{"id":"https://openalex.org/W4386694205","doi":"https://doi.org/10.48550/arxiv.2309.04891","title":"How to Evaluate Semantic Communications for Images with ViTScore Metric?","display_name":"How to Evaluate Semantic Communications for Images with ViTScore Metric?","publication_year":2023,"publication_date":"2023-09-09","ids":{"openalex":"https://openalex.org/W4386694205","doi":"https://doi.org/10.48550/arxiv.2309.04891"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2309.04891","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2309.04891","pdf_url":"https://arxiv.org/pdf/2309.04891","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2309.04891","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102846092","display_name":"Tingting Zhu","orcid":"https://orcid.org/0000-0003-1210-079X"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhu, Tingting","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025424500","display_name":"Bo Peng","orcid":"https://orcid.org/0000-0001-8225-2284"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng, Bo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067599426","display_name":"Jifan Liang","orcid":"https://orcid.org/0000-0001-6022-379X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Jifan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104168433","display_name":"Tingchen Han","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Tingchen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027600524","display_name":"Hai Wan","orcid":"https://orcid.org/0000-0001-5357-9130"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wan, Hai","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113184609","display_name":"Jingqiao Fu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fu, Jingqiao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100365533","display_name":"Junjie Chen","orcid":"https://orcid.org/0000-0001-7979-4357"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Junjie","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5102846092"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":2,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.9835000038146973,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9790999889373779,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.7154884338378906},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.6820244789123535},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6663221120834351},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.6434386968612671},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5180442333221436},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.517577052116394},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4331078827381134},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3998272120952606},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.38831740617752075},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37944620847702026}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7154884338378906},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.6820244789123535},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6663221120834351},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.6434386968612671},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5180442333221436},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.517577052116394},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4331078827381134},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3998272120952606},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.38831740617752075},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37944620847702026},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2309.04891","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2309.04891","pdf_url":"https://arxiv.org/pdf/2309.04891","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},{"id":"doi:10.48550/arxiv.2309.04891","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2309.04891","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":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2309.04891","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2309.04891","pdf_url":"https://arxiv.org/pdf/2309.04891","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1515965089","display_name":null,"funder_award_id":"62276284","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2260909462","display_name":null,"funder_award_id":"2022A1515011355","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"},{"id":"https://openalex.org/G3569266497","display_name":null,"funder_award_id":"20220101","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4488680036","display_name":null,"funder_award_id":"2022A15","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8320811317","display_name":null,"funder_award_id":"2021YFA1000500","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386694205.pdf","grobid_xml":"https://content.openalex.org/works/W4386694205.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2591697403","https://openalex.org/W2953716828","https://openalex.org/W2944728705","https://openalex.org/W3011538607","https://openalex.org/W2904022177","https://openalex.org/W2114797768","https://openalex.org/W2380654781","https://openalex.org/W2176214140","https://openalex.org/W2516873349","https://openalex.org/W1990601549"],"abstract_inverted_index":{"Semantic":[0],"communications":[1],"(SC)":[2],"have":[3],"been":[4],"expected":[5],"to":[6,12,26,44,54],"be":[7],"a":[8,109],"new":[9],"paradigm":[10],"shifting":[11],"catalyze":[13],"the":[14,34,46,56,64,68,73,76,92,147,214,222,229],"next":[15],"generation":[16],"communication,":[17],"whose":[18],"main":[19],"concerns":[20],"shift":[21],"from":[22],"accurate":[23],"bit":[24],"transmission":[25],"effective":[27,251],"semantic":[28,48,115,189,197,201,215,231,234],"information":[29],"exchange":[30],"in":[31,50,87,104,181,187,195,212,227,256],"communications.":[32],"However,":[33],"previous":[35],"and":[36,75,134,140,160,192,210],"widely-used":[37],"metrics":[38,53,82,157,226],"for":[39,96,112,142],"images":[40,60],"are":[41],"not":[42],"applicable":[43],"evaluate":[45,146],"image":[47,114,143,174,183,188,196,230,238],"similarity":[49,57,216],"SC.":[51,97],"Classical":[52],"measure":[55],"between":[58],"two":[59],"usually":[61],"rely":[62],"on":[63,84],"pixel":[65],"level":[66],"or":[67],"structural":[69],"level,":[70],"such":[71,90,236],"as":[72,91,237],"PSNR":[74],"MS-SSIM.":[77],"Straightforwardly":[78],"using":[79],"some":[80],"tailored":[81],"based":[83],"deep-learning":[85],"methods":[86],"CV":[88,177],"community,":[89,106],"LPIPS,":[93],"is":[94,208,249],"infeasible":[95],"To":[98,145],"tackle":[99],"this,":[100],"inspired":[101],"by":[102,233],"BERTScore":[103,170],"NLP":[105],"we":[107,151],"propose":[108],"novel":[110],"metric":[111,253],"evaluating":[113,213,228],"similarity,":[116],"named":[117],"Vision":[118],"Transformer":[119],"Score":[120],"(ViTScore).":[121],"We":[122],"prove":[123],"theoretically":[124],"that":[125,206,247],"ViTScore":[126,138,153,207,220,248],"has":[127],"3":[128,155,224],"important":[129],"properties,":[130],"including":[131],"symmetry,":[132],"boundedness,":[133],"normalization,":[135],"which":[136],"make":[137],"convenient":[139],"intuitive":[141],"measurement.":[144],"performance":[148,252],"of":[149,165,173,217],"ViTScore,":[150],"compare":[152],"with":[154,169,200,240],"typical":[156,225],"(PSNR,":[158],"MS-SSIM,":[159],"LPIPS)":[161],"through":[162,171],"4":[163],"classes":[164],"experiments:":[166],"(i)":[167],"correlation":[168],"evaluation":[172,180,186,194],"caption":[175],"downstream":[176],"task,":[178],"(ii)":[179],"classical":[182],"communications,":[184],"(iii)":[185],"communication":[190,198],"systems,":[191],"(iv)":[193],"systems":[199],"attack.":[202],"Experimental":[203],"results":[204],"demonstrate":[205],"robust":[209],"efficient":[211],"images.":[218],"Particularly,":[219],"outperforms":[221],"other":[223],"changes":[232],"attack,":[235],"inverse":[239],"Generative":[241],"Adversarial":[242],"Networks":[243],"(GANs).":[244],"This":[245],"indicates":[246],"an":[250],"when":[254],"deployed":[255],"SC":[257],"scenarios.":[258]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}