{"id":"https://openalex.org/W4390601433","doi":"https://doi.org/10.48550/arxiv.2401.01651","title":"AIGCBench: Comprehensive Evaluation of Image-to-Video Content Generated by AI","display_name":"AIGCBench: Comprehensive Evaluation of Image-to-Video Content Generated by AI","publication_year":2024,"publication_date":"2024-01-03","ids":{"openalex":"https://openalex.org/W4390601433","doi":"https://doi.org/10.48550/arxiv.2401.01651"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2401.01651","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2401.01651","pdf_url":"https://arxiv.org/pdf/2401.01651","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":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2401.01651","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5083043281","display_name":"Fanda Fan","orcid":"https://orcid.org/0000-0002-5214-0959"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Fan, Fanda","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033347503","display_name":"Chunjie Luo","orcid":"https://orcid.org/0000-0002-6977-929X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Chunjie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075110031","display_name":"Wanling Gao","orcid":"https://orcid.org/0000-0002-3911-9389"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Wanling","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5085963553","display_name":"Jianfeng Zhan","orcid":"https://orcid.org/0000-0002-3728-6837"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhan, Jianfeng","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5083043281"],"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9890000224113464,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9890000224113464,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9736999869346619,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9474999904632568,"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":0.8138169050216675},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7990646362304688},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.6663693189620972},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6593918800354004},{"id":"https://openalex.org/keywords/strengths-and-weaknesses","display_name":"Strengths and weaknesses","score":0.6077104806900024},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5532217025756836},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5127097368240356},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.511041522026062},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.457394003868103},{"id":"https://openalex.org/keywords/video-quality","display_name":"Video quality","score":0.4357631802558899},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4314817190170288},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.41440466046333313},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3950943052768707},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.3830098807811737},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3828672170639038},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32905033230781555},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.1535346806049347},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.08783307671546936}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8138169050216675},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7990646362304688},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.6663693189620972},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6593918800354004},{"id":"https://openalex.org/C63882131","wikidata":"https://www.wikidata.org/wiki/Q17122954","display_name":"Strengths and weaknesses","level":2,"score":0.6077104806900024},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5532217025756836},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5127097368240356},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.511041522026062},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.457394003868103},{"id":"https://openalex.org/C103910844","wikidata":"https://www.wikidata.org/wiki/Q2631256","display_name":"Video quality","level":3,"score":0.4357631802558899},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4314817190170288},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.41440466046333313},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3950943052768707},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.3830098807811737},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3828672170639038},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32905033230781555},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.1535346806049347},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.08783307671546936},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2401.01651","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2401.01651","pdf_url":"https://arxiv.org/pdf/2401.01651","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":"text"},{"id":"doi:10.48550/arxiv.2401.01651","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2401.01651","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:2401.01651","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2401.01651","pdf_url":"https://arxiv.org/pdf/2401.01651","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":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4390601433.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4295769391","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W2972220648","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W2144839145","https://openalex.org/W2057378461"],"abstract_inverted_index":{"The":[0,146,166],"burgeoning":[1],"field":[2],"of":[3,32,48,56,162,206],"Artificial":[4],"Intelligence":[5],"Generated":[6],"Content":[7],"(AIGC)":[8],"is":[9],"witnessing":[10],"rapid":[11],"advancements,":[12],"particularly":[13],"in":[14,179],"video":[15,33,106,131,207],"generation.":[16,43],"This":[17],"paper":[18],"introduces":[19],"AIGCBench,":[20],"a":[21,30,37,54,61,77,101,142,185],"pioneering":[22],"comprehensive":[23,143],"and":[24,63,81,130,139,160,177,200,215],"scalable":[25],"benchmark":[26,110],"designed":[27],"to":[28,83,92,117,173],"evaluate":[29],"variety":[31],"generation":[34,107,208],"tasks,":[35,108],"with":[36,152],"primary":[38],"focus":[39],"on":[40,218],"Image-to-Video":[41],"(I2V)":[42],"AIGCBench":[44,183],"tackles":[45],"the":[46,158,180,193,213,219],"limitations":[47],"existing":[49],"benchmarks,":[50],"which":[51,88],"suffer":[52],"from":[53,168],"lack":[55],"diverse":[57],"datasets,":[58],"by":[59],"including":[60],"varied":[62],"open-domain":[64],"image-text":[65],"dataset":[66,214],"that":[67],"evaluates":[68],"different":[69],"state-of-the-art":[70],"algorithms":[71],"under":[72],"equivalent":[73],"conditions.":[74],"We":[75,210],"employ":[76],"novel":[78],"text":[79,86],"combiner":[80],"GPT-4":[82],"create":[84],"rich":[85],"prompts,":[87],"are":[89,123,135],"then":[90],"used":[91],"generate":[93],"images":[94],"via":[95],"advanced":[96],"Text-to-Image":[97],"models.":[98],"To":[99],"establish":[100],"unified":[102],"evaluation":[103,144,147,216],"framework":[104,202],"for":[105,192,203],"our":[109,169],"includes":[111],"11":[112],"metrics":[113,134],"spanning":[114],"four":[115],"dimensions":[116,122],"assess":[118],"algorithm":[119],"performance.":[120],"These":[121,133],"control-video":[124],"alignment,":[125],"motion":[126],"effects,":[127],"temporal":[128],"consistency,":[129],"quality.":[132],"both":[136],"reference":[137],"video-dependent":[138],"video-free,":[140],"ensuring":[141],"strategy.":[145],"standard":[148],"proposed":[149],"correlates":[150],"well":[151],"human":[153],"judgment,":[154],"providing":[155],"insights":[156],"into":[157],"strengths":[159],"weaknesses":[161],"current":[163],"I2V":[164,181],"algorithms.":[165],"findings":[167],"extensive":[170],"experiments":[171],"aim":[172],"stimulate":[174],"further":[175],"research":[176],"development":[178],"field.":[182],"represents":[184],"significant":[186],"step":[187],"toward":[188],"creating":[189],"standardized":[190],"benchmarks":[191],"broader":[194],"AIGC":[195],"landscape,":[196],"proposing":[197],"an":[198],"adaptable":[199],"equitable":[201],"future":[204],"assessments":[205],"tasks.":[209],"have":[211],"open-sourced":[212],"code":[217],"project":[220],"website:":[221],"https://www.benchcouncil.org/AIGCBench.":[222]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-25T23:56:10.502304","created_date":"2024-01-05T00:00:00"}