution","display_name":"VSRM: A Robust Mamba-Based Framework for Video Super-Resolution","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4416507379","doi":"https://doi.org/10.1109/iccv51701.2025.01365"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51701.2025.01365","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.01365","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2506.22762","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120704304","display_name":"Dinh Phu Tran","orcid":null},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dinh Phu Tran","raw_affiliation_strings":["School of Computing,KAIST,Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing,KAIST,Republic of Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120559611","display_name":"Dao Duy Hung","orcid":null},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dao Duy Hung","raw_affiliation_strings":["School of Computing,KAIST,Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing,KAIST,Republic of Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5120371761","display_name":"Daeyoung Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Daeyoung Kim","raw_affiliation_strings":["School of Computing,KAIST,Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing,KAIST,Republic of Korea","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I157485424"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.40798922,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"14711","last_page":"14721"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.891700029373169,"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":0.891700029373169,"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":0.058400001376867294,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.010200000368058681,"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/feature","display_name":"Feature (linguistics)","score":0.49880000948905945},{"id":"https://openalex.org/keywords/receptive-field","display_name":"Receptive field","score":0.45399999618530273},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43560001254081726},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.4262000024318695},{"id":"https://openalex.org/keywords/compensation","display_name":"Compensation (psychology)","score":0.3903999924659729},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.37709999084472656},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.37459999322891235},{"id":"https://openalex.org/keywords/image-manipulation","display_name":"Image manipulation","score":0.3434999883174896}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7336999773979187},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6320000290870667},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6205999851226807},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49880000948905945},{"id":"https://openalex.org/C19071747","wikidata":"https://www.wikidata.org/wiki/Q1755207","display_name":"Receptive field","level":2,"score":0.45399999618530273},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43560001254081726},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.4262000024318695},{"id":"https://openalex.org/C2780023022","wikidata":"https://www.wikidata.org/wiki/Q1338171","display_name":"Compensation (psychology)","level":2,"score":0.3903999924659729},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.37709999084472656},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.37459999322891235},{"id":"https://openalex.org/C2987933465","wikidata":"https://www.wikidata.org/wiki/Q141130","display_name":"Image manipulation","level":3,"score":0.3434999883174896},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.3352000117301941},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30379998683929443},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.30239999294281006},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.2720000147819519},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2655999958515167},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2639000117778778},{"id":"https://openalex.org/C160086991","wikidata":"https://www.wikidata.org/wiki/Q5939193","display_name":"Human visual system model","level":3,"score":0.25360000133514404}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv51701.2025.01365","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.01365","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2506.22762","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.22762","pdf_url":"https://arxiv.org/pdf/2506.22762","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2506.22762","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2506.22762","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":"pmh:oai:arXiv.org:2506.22762","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.22762","pdf_url":"https://arxiv.org/pdf/2506.22762","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Video":[0],"super-resolution":[1],"remains":[2],"a":[3,63,106,136,165],"major":[4],"challenge":[5],"in":[6,40],"low-level":[7],"vision":[8],"tasks.":[9],"To":[10,92],"date,":[11],"CNN-":[12],"and":[13,53,78,87,117,131,148],"Transformer-based":[14],"methods":[15],"have":[16],"delivered":[17],"impressive":[18],"results.":[19],"However,":[20],"CNNs":[21],"are":[22],"limited":[23],"by":[24,134],"local":[25],"receptive":[26,55,89],"fields,":[27],"while":[28],"Transformers":[29],"struggle":[30],"with":[31],"quadratic":[32],"complexity,":[33,52],"posing":[34],"challenges":[35],"for":[36,47,168],"processing":[37],"long":[38],"sequences":[39],"VSR.":[41],"Recently,":[42],"Mamba":[43,77,80],"has":[44],"drawn":[45],"attention":[46],"its":[48],"long-sequence":[49],"modeling,":[50],"linear":[51],"large":[54],"fields.":[56],"In":[57],"this":[58],"work,":[59],"we":[60,97,123],"propose":[61,98],"VSRM,":[62],"novel":[64],"\\textbf{V}ideo":[65],"\\textbf{S}uper-\\textbf{R}esolution":[66],"framework":[67],"that":[68,143],"leverages":[69],"the":[70,112,125],"power":[71],"of":[72],"\\textbf{M}amba.":[73],"VSRM":[74,155],"introduces":[75],"Spatial-to-Temporal":[76],"Temporal-to-Spatial":[79],"blocks":[81],"to":[82,110],"extract":[83],"long-range":[84],"spatio-temporal":[85],"features":[86],"enhance":[88],"fields":[90],"efficiently.":[91],"better":[93,144],"align":[94],"adjacent":[95],"frames,":[96],"Deformable":[99],"Cross-Mamba":[100],"Alignment":[101],"module.":[102],"This":[103],"module":[104],"utilizes":[105],"deformable":[107],"cross-mamba":[108],"mechanism":[109],"make":[111],"compensation":[113],"stage":[114],"more":[115],"dynamic":[116],"flexible,":[118],"preventing":[119],"feature":[120],"distortions.":[121],"Finally,":[122],"minimize":[124],"frequency":[126],"domain":[127],"gaps":[128],"between":[129],"reconstructed":[130],"ground-truth":[132],"frames":[133],"proposing":[135],"simple":[137],"yet":[138],"effective":[139],"Frequency":[140],"Charbonnier-like":[141],"loss":[142],"preserves":[145],"high-frequency":[146],"content":[147],"enhances":[149],"visual":[150],"quality.":[151],"Through":[152],"extensive":[153],"experiments,":[154],"achieves":[156],"state-of-the-art":[157],"results":[158],"on":[159],"diverse":[160],"benchmarks,":[161],"establishing":[162],"itself":[163],"as":[164],"solid":[166],"foundation":[167],"future":[169],"research.":[170]},"counts_by_year":[],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2025-10-10T00:00:00"}
