{"id":"https://openalex.org/W7160308119","doi":"https://doi.org/10.1109/wacv61042.2026.00088","title":"MSRTrack: LLM-Powered Object Tracking with Motion and Semantic Reasoning","display_name":"MSRTrack: LLM-Powered Object Tracking with Motion and Semantic Reasoning","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W7160308119","doi":"https://doi.org/10.1109/wacv61042.2026.00088"},"language":null,"primary_location":{"id":"doi:10.1109/wacv61042.2026.00088","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00088","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5026209754","display_name":"Tong Shen","orcid":"https://orcid.org/0000-0003-1299-106X"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tong Shen","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135315120","display_name":"\u8fea Di \u738b Wang","orcid":"https://orcid.org/0009-0004-2632-0165"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Di Wang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5045861415","display_name":"Jos\u00e9 M. F. Moura","orcid":"https://orcid.org/0000-0002-9822-8294"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jos\u00e9 M. F. Moura","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.52170579,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"838","last_page":"848"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.536300003528595,"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":0.536300003528595,"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/T12031","display_name":"Speech and dialogue systems","score":0.09570000320672989,"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"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.0551999993622303,"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/object","display_name":"Object (grammar)","score":0.5957000255584717},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.4666000008583069},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.3919000029563904},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.32710000872612},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.31150001287460327}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7128000259399414},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.641700029373169},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6376000046730042},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5957000255584717},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.4666000008583069},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.3919000029563904},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.32710000872612},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.31150001287460327},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.28119999170303345},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.26969999074935913},{"id":"https://openalex.org/C95020103","wikidata":"https://www.wikidata.org/wiki/Q1813492","display_name":"Match moving","level":3,"score":0.26669999957084656},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wacv61042.2026.00088","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00088","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1926876413","https://openalex.org/W1999478556","https://openalex.org/W2082297081","https://openalex.org/W2317031775","https://openalex.org/W2470957771","https://openalex.org/W2518876086","https://openalex.org/W2605173812","https://openalex.org/W2794744029","https://openalex.org/W2891033863","https://openalex.org/W2898200825","https://openalex.org/W3090155371","https://openalex.org/W3096609285","https://openalex.org/W3167536469","https://openalex.org/W3181069167","https://openalex.org/W3214586131","https://openalex.org/W4214759957","https://openalex.org/W4312323989","https://openalex.org/W4312396403","https://openalex.org/W4312751983","https://openalex.org/W4312805142","https://openalex.org/W4313156423","https://openalex.org/W4385245566","https://openalex.org/W4386066081","https://openalex.org/W4386066394","https://openalex.org/W4386066459","https://openalex.org/W4386075643","https://openalex.org/W4387969322","https://openalex.org/W4390871890","https://openalex.org/W4390874039","https://openalex.org/W4390874575","https://openalex.org/W4390889789","https://openalex.org/W4393147957","https://openalex.org/W4394713372","https://openalex.org/W4399344486","https://openalex.org/W4402702990","https://openalex.org/W4402704550","https://openalex.org/W4402727134","https://openalex.org/W4402727824","https://openalex.org/W4402728032","https://openalex.org/W4402753915","https://openalex.org/W4402753923","https://openalex.org/W4402754150","https://openalex.org/W4402754270","https://openalex.org/W4402951596","https://openalex.org/W4402981768","https://openalex.org/W4405844469","https://openalex.org/W4409366594","https://openalex.org/W4409367158","https://openalex.org/W4409368393","https://openalex.org/W4409368509","https://openalex.org/W4413147546","https://openalex.org/W4415798615","https://openalex.org/W7122474438","https://openalex.org/W7133193636","https://openalex.org/W7133224883"],"related_works":[],"abstract_inverted_index":{"State-of-the-art":[0],"object":[1],"trackers":[2,113],"primarily":[3],"model":[4],"appearance":[5,46],"relations":[6],"between":[7],"the":[8,12,34,53,90,102,145,167,173,179],"image":[9],"template":[10],"and":[11,30,48,64,72,89,110,117,152,176],"search":[13],"region":[14],"with":[15,62,114,163],"Siamese":[16],"networks.":[17],"However,":[18],"this":[19],"well-established":[20],"approach":[21],"has":[22],"a":[23,58,137],"limited":[24],"ability":[25],"to":[26,38],"leverage":[27],"both":[28],"motion":[29,70,105],"semantic":[31,74,99,116,142],"cues":[32,106],"of":[33,101,140,144],"target":[35,149],"object,":[36],"leading":[37],"increasing":[39],"errors":[40],"in":[41],"challenging":[42],"scenarios":[43],"like":[44],"drastic":[45],"changes":[47],"similar-looking":[49],"distractors.":[50],"To":[51],"address":[52],"above":[54],"weaknesses,":[55],"we":[56],"propose":[57],"novel":[59],"tracking":[60,78,125,161],"framework":[61],"Motion":[63],"Semantic":[65],"Reasoning":[66],"(MSRTrack),":[67],"integrating":[68],"short-term":[69],"modeling":[71],"distinctive":[73],"features":[75],"for":[76],"robust":[77],"across":[79,107,159],"diverse":[80],"conditions.":[81],"Powered":[82],"by":[83],"vision":[84,123],"large":[85],"language":[86,124],"models":[87],"(VLLMs)":[88],"Segment":[91],"Anything":[92],"Model":[93],"2":[94],"(SAM2),":[95],"MSRTrack":[96,133,155],"identifies":[97],"unique":[98],"attributes":[100,143],"target,":[103,146],"exploits":[104],"consecutive":[108],"frames,":[109],"complements":[111],"appearance-based":[112],"strong":[115],"dynamic":[118],"reasoning":[119],"capabilities.":[120],"Unlike":[121],"previous":[122],"(VLT)":[126],"methods":[127],"that":[128],"rely":[129],"on":[130,136,166,172,178],"broad":[131],"captioning,":[132],"automatically":[134],"focuses":[135],"concise":[138],"set":[139],"key":[141],"substantially":[147],"improving":[148],"lost":[150],"recovery":[151],"distractor":[153],"rejection.":[154],"achieves":[156],"state-of-the-art":[157],"performance":[158],"multiple":[160],"benchmarks,":[162],"2.2%":[164],"improvement":[165,171],"LaSOT":[168],"dataset,":[169,175],"9.5%":[170],"VastTrack":[174],"1.4%":[177],"TNL2K":[180],"dataset.":[181]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-05-06T00:00:00"}