{"id":"https://openalex.org/W7161706439","doi":"https://doi.org/10.48550/arxiv.2605.18013","title":"TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model","display_name":"TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model","publication_year":2026,"publication_date":"2026-05-18","ids":{"openalex":"https://openalex.org/W7161706439","doi":"https://doi.org/10.48550/arxiv.2605.18013"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.18013","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.18013","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":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.18013","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136487250","display_name":"Zhaoyuan Ding","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding, Zhaoyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060735481","display_name":"Yijing Yang","orcid":"https://orcid.org/0000-0003-4197-2570"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Yijing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136468321","display_name":"Han Shu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shu, Han","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136504433","display_name":"Xinghao Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Xinghao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.3529999852180481,"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":0.3529999852180481,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.2565999925136566,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.20029999315738678,"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/encoder","display_name":"Encoder","score":0.49300000071525574},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4805000126361847},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.44290000200271606},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.4368000030517578},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.4334999918937683},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.413100004196167},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4018000066280365},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.398499995470047},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.38830000162124634}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8396000266075134},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5121999979019165},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.49300000071525574},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4893999993801117},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4805000126361847},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.44290000200271606},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.4368000030517578},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.4334999918937683},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.413100004196167},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4018000066280365},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.398499995470047},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.38830000162124634},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.37610000371932983},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.37299999594688416},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.3727000057697296},{"id":"https://openalex.org/C176649486","wikidata":"https://www.wikidata.org/wiki/Q2308807","display_name":"Memory management","level":3,"score":0.33980000019073486},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3231000006198883},{"id":"https://openalex.org/C82687282","wikidata":"https://www.wikidata.org/wiki/Q66221","display_name":"Auxiliary memory","level":2,"score":0.3228999972343445},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.31859999895095825},{"id":"https://openalex.org/C12186640","wikidata":"https://www.wikidata.org/wiki/Q6815743","display_name":"Memory model","level":3,"score":0.3012999892234802},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.29589998722076416},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.28850001096725464},{"id":"https://openalex.org/C57863822","wikidata":"https://www.wikidata.org/wiki/Q905488","display_name":"Flat memory model","level":4,"score":0.2849000096321106},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.2840999960899353},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.28290000557899475},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.28119999170303345},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.27410000562667847},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.25380000472068787}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.18013","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.18013","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":"doi:10.48550/arxiv.2605.18013","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.18013","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":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.49568066000938416}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Segment":[0],"Anything":[1],"Model":[2],"2":[3,183],"(SAM":[4],"2)":[5],"serves":[6],"as":[7,37,103,159,176],"a":[8,26,78,89,108,220],"core":[9],"foundation":[10],"model":[11,82,168],"in":[12,34,67,132,146,207],"the":[13,20,46,61,64,104,116,133,137,147,160,167,187,205,224],"field":[14],"of":[15,50,186,189,227],"video":[16,39,80,228],"segmentation.":[17],"Building":[18],"upon":[19],"original":[21],"SAM":[22,51,190,217],"model,":[23],"it":[24],"introduces":[25],"memory":[27,57,90,117,148,195],"bank":[28,149],"mechanism":[29,93],"and":[30,42,56,86,98,119,178,197,212],"demonstrates":[31],"outstanding":[32],"performance":[33,85,188],"tasks":[35],"such":[36,175],"semi-supervised":[38],"object":[40],"segmentation":[41,81,229],"tracking":[43],"anything.":[44],"However,":[45],"complex":[47],"computational":[48,120,210],"characteristics":[49],"2's":[52],"multi-stage":[53],"image":[54,162],"encoder":[55],"module":[58],"have":[59],"raised":[60],"barrier":[62],"to":[63,96,127],"model's":[65],"deployment":[66,213],"practical":[68],"applications.":[69],"To":[70],"address":[71],"this":[72],"issue,":[73],"we":[74,156],"propose":[75],"TinySAM":[76,182],"2,":[77,218],"lightweight":[79,161],"that":[83,114,181],"balances":[84],"efficiency.":[87],"First,":[88],"quality":[91],"management":[92],"is":[94,112,125],"introduced":[95],"select":[97],"retain":[99],"high-informative":[100],"historical":[101],"frames":[102,145],"memory.":[105],"In":[106,136],"addition,":[107],"joint-spatial-temporal":[109],"token":[110],"compression":[111],"proposed":[113],"reduces":[115,166],"storage":[118],"cost.":[121],"Specifically,":[122],"average":[123],"pooling":[124],"employed":[126],"first":[128],"compress":[129],"redundancy":[130],"tokens":[131,141,196],"spatial":[134],"domain.":[135],"temporal":[138],"domain,":[139],"informative":[140],"are":[142],"selected":[143],"across":[144],"based":[150],"on":[151,172,231],"token-level":[152],"similarity":[153],"measurement.":[154],"Besides,":[155],"take":[157],"RepViT":[158],"encoder,":[163],"which":[164],"further":[165],"parameters.":[169],"Extensive":[170],"experiments":[171],"challenging":[173],"datasets":[174],"DAVIS":[177],"SA-V":[179],"demonstrate":[180],"achieves":[184],"90%":[185],"2.1,":[191],"with":[192,216],"only":[193],"7%":[194],"3%":[198],"training":[199],"data.":[200],"This":[201],"study":[202],"effectively":[203],"alleviates":[204],"bottlenecks":[206],"parameter":[208],"count,":[209],"load,":[211],"costs":[214],"associated":[215],"providing":[219],"resource-efficient":[221],"solution":[222],"for":[223],"widespread":[225],"application":[226],"models":[230],"devices.":[232]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-20T00:00:00"}