{"id":"https://openalex.org/W7101675749","doi":"https://doi.org/10.1109/lgrs.2025.3626328","title":"Deformable-Aware Neural Radiance Fields for High-Fidelity Drone Geometry Reconstruction","display_name":"Deformable-Aware Neural Radiance Fields for High-Fidelity Drone Geometry Reconstruction","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7101675749","doi":"https://doi.org/10.1109/lgrs.2025.3626328"},"language":null,"primary_location":{"id":"doi:10.1109/lgrs.2025.3626328","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3626328","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-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":null,"display_name":"Li Li","orcid":"https://orcid.org/0009-0003-4642-8045"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Li","raw_affiliation_strings":["School of Geospatial Information, Information Engineering University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0009-0003-4642-8045","affiliations":[{"raw_affiliation_string":"School of Geospatial Information, Information Engineering University, Zhengzhou, China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yongsheng Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongsheng Zhang","raw_affiliation_strings":["School of Geospatial Information, Information Engineering University, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geospatial Information, Information Engineering University, Zhengzhou, China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhipeng Jiang","orcid":"https://orcid.org/0000-0001-8459-080X"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhipeng Jiang","raw_affiliation_strings":["School of Geospatial Information, Information Engineering University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-8459-080X","affiliations":[{"raw_affiliation_string":"School of Geospatial Information, Information Engineering University, Zhengzhou, China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ziquan Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziquan Wang","raw_affiliation_strings":["School of Geospatial Information, Information Engineering University, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geospatial Information, Information Engineering University, Zhengzhou, China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xin Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210160531","display_name":"Chinese People's Liberation Army","ror":"https://ror.org/05tf9r976","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210160531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Lin","raw_affiliation_strings":["32167 Troops, Chinese People’s Liberation Army, Lhasa, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"32167 Troops, Chinese People’s Liberation Army, Lhasa, China","institution_ids":["https://openalex.org/I4210160531"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ying Yu","orcid":"https://orcid.org/0000-0002-1189-3663"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Yu","raw_affiliation_strings":["School of Geospatial Information, Information Engineering University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-1189-3663","affiliations":[{"raw_affiliation_string":"School of Geospatial Information, Information Engineering University, Zhengzhou, China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"last","author":{"id":null,"display_name":"Lei Li","orcid":null},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Li","raw_affiliation_strings":["School of Geospatial Information, Information Engineering University, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geospatial Information, Information Engineering University, Zhengzhou, China","institution_ids":["https://openalex.org/I169689159"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.45958881,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.33390000462532043,"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":0.33390000462532043,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.2102999985218048,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.08100000023841858,"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/radiance","display_name":"Radiance","score":0.7145000100135803},{"id":"https://openalex.org/keywords/drone","display_name":"Drone","score":0.6567000150680542},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6466000080108643},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.5526999831199646},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.5511000156402588},{"id":"https://openalex.org/keywords/facade","display_name":"Facade","score":0.5347999930381775},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4587000012397766},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.3995000123977661},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.392300009727478}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7368999719619751},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7332000136375427},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7178000211715698},{"id":"https://openalex.org/C23690007","wikidata":"https://www.wikidata.org/wiki/Q1411145","display_name":"Radiance","level":2,"score":0.7145000100135803},{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.6567000150680542},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6466000080108643},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.5526999831199646},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.5511000156402588},{"id":"https://openalex.org/C2780113678","wikidata":"https://www.wikidata.org/wiki/Q183061","display_name":"Facade","level":2,"score":0.5347999930381775},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4587000012397766},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3995000123977661},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.392300009727478},{"id":"https://openalex.org/C2779989122","wikidata":"https://www.wikidata.org/wiki/Q15889487","display_name":"Perspective distortion","level":3,"score":0.3873000144958496},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.38119998574256897},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3743000030517578},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.3328999876976013},{"id":"https://openalex.org/C160697094","wikidata":"https://www.wikidata.org/wiki/Q1233197","display_name":"Oblique case","level":2,"score":0.3327000141143799},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3000999987125397},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.29750001430511475},{"id":"https://openalex.org/C50637493","wikidata":"https://www.wikidata.org/wiki/Q1136781","display_name":"Morphing","level":2,"score":0.28929999470710754},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.2775000035762787},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25850000977516174},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.2572999894618988},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.2556000053882599},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.25540000200271606},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.2513999938964844}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2025.3626328","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3626328","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.7448027729988098,"display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G4168836438","display_name":null,"funder_award_id":"221100211000-02","funder_id":"https://openalex.org/F4320330206","funder_display_name":"Science and Technology Program of Hunan Province"}],"funders":[{"id":"https://openalex.org/F4320330206","display_name":"Science and Technology Program of Hunan Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2770937555","https://openalex.org/W2912093940","https://openalex.org/W2962731536","https://openalex.org/W2962849139","https://openalex.org/W3120513023","https://openalex.org/W3138295133","https://openalex.org/W3176084073","https://openalex.org/W4200150166","https://openalex.org/W4223962571","https://openalex.org/W4292828931","https://openalex.org/W4385805083"],"related_works":[],"abstract_inverted_index":{"The":[0],"rapid":[1],"growth":[2],"of":[3],"the":[4],"low-altitude":[5],"economy":[6],"demands":[7],"highly":[8,13],"accurate":[9],"3D":[10],"reconstruction":[11],"from":[12,25],"oblique":[14],"drone":[15,108],"imagery,":[16],"yet":[17],"existing":[18],"Neural":[19],"Radiance":[20],"Fields":[21],"(NeRF)":[22],"methods":[23],"suffer":[24],"severe":[26],"facade":[27,75],"distortions":[28],"and":[29,37,55,77,99,121],"blurred":[30],"details":[31,96],"due":[32],"to":[33],"viewpoint-induced":[34],"radiometric":[35],"inconsistencies":[36],"fixed-frequency":[38],"encoding.":[39,58],"To":[40],"address":[41],"this,":[42],"we":[43],"propose":[44],"Deformable-Aware":[45],"NeRF":[46],"(DA-NeRF),":[47],"a":[48,81],"novel":[49,118],"framework":[50],"integrating":[51],"semantic-guided":[52],"deformable":[53,60],"convolution":[54,61],"frequency-adaptive":[56],"position":[57,83],"Our":[59],"module":[62],"dynamically":[63],"aligns":[64],"multi-view":[65],"image":[66],"features":[67],"by":[68],"learning":[69],"viewpoint-dependent":[70],"sampling":[71],"offsets,":[72],"effectively":[73],"reducing":[74],"distortion":[76],"texture":[78],"loss.":[79],"Further,":[80],"dynamic":[82],"encoding":[84],"mechanism":[85],"further":[86],"adjusts":[87],"high-frequency":[88],"components":[89],"based":[90],"on":[91,105],"semantic":[92],"attributes,":[93],"enhancing":[94],"structural":[95],"in":[97,102,116],"buildings":[98],"suppressing":[100],"noise":[101],"roads.":[103],"Experiments":[104],"our":[106],"collected":[107],"datasets":[109],"show":[110],"that":[111],"DA-NeRF":[112],"achieves":[113],"unprecedented":[114],"fidelity":[115],"both":[117],"view":[119],"synthesis":[120],"DSM":[122],"reconstruction.":[123]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-29T00:00:00"}