{"id":"https://openalex.org/W4402981125","doi":"https://doi.org/10.1109/icme57554.2024.10687901","title":"InFusionSurf: Refining Neural RGB-D Surface Reconstruction Using Per-Frame Intrinsic Refinement and TSDF Fusion Prior Learning","display_name":"InFusionSurf: Refining Neural RGB-D Surface Reconstruction Using Per-Frame Intrinsic Refinement and TSDF Fusion Prior Learning","publication_year":2024,"publication_date":"2024-07-15","ids":{"openalex":"https://openalex.org/W4402981125","doi":"https://doi.org/10.1109/icme57554.2024.10687901"},"language":"en","primary_location":{"id":"doi:10.1109/icme57554.2024.10687901","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme57554.2024.10687901","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Multimedia and Expo (ICME)","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/A5100410163","display_name":"Seung\u2010Hwan Lee","orcid":"https://orcid.org/0000-0001-8426-975X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Seunghwan Lee","raw_affiliation_strings":["ROKIT Healthcare, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ROKIT Healthcare, Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075724371","display_name":"Gwanmo Park","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gwanmo Park","raw_affiliation_strings":["ROKIT Healthcare, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ROKIT Healthcare, Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078327176","display_name":"Hyewon Son","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hyewon Son","raw_affiliation_strings":["ROKIT Healthcare, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ROKIT Healthcare, Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101483899","display_name":"Jiwon Ryu","orcid":"https://orcid.org/0000-0003-4371-4217"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiwon Ryu","raw_affiliation_strings":["ROKIT Healthcare, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ROKIT Healthcare, Inc","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059932142","display_name":"Han Joo Chae","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han Joo Chae","raw_affiliation_strings":["ROKIT Healthcare, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ROKIT Healthcare, Inc","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3287,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.55245477,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11245","display_name":"Advanced Numerical Analysis Techniques","score":0.9483000040054321,"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"}},"topics":[{"id":"https://openalex.org/T11245","display_name":"Advanced Numerical Analysis Techniques","score":0.9483000040054321,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.9133999943733215,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T10320","display_name":"Neural Networks and Applications","score":0.9071000218391418,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/refining","display_name":"Refining (metallurgy)","score":0.7310982942581177},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.6647635102272034},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6396701335906982},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.605851411819458},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.6017743349075317},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.4954627752304077},{"id":"https://openalex.org/keywords/surface","display_name":"Surface (topology)","score":0.49460503458976746},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49032142758369446},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43124663829803467},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.19571340084075928},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15406811237335205},{"id":"https://openalex.org/keywords/metallurgy","display_name":"Metallurgy","score":0.05775907635688782}],"concepts":[{"id":"https://openalex.org/C60044698","wikidata":"https://www.wikidata.org/wiki/Q1283324","display_name":"Refining (metallurgy)","level":2,"score":0.7310982942581177},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.6647635102272034},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6396701335906982},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.605851411819458},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.6017743349075317},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.4954627752304077},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.49460503458976746},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49032142758369446},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43124663829803467},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.19571340084075928},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15406811237335205},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.05775907635688782},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme57554.2024.10687901","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme57554.2024.10687901","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320311419","display_name":"Ministry of Health","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1987648924","https://openalex.org/W2009422376","https://openalex.org/W2229412420","https://openalex.org/W2336961836","https://openalex.org/W2414946225","https://openalex.org/W2566265240","https://openalex.org/W2594519801","https://openalex.org/W2805202215","https://openalex.org/W2982795046","https://openalex.org/W3134621679","https://openalex.org/W3154129649","https://openalex.org/W3170697543","https://openalex.org/W3215589927","https://openalex.org/W4200150166","https://openalex.org/W4221151978","https://openalex.org/W4293363567","https://openalex.org/W4312969460","https://openalex.org/W4321512716","https://openalex.org/W4386071524","https://openalex.org/W4386075752"],"related_works":["https://openalex.org/W1595345252","https://openalex.org/W2392526918","https://openalex.org/W2362540361","https://openalex.org/W2019560916","https://openalex.org/W2361983698","https://openalex.org/W2347697528","https://openalex.org/W2354123794","https://openalex.org/W2372508235","https://openalex.org/W2560036917","https://openalex.org/W2349506406"],"abstract_inverted_index":{"We":[0],"introduce":[1],"InFusionSurf,":[2],"an":[3,125],"innovative":[4],"enhancement":[5],"for":[6,84],"neural":[7],"radiance":[8],"field":[9,70],"(NeRF)":[10],"frameworks":[11],"in":[12,54],"3D":[13,76],"surface":[14,77],"reconstruction":[15,37,78,89],"using":[16],"RGB-D":[17],"video":[18],"frames.":[19],"Building":[20],"upon":[21],"previous":[22],"methods":[23],"that":[24,100],"have":[25],"employed":[26],"feature":[27,86],"encoding":[28],"to":[29],"improve":[30,35],"optimization":[31,43,109],"speed,":[32],"we":[33],"further":[34,122],"the":[36,66,85],"quality":[38],"with":[39,104],"minimal":[40],"impact":[41],"on":[42],"time":[44],"by":[45],"refining":[46],"depth":[47,56],"information.":[48],"InFusionSurf":[49,101],"addresses":[50],"camera":[51],"motion-induced":[52],"blurs":[53],"each":[55],"frame":[57],"through":[58,124],"a":[59,73,81],"per-frame":[60],"intrinsic":[61,115],"refinement":[62,116],"scheme.":[63],"It":[64],"incorporates":[65],"truncated":[67],"signed":[68],"distance":[69],"(TSDF)":[71],"Fusion,":[72],"classical":[74],"real-time":[75],"method,":[79],"as":[80],"pretraining":[82,120],"tool":[83],"grid,":[87],"enhancing":[88],"details":[90],"and":[91,96,117],"training":[92],"speed.":[93],"Comparative":[94],"quantitative":[95],"qualitative":[97],"analyses":[98],"show":[99],"reconstructs":[102],"scenes":[103],"high":[105],"accuracy":[106],"while":[107],"maintaining":[108],"efficiency.":[110],"The":[111],"effectiveness":[112],"of":[113],"our":[114],"TSDF":[118],"Fusion-based":[119],"is":[121],"validated":[123],"ablation":[126],"study.":[127]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2024-10-01T00:00:00"}
