{"id":"https://openalex.org/W7154121420","doi":"https://doi.org/10.48550/arxiv.2604.08945","title":"TouchAnything: Diffusion-Guided 3D Reconstruction from Sparse Robot Touches","display_name":"TouchAnything: Diffusion-Guided 3D Reconstruction from Sparse Robot Touches","publication_year":2026,"publication_date":"2026-04-10","ids":{"openalex":"https://openalex.org/W7154121420","doi":"https://doi.org/10.48550/arxiv.2604.08945"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.08945","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.08945","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.08945","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5121811954","display_name":"Langzhe Gu","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Gu, Langzhe","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012890780","display_name":"Hung-Jui Huang","orcid":"https://orcid.org/0009-0005-5039-3011"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Hung-Jui","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045939421","display_name":"Mohamad Qadri","orcid":"https://orcid.org/0000-0003-3320-5646"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qadri, Mohamad","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133497325","display_name":"Michael Kaess","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kaess, Michael","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133505003","display_name":"Wenzhen Yuan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuan, Wenzhen","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5121811954"],"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":0.48669999837875366,"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":0.48669999837875366,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.19030000269412994,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10914","display_name":"Tactile and Sensory Interactions","score":0.11410000175237656,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.535099983215332},{"id":"https://openalex.org/keywords/3d-reconstruction","display_name":"3D reconstruction","score":0.5268999934196472},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.4693000018596649},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.4334999918937683},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.3917999863624573},{"id":"https://openalex.org/keywords/epipolar-geometry","display_name":"Epipolar geometry","score":0.30300000309944153},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.2976999878883362},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.296999990940094},{"id":"https://openalex.org/keywords/solid-modeling","display_name":"Solid modeling","score":0.28519999980926514}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7928000092506409},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7809000015258789},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6528000235557556},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.535099983215332},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.5268999934196472},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.4693000018596649},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.4334999918937683},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.3917999863624573},{"id":"https://openalex.org/C23379248","wikidata":"https://www.wikidata.org/wiki/Q200904","display_name":"Epipolar geometry","level":3,"score":0.30300000309944153},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.2976999878883362},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.296999990940094},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.28519999980926514},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.28360000252723694},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.27869999408721924},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.2727999985218048},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.2705000042915344},{"id":"https://openalex.org/C46722567","wikidata":"https://www.wikidata.org/wiki/Q7674139","display_name":"Tactile sensor","level":3,"score":0.26809999346733093},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.26260000467300415},{"id":"https://openalex.org/C3004257","wikidata":"https://www.wikidata.org/wiki/Q17084606","display_name":"Correspondence problem","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C193581530","wikidata":"https://www.wikidata.org/wiki/Q683778","display_name":"Structured light","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.26089999079704285},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.260699987411499},{"id":"https://openalex.org/C31487907","wikidata":"https://www.wikidata.org/wiki/Q1154597","display_name":"Polygon mesh","level":2,"score":0.26019999384880066},{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.2549999952316284},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2538999915122986},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.25369998812675476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.08945","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.08945","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":"doi:10.48550/arxiv.2604.08945","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.08945","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":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.5498048067092896,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"object":[1,171],"geometry":[2,50],"estimation":[3],"is":[4,18,56,176],"essential":[5],"for":[6,22,79],"many":[7],"downstream":[8],"tasks,":[9],"including":[10],"robotic":[11],"manipulation":[12],"and":[13,76,121,163],"physical":[14,44],"interaction.":[15],"Although":[16],"vision":[17,70],"the":[19,104,114,127,147],"dominant":[20],"modality":[21],"shape":[23],"perception,":[24],"it":[25],"becomes":[26],"unreliable":[27],"under":[28],"occlusions":[29],"or":[30,94],"challenging":[31],"lighting":[32],"conditions.":[33],"In":[34],"such":[35],"scenarios,":[36],"tactile":[37,84,100,115,138],"sensing":[38],"provides":[39],"direct":[40],"geometric":[41,77,105],"information":[42],"through":[43],"contact.":[45],"However,":[46],"reconstructing":[47],"global":[48],"3D":[49,80,166],"from":[51,82,99,155],"sparse":[52,83,118],"local":[53],"touches":[54],"alone":[55],"fundamentally":[57],"underconstrained.":[58],"We":[59],"present":[60],"TouchAnything,":[61],"a":[62,66,74,122,157],"framework":[63],"that":[64,89,136],"leverages":[65],"pretrained":[67,109],"large-scale":[68],"2D":[69],"diffusion":[71,96,111,148],"model":[72],"as":[73,132],"semantic":[75],"prior":[78,87],"reconstruction":[81,92,131,167],"measurements.":[85],"Unlike":[86],"work":[88],"trains":[90],"category-specific":[91],"networks":[93],"learns":[95],"models":[97,112],"directly":[98],"data,":[101],"we":[102,129],"transfer":[103],"knowledge":[106],"encoded":[107],"in":[108],"visual":[110],"to":[113],"domain.":[116],"Given":[117],"contact":[119],"constraints":[120],"coarse":[123],"class-level":[124],"description":[125],"of":[126,168],"object,":[128],"formulate":[130],"an":[133],"optimization":[134],"problem":[135],"enforces":[137],"consistency":[139],"while":[140],"guiding":[141],"solutions":[142],"toward":[143],"shapes":[144],"consistent":[145],"with":[146],"prior.":[149],"Our":[150,173],"method":[151],"reconstructs":[152],"accurate":[153],"geometries":[154],"only":[156],"few":[158],"touches,":[159],"outperforms":[160],"existing":[161],"baselines,":[162],"enables":[164],"open-world":[165],"previously":[169],"unseen":[170],"instances.":[172],"project":[174],"page":[175],"https://grange007.github.io/touchanything":[177],".":[178]},"counts_by_year":[],"updated_date":"2026-04-14T06:08:25.285971","created_date":"2026-04-14T00:00:00"}