{"id":"https://openalex.org/W4316659991","doi":"https://doi.org/10.1109/vcip56404.2022.10008875","title":"No-reference Stereoscopic Image Quality Assessment Based on Parallel Multi-scale Perception","display_name":"No-reference Stereoscopic Image Quality Assessment Based on Parallel Multi-scale Perception","publication_year":2022,"publication_date":"2022-12-13","ids":{"openalex":"https://openalex.org/W4316659991","doi":"https://doi.org/10.1109/vcip56404.2022.10008875"},"language":"en","primary_location":{"id":"doi:10.1109/vcip56404.2022.10008875","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/vcip56404.2022.10008875","pdf_url":null,"source":{"id":"https://openalex.org/S4363608486","display_name":"2022 IEEE International Conference on Visual Communications and Image Processing (VCIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"},"type":"article","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/A5100352961","display_name":"Ziyi Zhang","orcid":"https://orcid.org/0009-0009-5841-2247"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ziyi Zhang","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University,Tianjin,China","School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University,Tianjin,China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036035213","display_name":"Sumei Li","orcid":"https://orcid.org/0000-0002-4793-3161"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sumei Li","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University,Tianjin,China","School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University,Tianjin,China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100352961"],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":null,"apc_paid":null,"fwci":0.0599,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.3457864,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9994000196456909,"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":0.9994000196456909,"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":0.9952999949455261,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/computer-science","display_name":"Computer science","score":0.8286451697349548},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7197954058647156},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6674807071685791},{"id":"https://openalex.org/keywords/stereoscopy","display_name":"Stereoscopy","score":0.656151294708252},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.630728006362915},{"id":"https://openalex.org/keywords/human-visual-system-model","display_name":"Human visual system model","score":0.6147615313529968},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6055377721786499},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.598125159740448},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.586513340473175},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.585963249206543},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5283181071281433},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4497697651386261},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44264543056488037},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.41905418038368225},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3677610754966736},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.33027899265289307},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07749819755554199}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8286451697349548},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7197954058647156},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6674807071685791},{"id":"https://openalex.org/C126057942","wikidata":"https://www.wikidata.org/wiki/Q35158","display_name":"Stereoscopy","level":2,"score":0.656151294708252},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.630728006362915},{"id":"https://openalex.org/C160086991","wikidata":"https://www.wikidata.org/wiki/Q5939193","display_name":"Human visual system model","level":3,"score":0.6147615313529968},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6055377721786499},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.598125159740448},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.586513340473175},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.585963249206543},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5283181071281433},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4497697651386261},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44264543056488037},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.41905418038368225},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3677610754966736},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.33027899265289307},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07749819755554199},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vcip56404.2022.10008875","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/vcip56404.2022.10008875","pdf_url":null,"source":{"id":"https://openalex.org/S4363608486","display_name":"2022 IEEE International Conference on Visual Communications and Image Processing (VCIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1593057674","https://openalex.org/W2144662207","https://openalex.org/W2258211000","https://openalex.org/W2560023338","https://openalex.org/W2810874584","https://openalex.org/W2884585870","https://openalex.org/W2902232295","https://openalex.org/W2904946794","https://openalex.org/W2905908087","https://openalex.org/W2920014186","https://openalex.org/W2964701660","https://openalex.org/W3000373634","https://openalex.org/W3022710784","https://openalex.org/W3035366025","https://openalex.org/W3093779980","https://openalex.org/W3187196322","https://openalex.org/W3195684134","https://openalex.org/W4220758784"],"related_works":["https://openalex.org/W1536158975","https://openalex.org/W2393788985","https://openalex.org/W2157670837","https://openalex.org/W2374120702","https://openalex.org/W2631594184","https://openalex.org/W2072849536","https://openalex.org/W1983607852","https://openalex.org/W2359818963","https://openalex.org/W2292083403","https://openalex.org/W2364766777"],"abstract_inverted_index":{"With":[0],"the":[1,50,58,92,97,116,131],"rapid":[2],"development":[3],"of":[4,52,120],"3D":[5],"technologies,":[6],"effective":[7],"no-reference":[8],"stereoscopic":[9],"image":[10],"quality":[11],"assessment":[12],"(NR-SIQA)":[13],"methods":[14],"are":[15],"in":[16],"great":[17],"demand.":[18],"In":[19,46,99],"this":[20],"paper,":[21],"we":[22,101],"propose":[23],"a":[24],"parallel":[25,61],"multi-scale":[26,55,62,93],"feature":[27,38,63],"extraction":[28,64],"convolution":[29],"neural":[30],"network":[31],"(CNN)":[32],"model":[33],"combined":[34],"with":[35,41,80],"novel":[36],"binocular":[37,107,111],"interaction":[39],"consistent":[40],"human":[42],"visual":[43,88],"system":[44],"(HVS).":[45],"order":[47],"to":[48,86,114,130],"simulate":[49,115],"characteristics":[51,119],"HVS":[53],"sensing":[54],"information":[56,70],"at":[57],"same":[59],"time,":[60],"module":[65,78],"(PMSFM)":[66],"followed":[67],"by":[68,96],"compensation":[69],"is":[71,84,128],"proposed.":[72],"And":[73],"modified":[74],"convolutional":[75],"block":[76],"attention":[77,89],"(MCBAM)":[79],"less":[81],"computational":[82],"complexity":[83],"designed":[85],"generate":[87],"maps":[90,109,113],"for":[91,105],"features":[94],"extracted":[95],"PMSFM.":[98],"addition,":[100],"employ":[102],"cross-stacked":[103],"strategy":[104],"multi-level":[106],"fusion":[108],"and":[110,134],"disparity":[112],"hierarchical":[117],"perception":[118],"HVS.":[121],"Experimental":[122],"results":[123],"show":[124],"that":[125],"our":[126],"method":[127],"superior":[129],"state-of-the-art":[132],"metrics":[133],"achieves":[135],"an":[136],"excellent":[137],"performance.":[138]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-02-01T03:34:12.195049","created_date":"2025-10-10T00:00:00"}
