{"id":"https://openalex.org/W4294068640","doi":"https://doi.org/10.1109/tpami.2022.3203516","title":"BiFuse++: Self-Supervised and Efficient Bi-Projection Fusion for $360^{\\circ }$ Depth Estimation","display_name":"BiFuse++: Self-Supervised and Efficient Bi-Projection Fusion for $360^{\\circ }$ Depth Estimation","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4294068640","doi":"https://doi.org/10.1109/tpami.2022.3203516","pmid":"https://pubmed.ncbi.nlm.nih.gov/36049011"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2022.3203516","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3203516","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2209.02952","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5014665083","display_name":"Fu-En Wang","orcid":"https://orcid.org/0000-0002-0992-1899"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Fu-En Wang","raw_affiliation_strings":["Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan"],"raw_orcid":"https://orcid.org/0000-0002-0992-1899","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003313794","display_name":"Yu-Hsuan Yeh","orcid":"https://orcid.org/0000-0002-5421-8385"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yu-Hsuan Yeh","raw_affiliation_strings":["Department of Computer Science, National Yang Ming Chiao Tung University, Hsinchu, Taiwan"],"raw_orcid":"https://orcid.org/0000-0002-5421-8385","affiliations":[{"raw_affiliation_string":"Department of Computer Science, National Yang Ming Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034494169","display_name":"Yi-Hsuan Tsai","orcid":"https://orcid.org/0000-0002-6191-0134"},"institutions":[{"id":"https://openalex.org/I4210095611","display_name":"Phiar (United States)","ror":"https://ror.org/00qh9vh90","country_code":"US","type":"company","lineage":["https://openalex.org/I4210095611"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yi-Hsuan Tsai","raw_affiliation_strings":["Phiar Technologies, USA"],"raw_orcid":"https://orcid.org/0000-0002-6191-0134","affiliations":[{"raw_affiliation_string":"Phiar Technologies, USA","institution_ids":["https://openalex.org/I4210095611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038549076","display_name":"Wei-Chen Chiu","orcid":"https://orcid.org/0000-0001-7715-8306"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Wei-Chen Chiu","raw_affiliation_strings":["Department of Computer Science, National Yang Ming Chiao Tung University, Hsinchu, Taiwan"],"raw_orcid":"https://orcid.org/0000-0001-7715-8306","affiliations":[{"raw_affiliation_string":"Department of Computer Science, National Yang Ming Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102008600","display_name":"Min Sun","orcid":"https://orcid.org/0000-0001-9598-8178"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Min Sun","raw_affiliation_strings":["Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan"],"raw_orcid":"https://orcid.org/0000-0001-9598-8178","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0238,"has_fulltext":false,"cited_by_count":33,"citation_normalized_percentile":{"value":0.879843,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"45","issue":"5","first_page":"1","last_page":"13"},"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9968000054359436,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9958000183105469,"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/computer-science","display_name":"Computer science","score":0.7468281984329224},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.742260217666626},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.7230379581451416},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6961241960525513},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.6377568244934082},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5817168951034546},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5450605750083923},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5352391004562378},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5124116539955139},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.43506523966789246},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.27169567346572876},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1489189863204956}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7468281984329224},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.742260217666626},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.7230379581451416},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6961241960525513},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.6377568244934082},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5817168951034546},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5450605750083923},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5352391004562378},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5124116539955139},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.43506523966789246},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.27169567346572876},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1489189863204956},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tpami.2022.3203516","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3203516","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:36049011","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