{"id":"https://openalex.org/W4386075857","doi":"https://doi.org/10.1109/cvpr52729.2023.00818","title":"PermutoSDF: Fast Multi-View Reconstruction with Implicit Surfaces Using Permutohedral Lattices","display_name":"PermutoSDF: Fast Multi-View Reconstruction with Implicit Surfaces Using Permutohedral Lattices","publication_year":2023,"publication_date":"2023-06-01","ids":{"openalex":"https://openalex.org/W4386075857","doi":"https://doi.org/10.1109/cvpr52729.2023.00818"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr52729.2023.00818","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52729.2023.00818","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-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/A5008612683","display_name":"Radu Alexandru Ro\u015fu","orcid":"https://orcid.org/0000-0001-7349-4126"},"institutions":[{"id":"https://openalex.org/I135140700","display_name":"University of Bonn","ror":"https://ror.org/041nas322","country_code":"DE","type":"education","lineage":["https://openalex.org/I135140700"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Radu Alexandru Rosu","raw_affiliation_strings":["University of Bonn,Germany","University of Bonn, Germany"],"affiliations":[{"raw_affiliation_string":"University of Bonn,Germany","institution_ids":["https://openalex.org/I135140700"]},{"raw_affiliation_string":"University of Bonn, Germany","institution_ids":["https://openalex.org/I135140700"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027761977","display_name":"Sven Behnke","orcid":"https://orcid.org/0000-0002-5040-7525"},"institutions":[{"id":"https://openalex.org/I135140700","display_name":"University of Bonn","ror":"https://ror.org/041nas322","country_code":"DE","type":"education","lineage":["https://openalex.org/I135140700"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sven Behnke","raw_affiliation_strings":["University of Bonn,Germany","University of Bonn, Germany"],"affiliations":[{"raw_affiliation_string":"University of Bonn,Germany","institution_ids":["https://openalex.org/I135140700"]},{"raw_affiliation_string":"University of Bonn, Germany","institution_ids":["https://openalex.org/I135140700"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5008612683"],"corresponding_institution_ids":["https://openalex.org/I135140700"],"apc_list":null,"apc_paid":null,"fwci":7.7222,"has_fulltext":false,"cited_by_count":63,"citation_normalized_percentile":{"value":0.98255775,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"8466","last_page":"8475"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9995999932289124,"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":0.9995999932289124,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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":0.8229084014892578},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.6222326755523682},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.6076181530952454},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.5485122203826904},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.49828672409057617},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49547278881073},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4472000002861023},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4032911956310272},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3963453769683838},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3628005385398865}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8229084014892578},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.6222326755523682},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.6076181530952454},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.5485122203826904},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.49828672409057617},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49547278881073},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4472000002861023},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4032911956310272},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3963453769683838},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3628005385398865},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr52729.2023.00818","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52729.2023.00818","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6600000262260437,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G3964146033","display_name":null,"funder_award_id":"EXC 