{"id":"https://openalex.org/W4416750324","doi":"https://doi.org/10.1109/iros60139.2025.11247003","title":"rt-RISeg: Real-Time Model-Free Robot Interactive Segmentation for Active Instance-Level Object Understanding","display_name":"rt-RISeg: Real-Time Model-Free Robot Interactive Segmentation for Active Instance-Level Object Understanding","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4416750324","doi":"https://doi.org/10.1109/iros60139.2025.11247003"},"language":null,"primary_location":{"id":"doi:10.1109/iros60139.2025.11247003","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11247003","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"type":"article","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/A5113134748","display_name":"Howard H. Qian","orcid":null},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Howard H. Qian","raw_affiliation_strings":["Rice University,Department of Computer Science,Houston,TX,USA,77005"],"affiliations":[{"raw_affiliation_string":"Rice University,Department of Computer Science,Houston,TX,USA,77005","institution_ids":["https://openalex.org/I74775410"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100348260","display_name":"Yi\u2010Ting Chen","orcid":"https://orcid.org/0000-0002-0063-4965"},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiting Chen","raw_affiliation_strings":["Rice University,Department of Computer Science,Houston,TX,USA,77005"],"affiliations":[{"raw_affiliation_string":"Rice University,Department of Computer Science,Houston,TX,USA,77005","institution_ids":["https://openalex.org/I74775410"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089761031","display_name":"Gaotian Wang","orcid":"https://orcid.org/0009-0008-6189-3873"},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gaotian Wang","raw_affiliation_strings":["Rice University,Department of Computer Science,Houston,TX,USA,77005"],"affiliations":[{"raw_affiliation_string":"Rice University,Department of Computer Science,Houston,TX,USA,77005","institution_ids":["https://openalex.org/I74775410"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026417037","display_name":"Podshara Chanrungmaneekul","orcid":null},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Podshara Chanrungmaneekul","raw_affiliation_strings":["Rice University,Department of Computer Science,Houston,TX,USA,77005"],"affiliations":[{"raw_affiliation_string":"Rice University,Department of Computer Science,Houston,TX,USA,77005","institution_ids":["https://openalex.org/I74775410"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011451275","display_name":"Kaiyu Hang","orcid":"https://orcid.org/0000-0003-4132-1217"},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kaiyu Hang","raw_affiliation_strings":["Rice University,Department of Computer Science,Houston,TX,USA,77005"],"affiliations":[{"raw_affiliation_string":"Rice University,Department of Computer Science,Houston,TX,USA,77005","institution_ids":["https://openalex.org/I74775410"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5113134748"],"corresponding_institution_ids":["https://openalex.org/I74775410"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.44999189,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"11561","last_page":"11568"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9128000140190125,"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":0.9128000140190125,"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":0.019300000742077827,"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":0.014499999582767487,"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":0.7718999981880188},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.6506999731063843},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6331999897956848},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.5267000198364258},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.515999972820282},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4657999873161316},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.46480000019073486},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.44119998812675476}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7925999760627747},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7718999981880188},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7397000193595886},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7081000208854675},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6506999731063843},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6331999897956848},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.5267000198364258},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.515999972820282},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4657999873161316},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