{"id":"https://openalex.org/W4416552802","doi":"https://doi.org/10.48550/arxiv.2508.01270","title":"SGCap: Decoding Semantic Group for Zero-shot Video Captioning","display_name":"SGCap: Decoding Semantic Group for Zero-shot Video Captioning","publication_year":2025,"publication_date":"2025-08-02","ids":{"openalex":"https://openalex.org/W4416552802","doi":"https://doi.org/10.48550/arxiv.2508.01270"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2508.01270","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2508.01270","pdf_url":"https://arxiv.org/pdf/2508.01270","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2508.01270","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071371334","display_name":"Zeyu Pan","orcid":"https://orcid.org/0009-0004-0284-698X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pan, Zeyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100435467","display_name":"Ping Li","orcid":"https://orcid.org/0000-0001-7715-0179"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Ping","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5101701726","display_name":"Wenxiao Wang","orcid":"https://orcid.org/0000-0001-7328-0267"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Wenxiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9800000190734863,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9800000190734863,"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/T11439","display_name":"Video Analysis and Summarization","score":0.003000000026077032,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.002199999988079071,"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/closed-captioning","display_name":"Closed captioning","score":0.9793999791145325},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.6273000240325928},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5436999797821045},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.5192999839782715},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5070000290870667},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.49880000948905945},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4490000009536743},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.43650001287460327},{"id":"https://openalex.org/keywords/cosine-similarity","display_name":"Cosine similarity","score":0.423799991607666}],"concepts":[{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.9793999791145325},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8180999755859375},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.6273000240325928},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5968000292778015},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5680000185966492},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5436999797821045},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5192999839782715},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5070000290870667},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.49880000948905945},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4490000009536743},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.43650001287460327},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.423799991607666},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.3968999981880188},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.39259999990463257},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3675999939441681},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3456999957561493},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.34549999237060547},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.337799996137619},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.32659998536109924},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3255999982357025},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.3160000145435333},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.3138999938964844},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.3118000030517578},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.2892000079154968},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.28859999775886536},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.2700999975204468},{"id":"https://openalex.org/C2781311116","wikidata":"https://www.wikidata.org/wiki/Q83306","display_name":"Group (periodic table)","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2597000002861023}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2508.01270","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2508.01270","pdf_url":"https://arxiv.org/pdf/2508.01270","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2508.01270","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2508.01270","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:2508.01270","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2508.01270","pdf_url":"https://arxiv.org/pdf/2508.01270","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Zero-shot":[0],"video":[1,47,75,174],"captioning":[2,23,100],"aims":[3],"to":[4,45,87,121,163,173],"generate":[5],"sentences":[6],"for":[7,73,107],"describing":[8],"videos":[9],"without":[10],"training":[11,29],"the":[12,46,81,112,135,142,161],"model":[13,162],"on":[14,104,178],"video-text":[15],"pairs,":[16],"which":[17],"remains":[18],"underexplored.":[19],"Existing":[20],"zero-shot":[21,74,99,188],"image":[22],"methods":[24,101],"typically":[25],"adopt":[26],"a":[27,32,67,116],"text-only":[28],"paradigm,":[30],"where":[31],"language":[33],"decoder":[34],"reconstructs":[35],"single-sentence":[36],"embeddings":[37],"obtained":[38],"from":[39],"CLIP.":[40],"However,":[41],"directly":[42],"extending":[43],"them":[44],"domain":[48],"is":[49,200],"suboptimal,":[50],"as":[51],"applying":[52],"average":[53],"pooling":[54],"over":[55],"all":[56],"frames":[57],"neglects":[58],"temporal":[59,95,157],"dynamics.":[60],"To":[61,126],"address":[62],"this":[63],"challenge,":[64],"we":[65,129],"propose":[66],"Semantic":[68,82],"Group":[69,83],"Captioning":[70],"(SGCap)":[71],"method":[72],"captioning.":[76,175],"In":[77],"particular,":[78],"it":[79],"develops":[80],"Decoding":[84],"(SGD)":[85],"strategy":[86],"employ":[88],"multi-frame":[89],"information":[90],"while":[91],"explicitly":[92],"modeling":[93],"inter-frame":[94],"relationships.":[96],"Furthermore,":[97],"existing":[98],"that":[102,155,182],"rely":[103],"cosine":[105],"similarity":[106],"sentence":[108,153],"retrieval":[109],"and":[110,141,159,190],"reconstruct":[111],"description":[113],"supervised":[114,197],"by":[115],"single":[117],"frame-level":[118],"caption,":[119],"fail":[120],"provide":[122],"sufficient":[123],"video-level":[124],"supervision.":[125],"alleviate":[127],"this,":[128],"introduce":[130],"two":[131,149],"key":[132],"components,":[133],"including":[134],"Key":[136],"Sentences":[137],"Selection":[138],"(KSS)":[139],"module":[140],"Probability":[143],"Sampling":[144],"Supervision":[145],"(PSS)":[146],"module.":[147],"The":[148],"modules":[150],"construct":[151],"semantically-diverse":[152],"groups":[154],"models":[156],"dynamics":[158],"guide":[160],"capture":[164],"inter-sentence":[165],"causal":[166],"relationships,":[167],"thereby":[168],"enhancing":[169],"its":[170],"generalization":[171],"ability":[172],"Experimental":[176],"results":[177],"several":[179],"benchmarks":[180],"demonstrate":[181],"SGCap":[183],"significantly":[184],"outperforms":[185],"previous":[186],"state-of-the-art":[187],"alternatives":[189],"even":[191],"achieves":[192],"performance":[193],"competitive":[194],"with":[195],"fully":[196],"ones.":[198],"Code":[199],"available":[201],"at":[202],"https://github.com/mlvccn/SGCap_Video.":[203]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}