{"id":"https://openalex.org/W7140220726","doi":"https://doi.org/10.48550/arxiv.2603.20669","title":"ToFormer: Towards Large-scale Scenario Depth Completion for Lightweight ToF Camera","display_name":"ToFormer: Towards Large-scale Scenario Depth Completion for Lightweight ToF Camera","publication_year":2026,"publication_date":"2026-03-21","ids":{"openalex":"https://openalex.org/W7140220726","doi":"https://doi.org/10.48550/arxiv.2603.20669"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.20669","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.20669","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.2603.20669","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Chen, Juncheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Juncheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Lai, Tiancheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lai, Tiancheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Wang, Xingpeng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xingpeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Liao, Bingxin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liao, Bingxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Zhang, Baozhe","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Baozhe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Xu, Chao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Chao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Cao, Yanjun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cao, Yanjun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"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/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9341999888420105,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9341999888420105,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.05270000174641609,"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"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.0013000000035390258,"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/pipeline","display_name":"Pipeline (software)","score":0.6747000217437744},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.5568000078201294},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.5393000245094299},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5310999751091003},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.40619999170303345},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.38350000977516174},{"id":"https://openalex.org/keywords/depth-map","display_name":"Depth map","score":0.37310001254081726},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.35989999771118164}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.730400025844574},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6747000217437744},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5963000059127808},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.5568000078201294},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5393000245094299},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5310999751091003},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5008000135421753},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4081999957561493},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.40619999170303345},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.38350000977516174},{"id":"https://openalex.org/C141268832","wikidata":"https://www.wikidata.org/wiki/Q2940499","display_name":"Depth map","level":3,"score":0.37310001254081726},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.35989999771118164},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.3276999890804291},{"id":"https://openalex.org/C2780056265","wikidata":"https://www.wikidata.org/wiki/Q106239881","display_name":"High dynamic range","level":3,"score":0.3197000026702881},{"id":"https://openalex.org/C86369673","wikidata":"https://www.wikidata.org/wiki/Q1203659","display_name":"Simultaneous localization and mapping","level":4,"score":0.2996000051498413},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2973000109195709},{"id":"https://openalex.org/C193581530","wikidata":"https://www.wikidata.org/wiki/Q683778","display_name":"Structured light","level":2,"score":0.29339998960494995},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.28349998593330383},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2637999951839447},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.2605000138282776},{"id":"https://openalex.org/C3018868555","wikidata":"https://www.wikidata.org/wiki/Q2918907","display_name":"Single camera","level":2,"score":0.25270000100135803}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.20669","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.20669","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.2603.20669","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.20669","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":[{"display_name":"Industry, innovation and infrastructure","score":0.40054839849472046,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Time-of-Flight":[0],"(ToF)":[1],"cameras":[2],"possess":[3],"compact":[4],"design":[5,189],"and":[6,49,127,138,218],"high":[7],"measurement":[8],"precision":[9],"to":[10,13,35,51,53,85,162,165,190,195],"be":[11],"applied":[12],"various":[14],"robot":[15],"tasks.":[16],"However,":[17],"their":[18],"limited":[19],"sensing":[20,38],"range":[21,39],"restricts":[22],"deployment":[23],"in":[24,68,221],"large-scale":[25,69,92,216],"scenarios.":[26],"Depth":[27],"completion":[28,67,102,111],"has":[29],"emerged":[30],"as":[31,159],"a":[32,61,78,82,108,115,120,160,208,211],"potential":[33],"solution":[34],"expand":[36],"the":[37,96,152,183,197],"of":[40,135],"ToF":[41,54,73,88,100,144,163,226],"cameras,":[42],"but":[43],"existing":[44],"research":[45],"lacks":[46],"dedicated":[47],"datasets":[48],"struggles":[50],"generalize":[52],"measurements.":[55],"In":[56],"this":[57],"paper,":[58],"we":[59,76,106,203],"propose":[60,107],"full-stack":[62],"framework":[63],"that":[64,113,172],"enables":[65],"depth":[66,101,110,145,164],"scenarios":[70],"for":[71,224],"short-range":[72,225],"cameras.":[74,227],"First,":[75],"construct":[77],"multi-sensor":[79],"platform":[80],"with":[81,90,119],"reconstruction-based":[83],"pipeline":[84],"collect":[86],"real-world":[87],"samples":[89],"dense":[91],"ground":[93],"truth,":[94],"yielding":[95],"first":[97],"LArge-ScalE":[98],"scenaRio":[99],"dataset":[103],"(LASER-ToF).":[104],"Second,":[105],"sensor-aware":[109],"network":[112,149],"incorporates":[114],"novel":[116],"3D":[117],"branch":[118],"3D-2D":[121,140],"Joint":[122],"Propagation":[123],"Pooling":[124],"(JPP)":[125],"module":[126],"Multimodal":[128],"Cross-Covariance":[129],"Attention":[130],"(MXCA),":[131],"enabling":[132,214],"effective":[133],"modeling":[134],"long-range":[136,219],"relationships":[137],"efficient":[139],"fusion":[141],"under":[142],"non-uniform":[143],"sparsity.":[146],"Moreover,":[147],"our":[148,173],"can":[150],"utilize":[151],"sparse":[153],"point":[154],"cloud":[155],"from":[156],"visual":[157],"SLAM":[158],"supplement":[161],"further":[166],"improve":[167],"prediction":[168],"accuracy.":[169],"Experiments":[170],"show":[171],"method":[174,206],"achieves":[175],"an":[176],"8.6%":[177],"lower":[178],"mean":[179],"absolute":[180],"error":[181],"than":[182],"second-best":[184],"method,":[185],"while":[186],"maintaining":[187],"lightweight":[188],"support":[191],"onboard":[192],"deployment.":[193],"Finally,":[194],"verify":[196],"system's":[198],"applicability":[199],"on":[200,207],"real":[201],"robots,":[202],"deploy":[204],"proposed":[205],"quadrotor":[209],"at":[210],"10Hz":[212],"runtime,":[213],"reliable":[215],"mapping":[217],"planning":[220],"challenging":[222],"environments":[223]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-25T00:00:00"}
