{"id":"https://openalex.org/W7133209166","doi":"https://doi.org/10.48550/arxiv.2602.24181","title":"A Mixed Diet Makes DINO An Omnivorous Vision Encoder","display_name":"A Mixed Diet Makes DINO An Omnivorous Vision Encoder","publication_year":2026,"publication_date":"2026-02-27","ids":{"openalex":"https://openalex.org/W7133209166","doi":"https://doi.org/10.48550/arxiv.2602.24181"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.24181","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"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":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071865603","display_name":"Rishabh Kabra","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kabra, Rishabh","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127790323","display_name":"Maks Ovsjanikov","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ovsjanikov, Maks","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027693232","display_name":"Drew A. Hudson","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hudson, Drew A.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127816388","display_name":"Ye Xia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xia, Ye","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035812263","display_name":"Skanda Koppula","orcid":"https://orcid.org/0009-0007-5397-1854"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Koppula, Skanda","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127811901","display_name":"Andre Araujo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Araujo, Andre","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122950769","display_name":"Jo\u00e3o Carreira","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Carreira, Joao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5058170430","display_name":"Niloy J. Mitra","orcid":"https://orcid.org/0000-0002-2597-0914"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mitra, Niloy J.","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5071865603"],"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/T10036","display_name":"Advanced Neural Network Applications","score":0.3301999866962433,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.3301999866962433,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.11710000038146973,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.058800000697374344,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.7475000023841858},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7141000032424927},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6269999742507935},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5184000134468079},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.49459999799728394},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4593000113964081},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4302999973297119},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.42179998755455017}],"concepts":[{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.7475000023841858},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7214999794960022},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7141000032424927},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6269999742507935},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6266000270843506},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5823000073432922},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5184000134468079},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.49459999799728394},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4593000113964081},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4302999973297119},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.42179998755455017},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.4027999937534332},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.39809998869895935},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.36800000071525574},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.35100001096725464},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.3352999985218048},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.31290000677108765},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.30090001225471497},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.28780001401901245},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.27790001034736633},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2687999904155731},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.2554999887943268}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.24181","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"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":"Article"},{"id":"doi:10.48550/arxiv.2602.24181","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.24181","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":"pmh:doi:10.48550/arxiv.2602.24181","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"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":"Article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7911887764930725}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Pre-trained":[0],"vision":[1],"encoders":[2],"like":[3],"DINOv2":[4],"have":[5],"demonstrated":[6],"exceptional":[7],"performance":[8],"on":[9],"unimodal":[10],"tasks.":[11],"However,":[12],"we":[13,61],"observe":[14],"that":[15,47,52,70,102],"their":[16],"feature":[17,28,74,88],"representations":[18,106],"are":[19],"poorly":[20],"aligned":[21],"across":[22],"different":[23,91],"modalities.":[24],"For":[25],"instance,":[26],"the":[27,40,63,78,87,94,104,108,136,151,155],"embedding":[29,129],"for":[30,130],"an":[31],"RGB":[32],"image":[33],"and":[34,97],"its":[35],"corresponding":[36],"depth":[37],"map":[38],"of":[39,53,93,110,135,154],"same":[41,95],"scene":[42],"exhibit":[43],"a":[44,67,72,81,99,111,126,131],"cosine":[45],"similarity":[46],"is":[48],"nearly":[49],"identical":[50],"to":[51,85,107],"two":[54],"random,":[55],"unrelated":[56],"images.":[57],"To":[58],"address":[59],"this,":[60],"propose":[62],"Omnivorous":[64],"Vision":[65],"Encoder,":[66],"novel":[68],"framework":[69],"learns":[71],"modality-agnostic":[73],"space.":[75],"We":[76],"train":[77],"encoder":[79,121],"with":[80],"dual":[82],"objective:":[83],"first,":[84],"maximize":[86],"alignment":[89],"between":[90],"modalities":[92],"scene;":[96],"second,":[98],"distillation":[100],"objective":[101],"anchors":[103],"learned":[105],"output":[109],"fully":[112],"frozen":[113],"teacher":[114],"such":[115],"as":[116],"DINOv2.":[117],"The":[118],"resulting":[119],"student":[120],"becomes":[122],"\"omnivorous\"":[123],"by":[124],"producing":[125],"consistent,":[127],"powerful":[128],"given":[132],"scene,":[133],"regardless":[134],"input":[137],"modality":[138],"(RGB,":[139],"Depth,":[140],"Segmentation,":[141],"etc.).":[142],"This":[143],"approach":[144],"enables":[145],"robust":[146],"cross-modal":[147],"understanding":[148],"while":[149],"retaining":[150],"discriminative":[152],"semantics":[153],"original":[156],"foundation":[157],"model.":[158]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-03-03T00:00:00"}