2070 - 390732324","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1964772475","https://openalex.org/W1987648924","https://openalex.org/W2008073424","https://openalex.org/W2009422376","https://openalex.org/W2071906076","https://openalex.org/W2085905957","https://openalex.org/W2112174119","https://openalex.org/W2129404737","https://openalex.org/W2205172244","https://openalex.org/W2519683295","https://openalex.org/W2527142681","https://openalex.org/W2618017917","https://openalex.org/W2785678896","https://openalex.org/W2996461983","https://openalex.org/W2997863059","https://openalex.org/W3034964128","https://openalex.org/W3034968345","https://openalex.org/W3092203888","https://openalex.org/W3092948912","https://openalex.org/W3129567753","https://openalex.org/W3153220274","https://openalex.org/W3202037070","https://openalex.org/W3203570626","https://openalex.org/W3213840695","https://openalex.org/W3215589927","https://openalex.org/W4200150166","https://openalex.org/W4221151978","https://openalex.org/W4233857083","https://openalex.org/W4285965606","https://openalex.org/W4287114999","https://openalex.org/W4287756134","https://openalex.org/W4288043288","https://openalex.org/W4297812694","https://openalex.org/W4300167250","https://openalex.org/W4312280420","https://openalex.org/W4312325284","https://openalex.org/W6652231383","https://openalex.org/W6736987314","https://openalex.org/W6738248287","https://openalex.org/W6748582592","https://openalex.org/W6779753539","https://openalex.org/W6781421651","https://openalex.org/W6784492152","https://openalex.org/W6784729325","https://openalex.org/W6797770180","https://openalex.org/W6798033281","https://openalex.org/W6841454795"],"related_works":["https://openalex.org/W3027020613","https://openalex.org/W2016533837","https://openalex.org/W3167885074","https://openalex.org/W2892386716","https://openalex.org/W1998563493","https://openalex.org/W4306164210","https://openalex.org/W4313316311","https://openalex.org/W4362608745","https://openalex.org/W2383143032","https://openalex.org/W2148204638"],"abstract_inverted_index":{"Neural":[0],"radiance-density":[1],"field":[2],"methods":[3,32,40,56],"have":[4],"become":[5],"increasingly":[6],"popular":[7],"for":[8,106,118,150],"the":[9,46,70,89,94,139],"task":[10],"of":[11,72,76,141],"novel-view":[12],"rendering.":[13],"Their":[14],"recent":[15],"extension":[16],"to":[17,88],"hash-based":[18,81],"positional":[19],"encoding":[20,97],"ensures":[21],"fast":[22],"training":[23],"and":[24,60,130,143],"inference":[25],"with":[26,34,98],"visually":[27],"pleasing":[28],"results.":[29],"However,":[30,53],"density-based":[31],"struggle":[33],"recovering":[35,119],"accurate":[36],"surface":[37,83],"geometry.":[38],"Hybrid":[39],"alleviate":[41],"this":[42,66],"issue":[43],"by":[44,92],"optimizing":[45],"density":[47],"based":[48],"on":[49,127,164],"an":[50,165],"underlying":[51],"SDF.":[52],"current":[54],"SDF":[55],"are":[57],"overly":[58],"smooth":[59],"miss":[61],"fine":[62],"geometric":[63,121,136],"details.":[64],"In":[65],"work,":[67],"we":[68,133,156],"combine":[69],"strengths":[71],"these":[73],"two":[74,90],"lines":[75],"work":[77],"in":[78],"a":[79,99,112],"novel":[80,159],"implicit":[82],"representation.":[84],"We":[85,109,123],"propose":[86,111],"improvements":[87],"areas":[91],"replacing":[93],"voxel":[95],"hash":[96],"permutohedral":[100],"lattice":[101],"which":[102,115],"optimizes":[103],"faster,":[104],"especially":[105],"higher":[107],"dimensions.":[108],"additionally":[110],"regularization":[113],"scheme":[114],"is":[116,169],"crucial":[117],"high-frequency":[120],"detail.":[122],"evaluate":[124],"our":[125],"method":[126],"multiple":[128],"datasets":[129],"show":[131],"that":[132],"can":[134,157],"recover":[135],"detail":[137],"at":[138,161,172],"level":[140],"pores":[142],"wrinkles":[144],"while":[145],"using":[146,153],"only":[147],"RGB":[148],"images":[149],"supervision.":[151],"Furthermore,":[152],"sphere":[154],"tracing":[155],"render":[158],"views":[160],"30":[162],"fps":[163],"RTX":[166],"3090.":[167],"Code":[168],"publicly":[170],"available":[171],"https://radualexandru.github.io/permuto_sdf.":[173]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":21},{"year":2024,"cited_by_count":28},{"year":2023,"cited_by_count":12}],"updated_date":"2026-02-27T16:54:17.756197","created_date":"2025-10-10T00:00:00"}