{"id":"https://openalex.org/W7162806068","doi":"https://doi.org/10.48550/arxiv.2605.29097","title":"GeRaF: Neural Geometry Reconstruction from Radio Frequency Signals","display_name":"GeRaF: Neural Geometry Reconstruction from Radio Frequency Signals","publication_year":2026,"publication_date":"2026-05-27","ids":{"openalex":"https://openalex.org/W7162806068","doi":"https://doi.org/10.48550/arxiv.2605.29097"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.29097","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.29097","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2605.29097","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137344204","display_name":"Jiachen Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Jiachen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030093811","display_name":"Hailan Shanbhag","orcid":"https://orcid.org/0009-0007-2320-0223"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shanbhag, Hailan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137357073","display_name":"Haitham Al Hassanieh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hassanieh, Haitham Al","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.12890000641345978,"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"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.12890000641345978,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.1143999993801117,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T11408","display_name":"Advanced Optical Imaging Technologies","score":0.09440000355243683,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/rendering","display_name":"Rendering (computer graphics)","score":0.7660999894142151},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5180000066757202},{"id":"https://openalex.org/keywords/radio-frequency","display_name":"Radio frequency","score":0.5073999762535095},{"id":"https://openalex.org/keywords/specular-reflection","display_name":"Specular reflection","score":0.4472000002861023},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.4043999910354614},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.38519999384880066},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.37380000948905945},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.35910001397132874}],"concepts":[{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.7660999894142151},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6355000138282776},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6074000000953674},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5812000036239624},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5180000066757202},{"id":"https://openalex.org/C74064498","wikidata":"https://www.wikidata.org/wiki/Q3396184","display_name":"Radio frequency","level":2,"score":0.5073999762535095},{"id":"https://openalex.org/C118381688","wikidata":"https://www.wikidata.org/wiki/Q1079524","display_name":"Specular reflection","level":2,"score":0.4472000002861023},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.4043999910354614},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.38519999384880066},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.37380000948905945},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.35910001397132874},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.34139999747276306},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.3357999920845032},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.3246999979019165},{"id":"https://openalex.org/C36816356","wikidata":"https://www.wikidata.org/wiki/Q16911860","display_name":"3D rendering","level":3,"score":0.27639999985694885},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.2644999921321869},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.26159998774528503},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2615000009536743}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.29097","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.29097","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.29097","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.29097","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"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":{"GeRaF":[0,89,139],"is":[1],"the":[2,58,141],"first":[3,142],"method":[4],"to":[5,39,51,66,94],"use":[6],"neural":[7],"implicit":[8],"learning":[9,126],"for":[10],"near-range":[11],"3D":[12],"geometry":[13,147],"reconstruction":[14],"from":[15,33,148],"radio":[16],"frequency":[17],"(RF)":[18],"signals.":[19],"Unlike":[20],"RGB":[21,47],"or":[22],"LiDAR-based":[23],"methods,":[24],"RF":[25,54,73,102,149],"sensing":[26],"can":[27],"see":[28],"through":[29,57,134],"occlusion":[30],"but":[31],"suffers":[32],"low":[34],"resolution":[35],"and":[36,64,106,113,131,136],"noise":[37,63],"due":[38],"its":[40],"lensless":[41,111,114],"imaging":[42,48],"nature.":[43],"While":[44],"lenses":[45],"in":[46,69,151],"constrain":[49],"sampling":[50,112,121],"1D":[52],"rays,":[53],"signals":[55,74,150],"propagate":[56],"entire":[59],"space,":[60],"introducing":[61],"significant":[62],"leading":[65],"cubic":[67],"complexity":[68],"volumetric":[70,103],"rendering.":[71],"Moreover,":[72],"interact":[75],"with":[76],"surfaces":[77],"via":[78],"specular":[79],"reflections,":[80],"requiring":[81],"fundamentally":[82],"different":[83],"modeling.":[84],"To":[85],"address":[86],"these":[87],"challenges,":[88],"(1)":[90],"introduces":[91],"filter-based":[92],"rendering":[93,104],"suppress":[95],"irrelevant":[96],"signals,":[97],"(2)":[98],"implements":[99],"a":[100,109],"physics-based":[101],"pipeline,":[105],"(3)":[107],"proposes":[108],"novel":[110],"alpha":[115],"blending":[116],"strategy":[117],"that":[118],"makes":[119],"full-space":[120],"feasible":[122],"during":[123],"training.":[124],"By":[125],"signed":[127],"distance":[128],"functions,":[129],"reflectiveness,":[130],"signal":[132],"power":[133],"MLPs":[135],"trainable":[137],"parameters,":[138],"takes":[140],"step":[143],"towards":[144],"reconstructing":[145],"millimeter-level":[146],"real-world":[152],"settings.":[153]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-30T00:00:00"}
