{"id":"https://openalex.org/W7158879152","doi":"https://doi.org/10.48550/arxiv.2604.26637","title":"ATLAS: An Annotation Tool for Long-horizon Robotic Action Segmentation","display_name":"ATLAS: An Annotation Tool for Long-horizon Robotic Action Segmentation","publication_year":2026,"publication_date":"2026-04-29","ids":{"openalex":"https://openalex.org/W7158879152","doi":"https://doi.org/10.48550/arxiv.2604.26637"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.26637","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.26637","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2604.26637","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5116211342","display_name":"Sergej Stanovcic","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stanovcic, Sergej","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134907088","display_name":"Daniel Sliwowski","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sliwowski, Daniel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134901504","display_name":"Dongheui Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Dongheui","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/T10653","display_name":"Robot Manipulation and Learning","score":0.7218000292778015,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.7218000292778015,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.06830000132322311,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.06210000067949295,"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/annotation","display_name":"Annotation","score":0.8374999761581421},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5461999773979187},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5424000024795532},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.5299000144004822},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.453900009393692},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.3772999942302704},{"id":"https://openalex.org/keywords/automatic-image-annotation","display_name":"Automatic image annotation","score":0.3564999997615814},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.33329999446868896}],"concepts":[{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.8374999761581421},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7698000073432922},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6761000156402588},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5461999773979187},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5424000024795532},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.5299000144004822},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.453900009393692},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38929998874664307},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3772999942302704},{"id":"https://openalex.org/C199579030","wikidata":"https://www.wikidata.org/wiki/Q2851778","display_name":"Automatic image annotation","level":4,"score":0.3564999997615814},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.33329999446868896},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.2957000136375427},{"id":"https://openalex.org/C2776673561","wikidata":"https://www.wikidata.org/wiki/Q655357","display_name":"Atlas (anatomy)","level":2,"score":0.2777000069618225},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.2721000015735626},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.26910001039505005},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.26820001006126404},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.26409998536109924},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.26350000500679016},{"id":"https://openalex.org/C2779982483","wikidata":"https://www.wikidata.org/wiki/Q6094420","display_name":"Iterative refinement","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.2558000087738037},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2551000118255615},{"id":"https://openalex.org/C89505385","wikidata":"https://www.wikidata.org/wiki/Q47146","display_name":"User interface","level":2,"score":0.2540000081062317},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2513999938964844},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.26637","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.26637","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.26637","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.26637","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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":{"Annotating":[0],"long-horizon":[1,72],"robotic":[2,73,82],"demonstrations":[3],"with":[4,184],"precise":[5],"temporal":[6,182],"action":[7,15,74,94,96],"boundaries":[8],"is":[9],"crucial":[10],"for":[11,33,71,125],"training":[12],"and":[13,17,87,90,98,114,121,151,191],"evaluating":[14],"segmentation":[16],"manipulation":[18],"policy":[19],"learning":[20],"methods.":[21],"Existing":[22],"annotation":[23,68,92,149,166,199],"tools,":[24],"however,":[25],"are":[26,30],"often":[27],"limited:":[28],"they":[29],"designed":[31],"primarily":[32],"vision-only":[34,198],"data,":[35,83],"do":[36],"not":[37],"natively":[38,103],"support":[39,124],"synchronized":[40],"visualization":[41,79],"of":[42,80,93,178],"robot-specific":[43],"time-series":[44,179],"signals":[45],"(e.g.,":[46],"gripper":[47],"state":[48],"or":[49,51],"force/torque),":[50],"require":[52],"substantial":[53],"effort":[54,150],"to":[55,57,136,173,197],"adapt":[56],"different":[58],"dataset":[59,108,142],"formats.":[60],"In":[61,154],"this":[62],"paper,":[63],"we":[64],"introduce":[65],"ATLAS,":[66],"an":[67],"tool":[69,102],"tailored":[70],"segmentation.":[75],"ATLAS":[76,131,161],"provides":[77,122],"time-synchronized":[78],"multi-modal":[81],"including":[84],"multi-view":[85],"video":[86],"proprioceptive":[88],"signals,":[89],"supports":[91],"boundaries,":[95],"labels,":[97],"task":[99],"outcomes.":[100],"The":[101],"handles":[104],"widely":[105],"used":[106],"robotics":[107],"formats":[109,138],"such":[110,128],"as":[111,129],"ROS":[112],"bags":[113],"the":[115,163,176],"Reinforcement":[116],"Learning":[117],"Dataset":[118],"(RLDS)":[119],"format,":[120],"direct":[123],"specific":[126],"datasets":[127],"REASSEMBLE.":[130],"can":[132],"be":[133],"easily":[134],"extended":[135],"new":[137],"via":[139],"a":[140,157],"modular":[141],"abstraction":[143],"layer.":[144],"Its":[145],"keyboard-centric":[146],"interface":[147],"minimizes":[148],"improves":[152],"efficiency.":[153],"experiments":[155],"on":[156],"contact-rich":[158],"assembly":[159],"task,":[160],"reduced":[162],"average":[164],"per-action":[165],"time":[167],"by":[168,187],"at":[169],"least":[170],"6%":[171],"compared":[172,196],"ELAN,":[174],"while":[175],"inclusion":[177],"data":[180],"improved":[181],"alignment":[183],"expert":[185],"annotations":[186],"more":[188],"than":[189],"2.8%":[190],"decreased":[192],"boundary":[193],"error":[194],"fivefold":[195],"tools.":[200]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-01T00:00:00"}