.46480000019073486},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.44119998812675476},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4284999966621399},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4138000011444092},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.39969998598098755},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.37560001015663147},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.3684999942779541},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.29910001158714294},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.27799999713897705},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.2750000059604645},{"id":"https://openalex.org/C111370547","wikidata":"https://www.wikidata.org/wiki/Q7451120","display_name":"Sensory cue","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.25690001249313354},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2551000118255615}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros60139.2025.11247003","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11247003","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1519958327","https://openalex.org/W1605181360","https://openalex.org/W1866852672","https://openalex.org/W1970531977","https://openalex.org/W1999478155","https://openalex.org/W2067191022","https://openalex.org/W2085261163","https://openalex.org/W2103088500","https://openalex.org/W2118154608","https://openalex.org/W2150903798","https://openalex.org/W2165830610","https://openalex.org/W2337977475","https://openalex.org/W2604662268","https://openalex.org/W2906430385","https://openalex.org/W2946970867","https://openalex.org/W2963678509","https://openalex.org/W2963837081","https://openalex.org/W2966885779","https://openalex.org/W3109908659","https://openalex.org/W3137905681","https://openalex.org/W3200139538","https://openalex.org/W4214570817","https://openalex.org/W4383108475","https://openalex.org/W4385430481","https://openalex.org/W4390874575","https://openalex.org/W4399469378","https://openalex.org/W4401413709","https://openalex.org/W4401413773"],"related_works":[],"abstract_inverted_index":{"Successful":[0],"execution":[1],"of":[2,70,104,120,170],"dexterous":[3],"robotic":[4],"manipulation":[5],"tasks":[6],"in":[7,30,53],"new":[8],"environments,":[9],"such":[10],"as":[11,208],"grasping,":[12],"depends":[13],"on":[14,38,46,73],"the":[15,23,68,74,114,157,168,200],"ability":[16],"to":[17,44,133,159,164,210],"proficiently":[18],"segment":[19],"unseen":[20,31,97],"objects":[21,98,135],"from":[22,126],"background":[24],"and":[25,81,102,117,147],"other":[26],"objects.":[27],"Previous":[28],"works":[29],"object":[32,149,180],"instance":[33],"segmentation":[34,139,144,150,181,203],"(UOIS)":[35],"train":[36],"models":[37,213],"large-scale":[39],"datasets,":[40],"which":[41],"often":[42],"leads":[43],"overfitting":[45],"static":[47],"visual":[48],"features.":[49],"This":[50,141],"dependency":[51],"results":[52],"poor":[54],"generalization":[55],"performance":[56],"when":[57],"confronted":[58],"with":[59],"out-of-distribution":[60],"scenarios.":[61],"To":[62],"address":[63],"this":[64],"limitation,":[65],"we":[66,197],"rethink":[67],"task":[69],"UOIS":[71,188],"based":[72],"principle":[75],"that":[76,94,113,199],"vision":[77,211],"is":[78,193],"inherently":[79],"interactive":[80,90,173],"occurs":[82],"over":[83],"time.":[84],"We":[85,111,166],"propose":[86],"a":[87,105,194],"novel":[88],"real-time":[89],"perception":[91,174],"framework,":[92,196],"rt-RISeg,":[93],"continuously":[95],"segments":[96],"by":[99,176],"robot":[100,128,154],"interactions":[101],"analysis":[103],"designed":[106],"body":[107,123],"frame-invariant":[108],"feature":[109],"(BFIF).":[110],"demonstrate":[112],"relative":[115],"rotational":[116],"linear":[118],"velocities":[119],"randomly":[121],"sampled":[122],"frames,":[124],"resulting":[125],"selected":[127],"interactions,":[129],"can":[130,205],"be":[131,206],"used":[132,207],"identify":[134],"without":[136,156],"any":[137],"learned":[138],"model.":[140],"fully":[142],"self-contained":[143],"pipeline":[145],"generates":[146],"updates":[148],"masks":[151,204],"throughout":[152],"each":[153],"interaction":[155],"need":[158],"wait":[160],"for":[161,214],"an":[162,178],"action":[163],"finish.":[165],"showcase":[167],"effectiveness":[169],"our":[171],"proposed":[172],"method":[175],"achieving":[177],"average":[179],"accuracy":[182],"rate":[183],"27.5%":[184],"greater":[185],"than":[186],"state-of-the-art":[187],"methods.":[189],"Furthermore,":[190],"although":[191],"rt-RISeg":[192],"standalone":[195],"show":[198],"autonomously":[201],"generated":[202],"prompts":[209],"foundation":[212],"significantly":[215],"improved":[216],"performance.":[217]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-11-28T00:00:00"}
