{"id":"https://openalex.org/W7138300246","doi":"https://doi.org/10.1609/aaai.v40i15.38273","title":"Tracking and Segmenting Anything in Any Modality","display_name":"Tracking and Segmenting Anything in Any Modality","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138300246","doi":"https://doi.org/10.1609/aaai.v40i15.38273"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v40i15.38273","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i15.38273","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/38273/42235","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/38273/42235","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079575136","display_name":"Tianlu Zhang","orcid":"https://orcid.org/0000-0003-4592-5448"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianlu Zhang","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129662465","display_name":"Qiang Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Zhang","raw_affiliation_strings":["Xidian University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian University","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129708934","display_name":"Guiguang Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guiguang Ding","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129646354","display_name":"Jungong Han","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jungong Han","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"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":"40","issue":"15","first_page":"12762","last_page":"12770"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.4043999910354614,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.4043999910354614,"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":0.2705000042915344,"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":0.12250000238418579,"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/segmentation","display_name":"Segmentation","score":0.7143999934196472},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5647000074386597},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5519000291824341},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5397999882698059},{"id":"https://openalex.org/keywords/market-segmentation","display_name":"Market segmentation","score":0.5335000157356262},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5037999749183655},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.4968999922275543},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.4941999912261963},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.482699990272522}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7340999841690063},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7143999934196472},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.692300021648407},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5647000074386597},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5519000291824341},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5397999882698059},{"id":"https://openalex.org/C125308379","wikidata":"https://www.wikidata.org/wiki/Q363057","display_name":"Market segmentation","level":2,"score":0.5335000157356262},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5037999749183655},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.4968999922275543},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.4941999912261963},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4876999855041504},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.482699990272522},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.46540001034736633},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.45399999618530273},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4442000091075897},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4345000088214874},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41269999742507935},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.40119999647140503},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.36649999022483826},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3458000123500824},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3450999855995178},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.3165000081062317},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3003000020980835},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.29760000109672546},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.28279998898506165},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2721000015735626},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.26649999618530273},{"id":"https://openalex.org/C142853389","wikidata":"https://www.wikidata.org/wiki/Q744778","display_name":"Association (psychology)","level":2,"score":0.2522999942302704},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.25060001015663147},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.25029999017715454}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v40i15.38273","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i15.38273","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/38273/42235","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:ojs.aaai.org:article/38273","is_oa":false,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/38273","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i15.38273","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i15.38273","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/38273/42235","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G338250432","display_name":null,"funder_award_id":"62441235","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":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7138300246.pdf","grobid_xml":"https://content.openalex.org/works/W7138300246.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Tracking":[0,173],"and":[1,13,40,50,78,90,112,124,154,210],"segmentation":[2,51,113,125,211],"play":[3],"essential":[4],"roles":[5],"in":[6],"video":[7,19,220],"understanding,":[8],"providing":[9],"basic":[10],"positional":[11],"information":[12],"temporal":[14],"association":[15],"of":[16,56,98,122,150,186,196],"objects":[17],"within":[18],"sequences.":[20],"Despite":[21],"their":[22,38],"shared":[23,152],"objective,":[24],"existing":[25],"approaches":[26,65],"often":[27],"tackle":[28],"these":[29,64,105],"tasks":[30],"using":[31],"specialized":[32],"architectures":[33],"or":[34,60],"modality-specific":[35],"parameters,":[36],"limiting":[37],"generalization":[39],"scalability.":[41],"Recent":[42],"efforts":[43],"have":[44],"attempted":[45],"to":[46,67,139,161,176],"unify":[47,177],"multiple":[48],"tracking":[49,111,123,209],"sub-tasks":[52],"from":[53],"the":[54,72,79,96,141,147,159,179,194],"perspectives":[55],"any":[57,128],"modality":[58,129],"input":[59],"multi-task":[61,200],"inference.":[62],"However,":[63],"tend":[66],"overlook":[68],"two":[69],"critical":[70],"challenges:":[71],"distributional":[73],"gap":[74,82],"across":[75,83],"different":[76],"modalities":[77],"feature":[80],"representation":[81,143],"tasks.":[84],"These":[85],"issues":[86],"hinder":[87],"effective":[88],"cross-task":[89],"cross-modal":[91,151],"knowledge":[92,153,198],"sharing,":[93],"ultimately":[94],"constraining":[95],"development":[97],"a":[99,109,119,132,170,183,214],"true":[100],"generalist":[101],"model.":[102],"To":[103],"address":[104],"limitations,":[106],"we":[107,168],"propose":[108],"universal":[110],"framework":[114],"named":[115],"SATA,":[116],"which":[117],"unifies":[118],"broad":[120],"spectrum":[121],"subtasks":[126],"with":[127,188],"input.":[130],"Specifically,":[131],"Decoupled":[133],"Mixture-of-Expert":[134],"(DeMoE)":[135],"mechanism":[136],"is":[137],"presented":[138],"decouple":[140],"unified":[142,184],"learning":[144],"task":[145,180],"into":[146],"modeling":[148],"process":[149],"specific":[155],"information,":[156,191],"thus":[157],"enabling":[158],"model":[160],"maintain":[162],"flexibility":[163],"while":[164],"enhancing":[165],"generalization.":[166],"Additionally,":[167],"introduce":[169],"Task-aware":[171],"Multi-object":[172],"(TaMOT)":[174],"pipeline":[175],"all":[178],"outputs":[181],"as":[182],"set":[185],"instances":[187],"calibrated":[189],"ID":[190],"thereby":[192],"alleviating":[193],"degradation":[195],"task-specific":[197],"during":[199],"training.":[201],"SATA":[202],"demonstrates":[203],"superior":[204],"performance":[205],"on":[206],"18":[207],"challenging":[208],"benchmarks,":[212],"offering":[213],"novel":[215],"perspective":[216],"for":[217],"more":[218],"generalizable":[219],"understanding.":[221]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-03-18T00:00:00"}