36049011","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null},{"id":"pmh:oai:arXiv.org:2209.02952","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2209.02952","pdf_url":"https://arxiv.org/pdf/2209.02952","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2209.02952","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2209.02952","pdf_url":"https://arxiv.org/pdf/2209.02952","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1915250530","https://openalex.org/W2108598243","https://openalex.org/W2125416623","https://openalex.org/W2132947399","https://openalex.org/W2194775991","https://openalex.org/W2300779272","https://openalex.org/W2336968928","https://openalex.org/W2409352305","https://openalex.org/W2476548250","https://openalex.org/W2520707372","https://openalex.org/W2557465155","https://openalex.org/W2586114507","https://openalex.org/W2605938684","https://openalex.org/W2608018946","https://openalex.org/W2609883120","https://openalex.org/W2788857104","https://openalex.org/W2796422723","https://openalex.org/W2798665861","https://openalex.org/W2883505290","https://openalex.org/W2884401041","https://openalex.org/W2902957614","https://openalex.org/W2948647700","https://openalex.org/W2950559486","https://openalex.org/W2951234442","https://openalex.org/W2955639361","https://openalex.org/W2962741876","https://openalex.org/W2963012943","https://openalex.org/W2963149945","https://openalex.org/W2963433827","https://openalex.org/W2963488291","https://openalex.org/W2963591054","https://openalex.org/W2963623257","https://openalex.org/W2964014680","https://openalex.org/W2964339842","https://openalex.org/W2969261403","https://openalex.org/W2973699682","https://openalex.org/W2982574419","https://openalex.org/W2985775862","https://openalex.org/W3034428934","https://openalex.org/W3034556105","https://openalex.org/W3034604951","https://openalex.org/W3034728336","https://openalex.org/W3034953156","https://openalex.org/W3081167590","https://openalex.org/W3092407498","https://openalex.org/W3107156787","https://openalex.org/W3126573238","https://openalex.org/W3131795671","https://openalex.org/W3173727695","https://openalex.org/W3174211490","https://openalex.org/W3174725336","https://openalex.org/W3175201472","https://openalex.org/W3180638445","https://openalex.org/W4287863801","https://openalex.org/W4295312788","https://openalex.org/W6631190155","https://openalex.org/W6685261749","https://openalex.org/W6733367512","https://openalex.org/W6736260464","https://openalex.org/W6753441378","https://openalex.org/W6765161899","https://openalex.org/W6766978945","https://openalex.org/W6769516661","https://openalex.org/W6771531989"],"related_works":["https://openalex.org/W200819717","https://openalex.org/W2032269556","https://openalex.org/W1991834176","https://openalex.org/W2944448661","https://openalex.org/W2064421702","https://openalex.org/W4253756925","https://openalex.org/W2805523177","https://openalex.org/W2131956013","https://openalex.org/W2036566443","https://openalex.org/W2081241816"],"abstract_inverted_index":{"Due":[0],"to":[1,81,102,142,166],"the":[2,47,61,75,117,123,144,150,168,174],"rise":[3],"of":[4,43,63,77,146,170,176],"spherical":[5],"cameras,":[6],"monocular":[7,24,94],"360$^\\circ$depth":[8,25],"estimation":[9,26,96],"becomes":[10,84],"an":[11],"important":[12],"technique":[13],"for":[14,23,93],"many":[15],"applications":[16],"(e.g.,":[17],"autonomous":[18],"systems).":[19],"Thus,":[20],"state-of-the-art":[21,193],"frameworks":[22,111],"such":[27,37,68],"as":[28],"bi-projection":[29,114,127,147],"fusion":[30,115,128,148,160],"in":[31],"BiFuse":[32,171],"are":[33,56,108],"proposed.":[34],"To":[35,87,153],"train":[36],"a":[38,40,69,85,91,158],"framework,":[39],"large":[41],"number":[42],"panoramas":[44],"along":[45],"with":[46],"corresponding":[48],"depth":[49,95],"ground":[50],"truths":[51],"captured":[52],"by":[53],"laser":[54],"sensors":[55],"required,":[57],"which":[58,120],"highly":[59,121],"increases":[60],"cost":[62],"data":[64,70],"collection.":[65],"Moreover,":[66],"since":[67,126],"collection":[71],"procedure":[72],"is":[73,99],"time-consuming,":[74],"scalability":[76],"extending":[78],"these":[79],"methods":[80],"different":[82,133],"scenes":[83],"challenge.":[86],"this":[88,104,137],"end,":[89],"self-training":[90,118,151,177],"network":[92],"from":[97,132],"360$^\\circ$videos":[98],"one":[100],"way":[101],"alleviate":[103],"issue.":[105],"However,":[106],"there":[107],"no":[109],"existing":[110],"that":[112],"incorporate":[113],"into":[116],"scheme,":[119],"limits":[122],"self-supervised":[124,186],"performance":[125,169],"can":[129],"leverage":[130],"information":[131],"projection":[134],"types.":[135],"In":[136],"paper,":[138],"we":[139,156],"propose":[140,157],"BiFuse++":[141],"explore":[143],"combination":[145],"and":[149,162,172,185,191],"scenario.":[152],"be":[154],"specific,":[155],"new":[159],"module":[161],"Contrast-Aware":[163],"Photometric":[164],"Loss":[165],"improve":[167],"increase":[173],"stability":[175],"on":[178,188],"real-world":[179],"videos.":[180],"We":[181],"conduct":[182],"both":[183],"supervised":[184],"experiments":[187],"benchmark":[189],"datasets":[190],"achieve":[192],"performance.":[194]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":1}],"updated_date":"2026-08-12T21:12:35.861297","created_date":"2022-09-01T00:00:00"}