{"id":"https://openalex.org/W4318189300","doi":"https://doi.org/10.1109/lra.2023.3240093","title":"Expanding Sparse LiDAR Depth and Guiding Stereo Matching for Robust Dense Depth Estimation","display_name":"Expanding Sparse LiDAR Depth and Guiding Stereo Matching for Robust Dense Depth Estimation","publication_year":2023,"publication_date":"2023-01-26","ids":{"openalex":"https://openalex.org/W4318189300","doi":"https://doi.org/10.1109/lra.2023.3240093"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2023.3240093","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2023.3240093","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766","2377-3774"],"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/A5101545997","display_name":"Zhenyu Xu","orcid":"https://orcid.org/0000-0002-2469-0339"},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenyu Xu","raw_affiliation_strings":["Research Center of Intelligent Robotics, Zhejiang Lab, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-2469-0339","affiliations":[{"raw_affiliation_string":"Research Center of Intelligent Robotics, Zhejiang Lab, Hangzhou, China","institution_ids":["https://openalex.org/I4210123185"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074721358","display_name":"Yuehua Li","orcid":"https://orcid.org/0000-0001-5631-885X"},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuehua Li","raw_affiliation_strings":["Research Center of Beijing, Zhejiang Lab, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-5631-885X","affiliations":[{"raw_affiliation_string":"Research Center of Beijing, Zhejiang Lab, Hangzhou, China","institution_ids":["https://openalex.org/I4210123185"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039356472","display_name":"Shiqiang Zhu","orcid":"https://orcid.org/0000-0002-5687-4001"},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiqiang Zhu","raw_affiliation_strings":["Zhejiang Lab, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang Lab, Hangzhou, China","institution_ids":["https://openalex.org/I4210123185"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039935452","display_name":"Yuxiang Sun","orcid":"https://orcid.org/0000-0002-7704-0559"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yuxiang Sun","raw_affiliation_strings":["The Hong Kong Polytechnic University, Kowloon, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-7704-0559","affiliations":[{"raw_affiliation_string":"The Hong Kong Polytechnic University, Kowloon, Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3667,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.80050541,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"8","issue":"3","first_page":"1479","last_page":"1486"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":1.0,"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/T10531","display_name":"Advanced Vision and Imaging","score":1.0,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9993000030517578,"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"}},{"id":"https://openalex.org/T10638","display_name":"Optical measurement and interference techniques","score":0.9983000159263611,"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/lidar","display_name":"Lidar","score":0.8845902681350708},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7570837140083313},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6883655190467834},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6373487114906311},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5822224617004395},{"id":"https://openalex.org/keywords/depth-map","display_name":"Depth map","score":0.43859708309173584},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.42538073658943176},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.41106194257736206},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3838875889778137},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.2933550775051117},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.20207160711288452},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.19060072302818298}],"concepts":[{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.8845902681350708},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7570837140083313},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6883655190467834},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6373487114906311},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5822224617004395},{"id":"https://openalex.org/C141268832","wikidata":"https://www.wikidata.org/wiki/Q2940499","display_name":"Depth map","level":3,"score":0.43859708309173584},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.42538073658943176},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.41106194257736206},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3838875889778137},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.2933550775051117},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.20207160711288452},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.19060072302818298},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2023.3240093","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2023.3240093","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766","2377-3774"],"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":[{"score":0.6100000143051147,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G3799234178","display_name":null,"funder_award_id":"U21B6001","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":30,"referenced_works":["https://openalex.org/W1772650917","https://openalex.org/W1921093919","https://openalex.org/W2604231069","https://openalex.org/W2886851716","https://openalex.org/W2892161145","https://openalex.org/W2950496566","https://openalex.org/W2952813711","https://openalex.org/W2955092942","https://openalex.org/W2963045776","https://openalex.org/W2963316641","https://openalex.org/W2963619659","https://openalex.org/W2998293366","https://openalex.org/W3003928900","https://openalex.org/W3004166074","https://openalex.org/W3034514115","https://openalex.org/W3034530552","https://openalex.org/W3034548607","https://openalex.org/W3041219150","https://openalex.org/W3089999934","https://openalex.org/W3145086533","https://openalex.org/W3172573759","https://openalex.org/W3174318861","https://openalex.org/W3176027594","https://openalex.org/W3176755188","https://openalex.org/W3206335707","https://openalex.org/W4221146773","https://openalex.org/W4312566889","https://openalex.org/W4312793957","https://openalex.org/W4312819733","https://openalex.org/W6638039622"],"related_works":["https://openalex.org/W4319317934","https://openalex.org/W2901265155","https://openalex.org/W2956374172","https://openalex.org/W4319837668","https://openalex.org/W4308071650","https://openalex.org/W3188333020","https://openalex.org/W1964041166","https://openalex.org/W4390887692","https://openalex.org/W4210818033","https://openalex.org/W4221065211"],"abstract_inverted_index":{"Dense":[0],"depth":[1,24,63,86,110,114],"estimation":[2],"is":[3,77,131,149],"an":[4],"important":[5],"task":[6],"for":[7,22],"applications,":[8],"such":[9],"as":[10,18,118],"object":[11],"detection,":[12],"3-D":[13],"reconstruction,":[14],"etc.":[15],"Stereo":[16],"matching,":[17],"a":[19,44,93,100,112,126],"popular":[20],"method":[21,103,130,148],"dense":[23],"estimation,":[25],"has":[26,41],"been":[27],"faced":[28],"with":[29,49,115,135],"challenges":[30],"when":[31,74],"low":[32,79],"textures,":[33],"occlusions":[34],"or":[35,80],"domain":[36],"gaps":[37],"exist.":[38],"Stereo-LiDAR":[39],"fusion":[40,67,102,147],"recently":[42],"become":[43],"promising":[45],"way":[46],"to":[47,54,70,95,111,133,152],"deal":[48,134],"these":[50],"challenges.":[51],"However,":[52],"due":[53],"the":[55,61,72,85,107,123,136,154,179,182],"sparsity":[56],"and":[57,146,176],"uneven":[58],"distribution":[59],"of":[60,139,181],"LiDAR":[62,109],"data,":[64],"existing":[65],"stereo-LiDAR":[66,101],"methods":[68],"tend":[69],"ignore":[71],"data":[73],"their":[75],"density":[76],"quite":[78],"they":[81],"largely":[82],"differ":[83],"from":[84,88],"predicted":[87],"stereo":[89],"images.":[90],"To":[91],"provide":[92],"solution":[94],"this":[96],"problem,":[97],"we":[98],"propose":[99],"by":[104],"first":[105],"expanding":[106],"sparse":[108,162],"semi-dense":[113,124],"RGB":[116],"image":[117],"reference.":[119],"Then,":[120],"based":[121],"on":[122,168],"depth,":[125],"varying-weight":[127],"Gaussian":[128],"guiding":[129,140],"proposed":[132],"varying":[137],"reliability":[138],"signals.":[141],"A":[142],"multi-scale":[143],"feature":[144],"extraction":[145],"further":[150],"used":[151],"enhance":[153],"network,":[155],"which":[156],"shows":[157],"superior":[158,174],"performance":[159],"over":[160,178],"traditional":[161],"invariant":[163],"convolution":[164],"methods.":[165],"Experimental":[166],"results":[167],"different":[169],"public":[170],"datasets":[171],"demonstrate":[172],"our":[173],"accuracy":[175],"robustness":[177],"state":[180],"arts.":[183]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}