{"id":"https://openalex.org/W7166670285","doi":"https://doi.org/10.48550/arxiv.2606.29531","title":"MotionAtlas: Detailed Region Captioning for Motion-Centric Videos","display_name":"MotionAtlas: Detailed Region Captioning for Motion-Centric Videos","publication_year":2026,"publication_date":"2026-06-28","ids":{"openalex":"https://openalex.org/W7166670285","doi":"https://doi.org/10.48550/arxiv.2606.29531"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.29531","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.29531","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.29531","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139675935","display_name":"Weisong Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Weisong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139682733","display_name":"Haochen Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Haochen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139689592","display_name":"Kuan Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Kuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139685195","display_name":"Yuhao Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yuhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139683399","display_name":"Yikang Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Yikang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066111997","display_name":"Zhongwei Ren","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ren, Zhongwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136591099","display_name":"Jacky Mai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mai, Jacky","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087779128","display_name":"A F Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Anna","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139651947","display_name":"Yanwei Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yanwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139689879","display_name":"Jason Jisen Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Jason","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139647752","display_name":"Zhaoxiang Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Zhaoxiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":0.48989999294281006,"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":0.48989999294281006,"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":0.20360000431537628,"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":0.11479999870061874,"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":0.8537999987602234},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.7031999826431274},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5676000118255615},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5640000104904175},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.48980000615119934},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.48089998960494995},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.45559999346733093},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4372999966144562}],"concepts":[{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.8537999987602234},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8068000078201294},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.7031999826431274},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5676000118255615},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5659999847412109},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5640000104904175},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.48980000615119934},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.48089998960494995},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.45559999346733093},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4372999966144562},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3970000147819519},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.37049999833106995},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3084000051021576},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.3050999939441681},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2973000109195709},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.2930999994277954},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2906999886035919},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2881999909877777},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.2669999897480011},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.29531","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.29531","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.29531","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.29531","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":"Preprint"},"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":{"We":[0],"propose":[1],"MotionAtlas,":[2],"a":[3,13,18,28,46,49,80,90,110,133],"system":[4],"for":[5,89],"detailed":[6],"captioning":[7,37,128],"of":[8,30,57,93,102,162],"motion-centric":[9,95],"videos,":[10,96],"comprising":[11,83],"(1)":[12],"dedicated":[14],"human-annotated":[15],"benchmark,":[16,171],"(2)":[17],"scalable,":[19],"high-quality":[20,126],"pipeline":[21,115],"to":[22,97,120],"construct":[23],"training":[24,135],"samples,":[25],"and":[26,48,67,70,112,142,152,173],"(3)":[27],"family":[29],"powerful":[31],"Video-MLLMs.":[32],"Unlike":[33],"conventional":[34],"global":[35],"motion":[36,43,58,68,100,127,168],"datasets,":[38],"we":[39,76,108,131],"focus":[40],"on":[41],"region-aware":[42],"captioning:":[44],"given":[45],"video":[47],"spatiotemporal":[50],"mask,":[51],"the":[52,60,103],"model":[53],"generates":[54],"precise":[55],"descriptions":[56],"within":[59],"target":[61],"region,":[62],"thereby":[63],"alleviating":[64],"visual":[65],"clutter":[66],"entanglement":[69],"enabling":[71],"reliable,":[72],"quantifiable":[73],"evaluation.":[74],"Concretely,":[75],"first":[77],"build":[78],"MotionAtlas-Bench,":[79],"comprehensive":[81],"benchmark":[82],"2,073":[84],"multiple-choice":[85],"questions,":[86],"meticulously":[87],"annotated":[88],"curated":[91],"set":[92],"high-quality,":[94],"evaluate":[98],"fine-grained":[99,122],"understanding":[101],"objects":[104],"in":[105],"question.":[106],"Second,":[107],"design":[109,132],"rigorous":[111],"scalable":[113],"data":[114,136],"that":[116],"leverages":[117],"self-bootstrap":[118],"refinement":[119],"suppress":[121],"hallucinations,":[123],"yielding":[124],"159k":[125],"data.":[129],"Third,":[130],"tailored":[134],"composition":[137],"strategy,":[138],"which":[139],"achieves":[140],"consistent":[141],"substantial":[143],"performance":[144],"gains":[145],"across":[146,166],"diverse":[147],"baseline":[148],"Video-MLLMs,":[149],"including":[150],"Molmo2":[151],"Qwen3-VL.":[153],"For":[154],"instance,":[155],"MotionAtlas-4B":[156],"surpasses":[157],"Qwen3-VL-4B":[158],"by":[159],"an":[160],"average":[161],"5.2":[163],"percentage":[164],"points":[165],"general":[167],"benchmarks.":[169],"The":[170],"dataset,":[172],"code":[174],"have":[175],"been":[176],"released.":[177]},"counts_by_year":[],"updated_date":"2026-07-01T06:29:00.853634","created_date":"2026-07-01T00:00:00"}