{"id":"https://openalex.org/W4407450971","doi":"https://doi.org/10.1109/tpami.2025.3541964","title":"Revisiting Gradient-Based Uncertainty for Monocular Depth Estimation","display_name":"Revisiting Gradient-Based Uncertainty for Monocular Depth Estimation","publication_year":2025,"publication_date":"2025-02-13","ids":{"openalex":"https://openalex.org/W4407450971","doi":"https://doi.org/10.1109/tpami.2025.3541964","pmid":"https://pubmed.ncbi.nlm.nih.gov/40031847"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2025.3541964","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3541964","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":["crossref","pubmed"],"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/A5013391327","display_name":"Julia Hornauer","orcid":"https://orcid.org/0009-0005-8590-2437"},"institutions":[{"id":"https://openalex.org/I196349391","display_name":"Universit\u00e4t Ulm","ror":"https://ror.org/032000t02","country_code":"DE","type":"education","lineage":["https://openalex.org/I196349391"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Julia Hornauer","raw_affiliation_strings":["Ulm University, Ulm, Germany"],"raw_orcid":"https://orcid.org/0009-0005-8590-2437","affiliations":[{"raw_affiliation_string":"Ulm University, Ulm, Germany","institution_ids":["https://openalex.org/I196349391"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5098937108","display_name":"Amir El-Ghoussani","orcid":null},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Amir El-Ghoussani","raw_affiliation_strings":["Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027065196","display_name":"Vasileios Belagiannis","orcid":"https://orcid.org/0000-0003-0960-8453"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Vasileios Belagiannis","raw_affiliation_strings":["Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany"],"raw_orcid":"https://orcid.org/0000-0003-0960-8453","affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.0621,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.90677437,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"47","issue":"6","first_page":"4395","last_page":"4408"},"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":0.9994000196456909,"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":0.9990000128746033,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7055867314338684},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.5759826302528381},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5655543804168701},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5441766977310181},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.49096444249153137},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37446004152297974},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13316887617111206}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7055867314338684},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.5759826302528381},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5655543804168701},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5441766977310181},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.49096444249153137},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37446004152297974},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13316887617111206},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2025.3541964","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3541964","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:40031847","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40031847","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}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","score":0.8299999833106995,"id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W1560021816","https://openalex.org/W2095705004","https://openalex.org/W2115579991","https://openalex.org/W2254249950","https://openalex.org/W2397830550","https://openalex.org/W2520707372","https://openalex.org/W2609883120","https://openalex.org/W2803756472","https://openalex.org/W2887922452","https://openalex.org/W2895192073","https://openalex.org/W2934279571","https://openalex.org/W2955639361","https://openalex.org/W2963316641","https://openalex.org/W2963591054","https://openalex.org/W2964556657","https://openalex.org/W2985775862","https://openalex.org/W3034475171","https://openalex.org/W3081167590","https://openalex.org/W3118453581","https://openalex.org/W3119028141","https://openalex.org/W3173727695","https://openalex.org/W3175528029","https://openalex.org/W3177724741","https://openalex.org/W3188511781","https://openalex.org/W4206198450","https://openalex.org/W4214520160","https://openalex.org/W4312787459","https://openalex.org/W4312819733","https://openalex.org/W4312977443","https://openalex.org/W4313150140","https://openalex.org/W4319300976","https://openalex.org/W4321512633","https://openalex.org/W4390873310","https://openalex.org/W4392402550","https://openalex.org/W4402727359","https://openalex.org/W4402753888","https://openalex.org/W6674330103","https://openalex.org/W6685261749","https://openalex.org/W6730042731","https://openalex.org/W6737496325","https://openalex.org/W6767088534","https://openalex.org/W6767826613","https://openalex.org/W6768698167","https://openalex.org/W6779823529","https://openalex.org/W6784333009","https://openalex.org/W6797359156","https://openalex.org/W6801968024","https://openalex.org/W6802066719","https://openalex.org/W6804122398","https://openalex.org/W6838639034","https://openalex.org/W6839754751","https://openalex.org/W6869729717"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Monocular":[0],"depth":[1,63,89,159],"estimation,":[2],"similar":[3],"to":[4,10,14,38,177],"other":[5],"image-based":[6],"tasks,":[7],"is":[8,33,45,103,147],"prone":[9,176],"erroneous":[11],"predictions":[12],"due":[13],"ambiguities":[15],"in":[16,50,104,149],"the":[17,40,43,72,84,87,122,126,129,151,156],"image,":[18],"for":[19,35,60,167],"example,":[20],"caused":[21],"by":[22],"dynamic":[23],"objects":[24],"or":[25,111,134],"shadows.":[26],"For":[27],"this":[28,49],"reason,":[29],"pixel-wise":[30],"uncertainty":[31,58,124,152],"assessment":[32],"required":[34],"safety-critical":[36],"applications":[37],"highlight":[39],"areas":[41],"where":[42],"prediction":[44],"unreliable.":[46],"We":[47,141],"address":[48],"a":[51,91,108],"post":[52],"hoc":[53],"manner":[54],"and":[55,90,118,163,173],"introduce":[56,77],"gradient-based":[57,145],"estimation":[59,64,160],"already":[61],"trained":[62,169],"models.":[65],"To":[66,120],"extract":[67],"gradients":[68],"without":[69,153],"depending":[70],"on":[71,83],"ground":[73,101],"truth":[74],"depth,":[75,96],"we":[76],"an":[78],"auxiliary":[79],"loss":[80],"function":[81],"based":[82],"consistency":[85],"of":[86],"predicted":[88],"reference":[92,95],"depth.":[93],"The":[94],"which":[97],"acts":[98],"as":[99],"pseudo":[100],"truth,":[102],"fact":[105],"generated":[106],"using":[107,139,155],"simple":[109,117],"image":[110],"feature":[112,130],"augmentation,":[113],"making":[114],"our":[115,144,179],"approach":[116,146],"effective.":[119],"obtain":[121],"final":[123],"score,":[125],"derivatives":[127],"w.r.t.":[128],"maps":[131],"from":[132],"single":[133],"multiple":[135],"layers":[136],"are":[137],"calculated":[138],"back-propagation.":[140],"demonstrate":[142],"that":[143],"effective":[148],"determining":[150],"re-training":[154],"two":[157],"standard":[158],"benchmarks":[161],"KITTI":[162],"NYU.":[164],"In":[165],"particular,":[166],"models":[168],"with":[170],"monocular":[171],"sequences":[172],"therefore":[174],"most":[175],"uncertainty,":[178],"method":[180],"outperforms":[181],"related":[182],"approaches.":[183]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2}],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}