{"id":"https://openalex.org/W4415540974","doi":"https://doi.org/10.1145/3746027.3754824","title":"MVQA-68K: A Multi-dimensional and Causally-annotated Dataset with Quality Interpretability for Video Assessment","display_name":"MVQA-68K: A Multi-dimensional and Causally-annotated Dataset with Quality Interpretability for Video Assessment","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415540974","doi":"https://doi.org/10.1145/3746027.3754824"},"language":null,"primary_location":{"id":"doi:10.1145/3746027.3754824","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746027.3754824","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3746027.3754824","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037358057","display_name":"Yanyun Pu","orcid":"https://orcid.org/0000-0001-5282-8916"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yanyun Pu","raw_affiliation_strings":["Huawei Technologies Co., Hangzhou, Zhejiang, China"],"raw_orcid":"https://orcid.org/0009-0003-7120-2777","affiliations":[{"raw_affiliation_string":"Huawei Technologies Co., Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089327790","display_name":"Kehan Li","orcid":"https://orcid.org/0000-0002-5318-4806"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kehan Li","raw_affiliation_strings":["Huawei Technologies Co., Hangzhou, Zhejiang, China"],"raw_orcid":"https://orcid.org/0000-0002-5318-4806","affiliations":[{"raw_affiliation_string":"Huawei Technologies Co., Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110608354","display_name":"Zeyi Huang","orcid":"https://orcid.org/0009-0009-5897-2172"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zeyi Huang","raw_affiliation_strings":["Huawei Technologies Co., Hangzhou, Zhejiang, China"],"raw_orcid":"https://orcid.org/0009-0009-5897-2172","affiliations":[{"raw_affiliation_string":"Huawei Technologies Co., Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102841191","display_name":"Zhijie Zhong","orcid":"https://orcid.org/0000-0003-0203-8419"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhijie Zhong","raw_affiliation_strings":["South China University of Technology, GuangZhou, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0003-0203-8419","affiliations":[{"raw_affiliation_string":"South China University of Technology, GuangZhou, Guangdong, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050942308","display_name":"Kaixiang Yang","orcid":"https://orcid.org/0000-0003-2180-2101"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaixiang Yang","raw_affiliation_strings":["South China University of Technology, GuangZhou, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0003-2180-2101","affiliations":[{"raw_affiliation_string":"South China University of Technology, GuangZhou, Guangdong, China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5037358057"],"corresponding_institution_ids":["https://openalex.org/I2250955327"],"apc_list":null,"apc_paid":null,"fwci":1.0943,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.83066905,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"11189","last_page":"11198"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9998000264167786,"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/T11165","display_name":"Image and Video Quality Assessment","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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9972000122070312,"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":0.9962000250816345,"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/interpretability","display_name":"Interpretability","score":0.9764999747276306},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5727999806404114},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5720000267028809},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.5297999978065491},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5297999978065491},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.42320001125335693},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.374099999666214},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.3273000121116638}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9764999747276306},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7971000075340271},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6015999913215637},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5727999806404114},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5720000267028809},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5454999804496765},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5297999978065491},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5297999978065491},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.42320001125335693},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.374099999666214},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3652999997138977},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3352999985218048},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3273000121116638},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3140999972820282},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.2969000041484833},{"id":"https://openalex.org/C3020001037","wikidata":"https://www.wikidata.org/wiki/Q836575","display_name":"Quality assessment","level":3,"score":0.2791999876499176},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.2727999985218048},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2671000063419342},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.2615000009536743}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746027.3754824","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746027.3754824","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3746027.3754824","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746027.3754824","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1972006393","https://openalex.org/W1982471090","https://openalex.org/W2063658831","https://openalex.org/W2194363988","https://openalex.org/W2511458122","https://openalex.org/W2611434713","https://openalex.org/W2617811665","https://openalex.org/W2791258091","https://openalex.org/W2950154603","https://openalex.org/W2963398015","https://openalex.org/W3030701471","https://openalex.org/W3167030277","https://openalex.org/W3174722860","https://openalex.org/W3193919962","https://openalex.org/W4225292576","https://openalex.org/W4304014328","https://openalex.org/W4312560592","https://openalex.org/W4312929873","https://openalex.org/W4322706707","https://openalex.org/W4390874113","https://openalex.org/W4402704606","https://openalex.org/W4403081466","https://openalex.org/W4403601500","https://openalex.org/W4403791714","https://openalex.org/W4404965692","https://openalex.org/W4413145449","https://openalex.org/W4413147296","https://openalex.org/W4413158035"],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1,98,108,142],"rapid":[2],"advancement":[3],"of":[4,100],"video":[5,11],"generation":[6],"models":[7,105],"such":[8],"as":[9],"Sora,":[10],"quality":[12,63],"assessment":[13],"(VQA)":[14],"is":[15],"becoming":[16],"increasingly":[17],"crucial":[18],"for":[19],"selecting":[20],"high-quality":[21],"videos":[22],"from":[23],"large-scale":[24],"datasets":[25],"used":[26],"in":[27],"pre-training.":[28],"Traditional":[29],"VQA":[30,52,109,138],"methods,":[31],"typically":[32],"producing":[33],"single":[34],"numerical":[35],"scores,":[36],"often":[37],"lack":[38],"comprehensiveness":[39],"and":[40,76,88,130,146],"interpretability.":[41],"To":[42],"address":[43],"these":[44],"challenges,":[45],"we":[46],"introduce":[47],"MVQA-68K,":[48],"a":[49],"novel":[50],"multi-dimensional":[51],"dataset":[53,147],"comprising":[54],"over":[55],"68,000":[56],"carefully":[57],"annotated":[58],"videos,":[59],"covering":[60],"seven":[61],"essential":[62],"dimensions:":[64],"overall":[65],"aesthetics,":[66],"camera":[67],"movement,":[68],"dynamic":[69],"degree,":[70],"texture":[71],"detail,":[72],"composition,":[73],"visual":[74],"quality,":[75],"factual":[77],"consistency.":[78],"Each":[79],"annotation":[80],"includes":[81],"detailed":[82],"chain-of-thought":[83],"reasoning":[84,135],"to":[85],"facilitate":[86],"interpretability":[87],"comprehensive":[89],"understanding.":[90],"Extensive":[91],"experiments":[92],"demonstrate":[93],"that":[94],"MVQA-68K":[95],"significantly":[96],"enhances":[97],"performance":[99],"various":[101],"multimodal":[102],"large":[103],"language":[104],"(MLLMs)":[106],"on":[107,116,124],"task,":[110],"achieving":[111],"state-of-the-art":[112],"results":[113],"not":[114],"only":[115],"our":[117],"internal":[118],"test":[119],"set":[120],"(Fig.1)":[121],"but":[122],"also":[123],"public":[125],"benchmarks":[126],"including":[127],"LSVQ-test,":[128],"LSVQ-1080p,":[129],"LIVE-VQC.":[131],"Meantime,":[132],"incorporating":[133],"explicit":[134],"process":[136],"during":[137],"training":[139],"substantially":[140],"boosts":[141],"zero-shot":[143],"generalization.":[144],"Code":[145],"will":[148],"be":[149],"available":[150],"at":[151],"github:":[152],"https://github.com/Controller01-ai/MVQA-68K.":[153]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-25T00:00:00"}
