{"id":"https://openalex.org/W3133010999","doi":"https://doi.org/10.5220/0010226409010909","title":"Learning to Correct Reconstructions from Multiple Views","display_name":"Learning to Correct Reconstructions from Multiple Views","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3133010999","doi":"https://doi.org/10.5220/0010226409010909","mag":"3133010999"},"language":"en","primary_location":{"id":"doi:10.5220/0010226409010909","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0010226409010909","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.5220/0010226409010909","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005382900","display_name":"\u015etefan S\u0103ftescu","orcid":"https://orcid.org/0000-0002-9414-5571"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"\u0218tefan S\u0103ftescu","raw_affiliation_strings":["Oxford Robotics Institute, University of Oxford, U.K., --- Select a Country ---"],"affiliations":[{"raw_affiliation_string":"Oxford Robotics Institute, University of Oxford, U.K., --- Select a Country ---","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055299977","display_name":"Paul Newman","orcid":"https://orcid.org/0000-0001-6562-8454"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Paul Newman","raw_affiliation_strings":["Oxford Robotics Institute, University of Oxford, U.K., --- Select a Country ---"],"affiliations":[{"raw_affiliation_string":"Oxford Robotics Institute, University of Oxford, U.K., --- Select a Country ---","institution_ids":["https://openalex.org/I40120149"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5005382900"],"corresponding_institution_ids":["https://openalex.org/I40120149"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02047386,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"901","last_page":"909"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9990000128746033,"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":0.9990000128746033,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9821000099182129,"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":0.780053436756134},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6896361708641052},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6376111507415771},{"id":"https://openalex.org/keywords/image-warping","display_name":"Image warping","score":0.6332485675811768},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5994876623153687},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5839086174964905},{"id":"https://openalex.org/keywords/complement","display_name":"Complement (music)","score":0.5555873513221741},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.45178186893463135},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.43966230750083923},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42104193568229675},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3871602714061737},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38179025053977966},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.28154778480529785}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.780053436756134},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6896361708641052},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6376111507415771},{"id":"https://openalex.org/C157202957","wikidata":"https://www.wikidata.org/wiki/Q1659609","display_name":"Image warping","level":2,"score":0.6332485675811768},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5994876623153687},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5839086174964905},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.5555873513221741},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.45178186893463135},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.43966230750083923},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42104193568229675},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3871602714061737},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38179025053977966},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28154778480529785},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C188082640","wikidata":"https://www.wikidata.org/wiki/Q1780899","display_name":"Complementation","level":4,"score":0.0},{"id":"https://openalex.org/C127716648","wikidata":"https://www.wikidata.org/wiki/Q104053","display_name":"Phenotype","level":3,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5220/0010226409010909","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0010226409010909","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.5220/0010226409010909","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0010226409010909","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.8100000023841858}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1670332068","https://openalex.org/W2095618524","https://openalex.org/W2735770592","https://openalex.org/W1971024059","https://openalex.org/W1502062143","https://openalex.org/W4224236531","https://openalex.org/W4291993329","https://openalex.org/W2063177452","https://openalex.org/W2413982977","https://openalex.org/W2369637271"],"abstract_inverted_index":{"This":[0,114],"paper":[1],"is":[2,115,171],"about":[3],"reducing":[4],"the":[5,38,46,51,83,131,136,157],"cost":[6],"of":[7,18,63,110],"building":[8],"good":[9],"large-scale":[10],"3D":[11,127],"reconstructions":[12],"post-hoc.":[13],"We":[14,60,129],"render":[15],"2D":[16],"views":[17,39,56,80,112,122],"an":[19],"existing":[20],"reconstruction":[21],"and":[22,86,123,141],"train":[23],"a":[24,34,71,143,153],"convolutional":[25],"neural":[26],"network":[27],"(CNN)":[28],"that":[29,40,64,133,167],"refines":[30],"inverse-depth":[31],"to":[32,81,90,96],"match":[33],"higher-quality":[35],"reconstruction.":[36],"Since":[37],"we":[41,69,104,165],"correct":[42],"are":[43,139],"rendered":[44],"from":[45,156],"same":[47,52,84],"reconstruction,":[48],"they":[49],"share":[50],"geometry,":[53],"so":[54],"overlapping":[55],"complement":[57],"each":[58,101],"other.":[59],"take":[61],"advantage":[62],"in":[65,94,135],"two":[66],"ways.":[67],"Firstly,":[68],"impose":[70],"loss":[72],"during":[73],"training":[74],"which":[75,99],"guides":[76],"predictions":[77,107],"on":[78,108],"neighbouring":[79,111],"have":[82],"geometry":[85],"has":[87],"been":[88],"shown":[89],"improve":[91],"performance.":[92],"Secondly,":[93],"contrast":[95],"previous":[97],"work,":[98],"corrects":[100],"view":[102],"independently,":[103],"also":[105],"make":[106,130],"sets":[109],"jointly.":[113],"achieved":[116],"by":[117,152],"warping":[118],"feature":[119,137,176],"maps":[120,138,177],"between":[121,160,178],"thus":[124],"bypassing":[125],"memory-intensive":[126],"computation.":[128],"observation":[132],"features":[134,147],"viewpoint-dependent,":[140],"propose":[142],"method":[144],"for":[145,173],"transforming":[146],"with":[148],"dynamic":[149],"filters":[150],"generated":[151],"multi-layer":[154],"perceptron":[155],"relative":[158],"poses":[159],"views.":[161,179],"In":[162],"our":[163],"experiments":[164],"show":[166],"this":[168],"last":[169],"step":[170],"necessary":[172],"successfully":[174],"fusing":[175]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
