{"id":"https://openalex.org/W4416749735","doi":"https://doi.org/10.1109/iros60139.2025.11245809","title":"Efficient Prediction of Dense Visual Embeddings via Distillation and RGB-D Transformers","display_name":"Efficient Prediction of Dense Visual Embeddings via Distillation and RGB-D Transformers","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4416749735","doi":"https://doi.org/10.1109/iros60139.2025.11245809"},"language":null,"primary_location":{"id":"doi:10.1109/iros60139.2025.11245809","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11245809","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":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2601.00359","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019677916","display_name":"S\u00f6hnke Benedikt Fischedick","orcid":"https://orcid.org/0000-0001-8447-0584"},"institutions":[{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"S\u00f6hnke Benedikt Fischedick","raw_affiliation_strings":["Technische Universität Ilmenau,Neuroinformatics and Cognitive Robotics Lab,Ilmenau,Germany,98693"],"affiliations":[{"raw_affiliation_string":"Technische Universität Ilmenau,Neuroinformatics and Cognitive Robotics Lab,Ilmenau,Germany,98693","institution_ids":["https://openalex.org/I119449181"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077353311","display_name":"Daniel Seichter","orcid":"https://orcid.org/0000-0002-3828-2926"},"institutions":[{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Daniel Seichter","raw_affiliation_strings":["Technische Universität Ilmenau,Neuroinformatics and Cognitive Robotics Lab,Ilmenau,Germany,98693"],"affiliations":[{"raw_affiliation_string":"Technische Universität Ilmenau,Neuroinformatics and Cognitive Robotics Lab,Ilmenau,Germany,98693","institution_ids":["https://openalex.org/I119449181"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068815583","display_name":"Benedict Stephan","orcid":"https://orcid.org/0000-0001-5445-3935"},"institutions":[{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Benedict Stephan","raw_affiliation_strings":["Technische Universität Ilmenau,Neuroinformatics and Cognitive Robotics Lab,Ilmenau,Germany,98693"],"affiliations":[{"raw_affiliation_string":"Technische Universität Ilmenau,Neuroinformatics and Cognitive Robotics Lab,Ilmenau,Germany,98693","institution_ids":["https://openalex.org/I119449181"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065050142","display_name":"Robin Schmidt","orcid":"https://orcid.org/0000-0001-5613-8349"},"institutions":[{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Robin Schmidt","raw_affiliation_strings":["Technische Universität Ilmenau,Neuroinformatics and Cognitive Robotics Lab,Ilmenau,Germany,98693"],"affiliations":[{"raw_affiliation_string":"Technische Universität Ilmenau,Neuroinformatics and Cognitive Robotics Lab,Ilmenau,Germany,98693","institution_ids":["https://openalex.org/I119449181"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075114390","display_name":"Horst\u2013Michael Gro\u00df","orcid":"https://orcid.org/0000-0001-9712-0225"},"institutions":[{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Horst-Michael Gross","raw_affiliation_strings":["Technische Universität Ilmenau,Neuroinformatics and Cognitive Robotics Lab,Ilmenau,Germany,98693"],"affiliations":[{"raw_affiliation_string":"Technische Universität Ilmenau,Neuroinformatics and Cognitive Robotics Lab,Ilmenau,Germany,98693","institution_ids":["https://openalex.org/I119449181"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5019677916"],"corresponding_institution_ids":["https://openalex.org/I119449181"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37038015,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2400","last_page":"2407"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.894599974155426,"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":0.894599974155426,"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":0.02879999950528145,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.02710000053048134,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.6904000043869019},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6600000262260437},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5131000280380249},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.4659000039100647},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.46540001034736633},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.43160000443458557},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.39899998903274536}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7788000106811523},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6904000043869019},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6600000262260437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5157999992370605},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5131000280380249},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.4659000039100647},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.46540001034736633},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.43160000443458557},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