{"id":"https://openalex.org/W7161295327","doi":"https://doi.org/10.1109/lra.2026.3693984","title":"BurnDC: A Progressive Propagation Framework for Low Coverage Depth Completion","display_name":"BurnDC: A Progressive Propagation Framework for Low Coverage Depth Completion","publication_year":2026,"publication_date":"2026-05-15","ids":{"openalex":"https://openalex.org/W7161295327","doi":"https://doi.org/10.1109/lra.2026.3693984"},"language":null,"primary_location":{"id":"doi:10.1109/lra.2026.3693984","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2026.3693984","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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 Robotics and Automation 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":"https://openalex.org/A5086926899","display_name":"Zhengyu Zhu","orcid":"https://orcid.org/0000-0001-6562-8243"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengyu Zhu","raw_affiliation_strings":["School of Artificial Intelligence, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0001-2943-1088","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136220887","display_name":"Cong Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cong Zhang","raw_affiliation_strings":["School of Artificial Intelligence, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136238773","display_name":"Hongmin Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongmin Liu","raw_affiliation_strings":["School of Artificial Intelligence, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9834-4087","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5136232366","display_name":"Bin Fan","orcid":null},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Fan","raw_affiliation_strings":["School of Artificial Intelligence, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-1155-467X","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I92403157"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.6382055,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":"7","first_page":"8052","last_page":"8059"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.12809999287128448,"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"}},"topics":[{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.12809999287128448,"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/T11019","display_name":"Image Enhancement Techniques","score":0.06599999964237213,"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":0.042100001126527786,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/completion","display_name":"Completion (oil and gas wells)","score":0.3199999928474426},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.2915000021457672},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.26159998774528503},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.23240000009536743},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.22619999945163727}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42669999599456787},{"id":"https://openalex.org/C2779538338","wikidata":"https://www.wikidata.org/wiki/Q2990590","display_name":"Completion (oil and gas wells)","level":2,"score":0.3199999928474426},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.2915000021457672},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.26159998774528503},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2578999996185303},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2379000037908554},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.23240000009536743},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.22619999945163727},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.22120000422000885},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.22089999914169312}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2026.3693984","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2026.3693984","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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 Robotics and Automation Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","score":0.5684131383895874,"display_name":"Climate action"}],"awards":[{"id":"https://openalex.org/G2832388536","display_name":null,"funder_award_id":"U24A20218","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4103426291","display_name":null,"funder_award_id":"U2441251","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G974957621","display_name":null,"funder_award_id":"U22B2055","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"growing":[1],"adoption":[2],"of":[3,103,146,162],"compact":[4],"and":[5,56,61,83,101,120,127],"cost-effective":[6],"solid-state":[7,115,163],"LiDARs":[8,164],"has":[9],"greatly":[10],"advanced":[11],"robotics.":[12],"However,":[13],"their":[14,20],"inherently":[15],"limited":[16],"Field-of-View":[17],"(FOV)":[18],"hinders":[19],"application":[21],"in":[22,125,138,165],"tasks":[23],"requiring":[24],"wide-range":[25],"depth":[26,47,54,76,106],"perception.":[27],"To":[28,108],"overcome":[29],"this":[30],"limitation,":[31],"we":[32,111],"introduce":[33],"the":[34,71,104,159],"Low":[35],"Coverage":[36],"Depth":[37,80],"Completion":[38],"(LCDC)":[39],"task,":[40],"which":[41],"aims":[42],"to":[43,89],"generate":[44],"a":[45,50,57,63,98,113,154],"full-scene":[46],"map":[48,55],"from":[49],"low":[51,122,139],"coverage":[52,123,140],"sparse":[53],"corresponding":[58],"RGB":[59],"image,":[60],"propose":[62],"tailored":[64],"framework":[65],"named":[66],"BurnDC.":[67],"BurnDC":[68,133],"progressively":[69],"expands":[70],"propagation":[72],"frontier":[73],"around":[74],"reliable":[75],"anchors":[77],"via":[78],"Progressive":[79],"Burn":[81],"(PDB)":[82],"utilizes":[84],"Weighted":[85],"Ring":[86],"Attention":[87],"(WRA)":[88],"inject":[90],"stable":[91],"geometric":[92],"context":[93],"into":[94],"boundary":[95],"regions,":[96],"achieving":[97],"controlled":[99],"refinement":[100],"completion":[102],"entire":[105],"map.":[107],"evaluate":[109],"LCDC,":[110],"construct":[112],"real-world":[114],"LiDAR":[116],"based":[117],"benchmark,":[118],"LC-TIERS,":[119],"simulate":[121],"settings":[124],"NYUv2":[126],"KITTI.":[128],"Experimental":[129],"results":[130],"demonstrate":[131],"that":[132],"significantly":[134],"outperforms":[135],"existing":[136],"methods":[137],"scenarios,":[141],"with":[142],"an":[143],"RMSE":[144],"reduction":[145],"10-20%":[147],"over":[148],"top":[149],"competitors.":[150],"Our":[151],"work":[152],"provides":[153],"promising":[155],"solution":[156],"for":[157],"unlocking":[158],"full":[160],"potential":[161],"various":[166],"applications.":[167],"Code":[168],"available":[169],"at:":[170],"<uri":[171],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[172],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/yudmoe/burnDC/</uri>.":[173]},"counts_by_year":[],"updated_date":"2026-05-23T06:10:36.450269","created_date":"2026-05-16T00:00:00"}