{"id":"https://openalex.org/W4313484218","doi":"https://doi.org/10.48550/arxiv.2301.00514","title":"Rethinking the Video Sampling and Reasoning Strategies for Temporal Sentence Grounding","display_name":"Rethinking the Video Sampling and Reasoning Strategies for Temporal Sentence Grounding","publication_year":2023,"publication_date":"2023-01-02","ids":{"openalex":"https://openalex.org/W4313484218","doi":"https://doi.org/10.48550/arxiv.2301.00514"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2301.00514","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2301.00514","pdf_url":"https://arxiv.org/pdf/2301.00514","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/2301.00514","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101901855","display_name":"Jiahao Zhu","orcid":"https://orcid.org/0000-0001-7925-3614"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhu, Jiahao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078220957","display_name":"Daizong Liu","orcid":"https://orcid.org/0000-0001-8179-4508"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Daizong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100693197","display_name":"Pan Zhou","orcid":"https://orcid.org/0000-0002-8629-4622"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Pan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013497247","display_name":"Xing Di","orcid":"https://orcid.org/0000-0001-7232-2330"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Di, Xing","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100622632","display_name":"Cheng Yu","orcid":"https://orcid.org/0000-0003-4816-1586"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, Yu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083873109","display_name":"Yang Song","orcid":"https://orcid.org/0000-0002-1714-5527"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Song","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079727396","display_name":"Wenzheng Xu","orcid":"https://orcid.org/0000-0002-8396-6825"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Wenzheng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063489530","display_name":"Zichuan Xu","orcid":"https://orcid.org/0000-0001-5438-1468"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Zichuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102201025","display_name":"Yao Wan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wan, Yao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015105117","display_name":"Lichao Sun","orcid":"https://orcid.org/0000-0003-1539-7939"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Lichao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5056981085","display_name":"Zeyu Xiong","orcid":"https://orcid.org/0000-0002-8330-5912"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiong, Zeyu","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":11,"corresponding_author_ids":["https://openalex.org/A5101901855"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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":0.9998000264167786,"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":0.9998000264167786,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9950000047683716,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9632999897003174,"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":0.7624005675315857},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6465297341346741},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5921471118927002},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5785444378852844},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.557921290397644},{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.5278646349906921},{"id":"https://openalex.org/keywords/timestamp","display_name":"Timestamp","score":0.4965055584907532},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4594901204109192},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.45350128412246704},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.42804545164108276},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.42544135451316833},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.41384539008140564},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3235410153865814},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.25098326802253723},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1477736234664917},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09419754147529602}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7624005675315857},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6465297341346741},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5921471118927002},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5785444378852844},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.557921290397644},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.5278646349906921},{"id":"https://openalex.org/C113954288","wikidata":"https://www.wikidata.org/wiki/Q186885","display_name":"Timestamp","level":2,"score":0.4965055584907532},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4594901204109192},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.45350128412246704},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.42804545164108276},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.42544135451316833},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.41384539008140564},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3235410153865814},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.25098326802253723},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1477736234664917},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09419754147529602},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2301.00514","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2301.00514","pdf_url":"https://arxiv.org/pdf/2301.00514","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.2301.00514","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2301.00514","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:2301.00514","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2301.00514","pdf_url":"https://arxiv.org/pdf/2301.00514","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/G1163254860","display_name":null,"funder_award_id":"2172038","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1671829941","display_name":null,"funder_award_id":"62172068","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G235913322","display_name":null,"funder_award_id":"62272328","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5443068723","display_name":null,"funder_award_id":"62172038","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5817064308","display_name":null,"funder_award_id":"61972448","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6058138561","display_name":null,"funder_award_id":", No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8863666567","display_name":null,"funder_award_id":"and No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2060561905","https://openalex.org/W2062399876","https://openalex.org/W1417711376","https://openalex.org/W2607795551","https://openalex.org/W1986883493","https://openalex.org/W3155117723","https://openalex.org/W1991429770","https://openalex.org/W1983892167","https://openalex.org/W2281134365","https://openalex.org/W4310746709"],"abstract_inverted_index":{"Temporal":[0],"sentence":[1,20,46],"grounding":[2],"(TSG)":[3],"aims":[4],"to":[5,31,68,105,143,148,161,184,191],"identify":[6],"the":[7,89,106,113,152,163,186,192,203],"temporal":[8],"boundary":[9,101],"of":[10,36,116,205],"a":[11,19,27,33,127,139,156],"specific":[12,70],"segment":[13,65],"from":[14],"an":[15],"untrimmed":[16],"video":[17,37,79],"by":[18],"query.":[21],"All":[22],"existing":[23],"works":[24],"first":[25],"utilize":[26],"sparse":[28,194],"sampling":[29,141],"strategy":[30,158],"extract":[32],"fixed":[34],"number":[35],"frames":[38,71,86,92,102,147,167,195],"and":[39,75,87,131,150,168],"then":[40],"conduct":[41],"multi-modal":[42],"interactions":[43],"with":[44],"query":[45],"for":[47,135,174,196],"reasoning.":[48,178],"However,":[49],"we":[50,125],"argue":[51],"that":[52],"these":[53,84,166],"methods":[54],"have":[55],"overlooked":[56],"two":[57,69,85],"indispensable":[58],"issues:":[59],"1)":[60],"Boundary-bias:":[61],"The":[62,78],"annotated":[63],"target":[64],"generally":[66],"refers":[67],"as":[72,93],"corresponding":[73],"start":[74],"end":[76],"timestamps.":[77],"downsampling":[80],"process":[81],"may":[82],"lose":[83],"take":[88],"adjacent":[90],"irrelevant":[91],"new":[94,100,153],"boundaries.":[95,154],"2)":[96],"Reasoning-bias:":[97],"Such":[98,179],"incorrect":[99],"also":[103,182],"lead":[104],"reasoning":[107,157],"bias":[108],"during":[109],"frame-query":[110,177],"interaction,":[111],"reducing":[112],"generalization":[114],"ability":[115],"model.":[117],"To":[118],"alleviate":[119],"above":[120],"limitations,":[121],"in":[122],"this":[123],"paper,":[124],"propose":[126],"novel":[128],"Siamese":[129],"Sampling":[130],"Reasoning":[132],"Network":[133],"(SSRN)":[134],"TSG,":[136],"which":[137],"introduces":[138],"siamese":[140],"mechanism":[142,180],"generate":[144,169],"additional":[145],"contextual":[146],"enrich":[149],"refine":[151],"Specifically,":[155],"is":[159,181],"developed":[160],"learn":[162],"inter-relationship":[164],"among":[165],"soft":[170],"labels":[171],"on":[172,207],"boundaries":[173],"more":[175],"accurate":[176],"able":[183],"supplement":[185],"absent":[187],"consecutive":[188],"visual":[189],"semantics":[190],"sampled":[193],"fine-grained":[197],"activity":[198],"understanding.":[199],"Extensive":[200],"experiments":[201],"demonstrate":[202],"effectiveness":[204],"SSRN":[206],"three":[208],"challenging":[209],"datasets.":[210]},"counts_by_year":[],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2023-01-06T00:00:00"}