{"id":"https://openalex.org/W3093431261","doi":"https://doi.org/10.1145/3394171.3413845","title":"Blind Natural Video Quality Prediction via Statistical Temporal Features and Deep Spatial Features","display_name":"Blind Natural Video Quality Prediction via Statistical Temporal Features and Deep Spatial Features","publication_year":2020,"publication_date":"2020-10-12","ids":{"openalex":"https://openalex.org/W3093431261","doi":"https://doi.org/10.1145/3394171.3413845","mag":"3093431261"},"language":"en","primary_location":{"id":"doi:10.1145/3394171.3413845","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3413845","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"conference-paper","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/A5103007977","display_name":"Jari Korhonen","orcid":"https://orcid.org/0000-0003-4354-5310"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jari Korhonen","raw_affiliation_strings":["Shenzhen University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064949050","display_name":"Yicheng Su","orcid":null},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yicheng Su","raw_affiliation_strings":["Shenzhen University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052816488","display_name":"Junyong You","orcid":"https://orcid.org/0000-0002-4288-5244"},"institutions":[{"id":"https://openalex.org/I4210107808","display_name":"NORCE Research AS","ror":"https://ror.org/02gagpf75","country_code":"NO","type":"facility","lineage":["https://openalex.org/I4210107808"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Junyong You","raw_affiliation_strings":["Norwegian Research Centre, Bergen, Norway"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Norwegian Research Centre, Bergen, Norway","institution_ids":["https://openalex.org/I4210107808"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":85,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3311","last_page":"3319"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":1.0,"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":1.0,"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":0.9902999997138977,"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":0.9873999953269958,"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/computer-science","display_name":"Computer science","score":0.844536542892456},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7127578854560852},{"id":"https://openalex.org/keywords/video-quality","display_name":"Video quality","score":0.6984547972679138},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6963944435119629},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.6122940182685852},{"id":"https://openalex.org/keywords/subjective-video-quality","display_name":"Subjective video quality","score":0.5465906858444214},{"id":"https://openalex.org/keywords/natural","display_name":"Natural (archaeology)","score":0.4652498662471771},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45097607374191284},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.42528587579727173},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4204399585723877},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41790422797203064},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3990210294723511},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.3636038601398468},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33693182468414307},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2202804982662201}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.844536542892456},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7127578854560852},{"id":"https://openalex.org/C103910844","wikidata":"https://www.wikidata.org/wiki/Q2631256","display_name":"Video quality","level":3,"score":0.6984547972679138},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6963944435119629},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.6122940182685852},{"id":"https://openalex.org/C114227958","wikidata":"https://www.wikidata.org/wiki/Q7631422","display_name":"Subjective video quality","level":4,"score":0.5465906858444214},{"id":"https://openalex.org/C2776608160","wikidata":"https://www.wikidata.org/wiki/Q4785462","display_name":"Natural (archaeology)","level":2,"score":0.4652498662471771},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45097607374191284},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.42528587579727173},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4204399585723877},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41790422797203064},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3990210294723511},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.3636038601398468},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33693182468414307},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2202804982662201},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.0},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3394171.3413845","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3413845","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1589326101","https://openalex.org/W1982471090","https://openalex.org/W2038911825","https://openalex.org/W2046863527","https://openalex.org/W2048042940","https://openalex.org/W2059823394","https://openalex.org/W2063658831","https://openalex.org/W2102166818","https://openalex.org/W2108598243","https://openalex.org/W2148848374","https://openalex.org/W2161304138","https://openalex.org/W2194363988","https://openalex.org/W2194775991","https://openalex.org/W2286686646","https://openalex.org/W2368744241","https://openalex.org/W2411063280","https://openalex.org/W2603172850","https://openalex.org/W2611434713","https://openalex.org/W2617811665","https://openalex.org/W2752223497","https://openalex.org/W2791258091","https://openalex.org/W2890744673","https://openalex.org/W2891843192","https://openalex.org/W2895868297","https://openalex.org/W2896261175","https://openalex.org/W2939768411","https://openalex.org/W2939995367","https://openalex.org/W2950154603","https://openalex.org/W2963918210","https://openalex.org/W2965644659","https://openalex.org/W2970478035","https://openalex.org/W2996244170","https://openalex.org/W3002992380","https://openalex.org/W3022136701","https://openalex.org/W3091249416","https://openalex.org/W3099047215","https://openalex.org/W3100404621","https://openalex.org/W3102733987","https://openalex.org/W3103745061","https://openalex.org/W3140428646","https://openalex.org/W3152581407"],"related_works":["https://openalex.org/W4388138958","https://openalex.org/W1996919562","https://openalex.org/W2046455617","https://openalex.org/W4390244677","https://openalex.org/W3183901164","https://openalex.org/W3176438653","https://openalex.org/W3135818718","https://openalex.org/W4290188444","https://openalex.org/W2809031010","https://openalex.org/W3167935049"],"abstract_inverted_index":{"Due":[0],"to":[1],"the":[2,34,74,85,92],"wide":[3],"range":[4],"of":[5,20,102],"different":[6],"natural":[7,21,68],"temporal":[8,37],"and":[9,46],"spatial":[10,47],"distortions":[11],"appearing":[12],"in":[13,40,100],"user":[14],"generated":[15],"video":[16,22,43,69,80,88],"content,":[17],"blind":[18],"assessment":[19,58],"quality":[23,44,57,70,81,89],"is":[24,97],"a":[25,41],"challenging":[26],"research":[27],"problem.":[28],"In":[29],"this":[30],"study,":[31],"we":[32],"combine":[33],"hand-crafted":[35],"statistical":[36],"features":[38,48],"used":[39],"state-of-the-art":[42],"model":[45,76,96],"obtained":[49],"from":[50],"convolutional":[51],"neural":[52],"network":[53],"trained":[54],"for":[55],"image":[56],"via":[59],"transfer":[60],"learning.":[61],"Experimental":[62],"results":[63],"on":[64],"two":[65],"recently":[66],"published":[67],"databases":[71],"show":[72],"that":[73],"proposed":[75,95],"can":[77],"predict":[78],"subjective":[79],"more":[82],"accurately":[83],"than":[84],"publicly":[86],"available":[87],"models":[90],"representing":[91],"state-of-the-art.":[93],"The":[94],"also":[98],"competitive":[99],"terms":[101],"computational":[103],"complexity.":[104]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":21},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":16},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}