.39899998903274536},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.3885999917984009},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3847000002861023},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3407999873161316},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.27950000762939453},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.2777999937534332},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26660001277923584},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.25769999623298645}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iros60139.2025.11245809","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11245809","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"},{"id":"pmh:oai:arXiv.org:2601.00359","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2601.00359","pdf_url":"https://arxiv.org/pdf/2601.00359","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2601.00359","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2601.00359","pdf_url":"https://arxiv.org/pdf/2601.00359","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309895","display_name":"Carl-Zeiss-Stiftung","ror":"https://ror.org/03ng4kg22"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W1923184257","https://openalex.org/W2037341500","https://openalex.org/W2507296351","https://openalex.org/W2587989515","https://openalex.org/W2594519801","https://openalex.org/W2787091153","https://openalex.org/W2924485953","https://openalex.org/W2956887593","https://openalex.org/W2963896186","https://openalex.org/W2971014764","https://openalex.org/W2973181288","https://openalex.org/W3004300126","https://openalex.org/W3097660860","https://openalex.org/W3105966348","https://openalex.org/W3108601100","https://openalex.org/W3110108516","https://openalex.org/W3168649818","https://openalex.org/W3194841206","https://openalex.org/W3201048198","https://openalex.org/W3207537403","https://openalex.org/W4285102466","https://openalex.org/W4285192809","https://openalex.org/W4286982960","https://openalex.org/W4312349930","https://openalex.org/W4312372834","https://openalex.org/W4312610896","https://openalex.org/W4312685069","https://openalex.org/W4312815172","https://openalex.org/W4312935996","https://openalex.org/W4312960937","https://openalex.org/W4385245566","https://openalex.org/W4385488625","https://openalex.org/W4386065383","https://openalex.org/W4386065698","https://openalex.org/W4386179772","https://openalex.org/W4389667339","https://openalex.org/W4390272170","https://openalex.org/W4390872133","https://openalex.org/W4398202191","https://openalex.org/W4399563945","https://openalex.org/W4402703011","https://openalex.org/W4402715795","https://openalex.org/W4402727277","https://openalex.org/W4402773761","https://openalex.org/W4403919731"],"related_works":[],"abstract_inverted_index":{"In":[0,19],"domestic":[1],"environments,":[2],"robots":[3],"require":[4],"a":[5,124,154],"comprehensive":[6,95],"understanding":[7],"of":[8,42],"their":[9],"surroundings":[10],"to":[11,59],"interact":[12],"effectively":[13],"and":[14,89,121,142,166],"intuitively":[15],"with":[16,48],"untrained":[17],"humans.":[18],"this":[20,72],"paper,":[21],"we":[22,134],"propose":[23],"DVEFormer":[24,65],"\u2013":[25],"an":[26,128],"efficient":[27,62],"RGB-D":[28],"Transformer-based":[29],"approach":[30,73,106],"that":[31,104,138],"predicts":[32],"dense":[33],"text-aligned":[34],"visual":[35],"embeddings":[36,56],"(DVE)":[37],"via":[38,80],"knowledge":[39],"distillation.":[40],"Instead":[41],"directly":[43],"performing":[44],"classical":[45,76],"semantic":[46,77],"segmentation":[47,159],"fixed":[49],"predefined":[50],"classes,":[51],"our":[52,61,105,150],"method":[53,151],"uses":[54],"teacher":[55],"from":[57],"Alpha-CLIP":[58],"guide":[60],"student":[63],"model":[64,120],"in":[66,146],"learning":[67],"fine-grained":[68],"pixel-wise":[69],"embeddings.":[70],"While":[71],"still":[74],"enables":[75,85],"segmentation,":[78],"e.g.,":[79],"linear":[81],"probing,":[82],"it":[83],"further":[84],"flexible":[86,163],"text-based":[87],"querying":[88,165],"other":[90],"applications,":[91],"such":[92],"as":[93,153],"creating":[94],"3D":[96,170],"maps.":[97],"Evaluations":[98],"on":[99,127],"common":[100],"indoor":[101],"datasets":[102],"demonstrate":[103],"achieves":[107],"competitive":[108],"performance":[109],"while":[110,161],"meeting":[111],"real-time":[112],"requirements,":[113],"operating":[114],"at":[115],"26.3FPS":[116],"for":[117,123,157,173],"the":[118,140],"full":[119],"77.0FPS":[122],"smaller":[125],"variant":[126],"NVIDIA":[129],"Jetson":[130],"AGX":[131],"Orin.":[132],"Additionally,":[133],"show":[135],"qualitative":[136],"results":[137],"highlight":[139],"effectiveness":[141],"possible":[143],"use":[144],"cases":[145],"real-world":[147],"applications.":[148],"Overall,":[149],"serves":[152],"drop-in":[155],"replacement":[156],"traditional":[158],"approaches":[160],"enabling":[162],"natural-language":[164],"seamless":[167],"integration":[168],"into":[169],"mapping":[171],"pipelines":[172],"mobile":[174],"robotics.":[175]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-11-28T00:00:00"}