{"id":"https://openalex.org/W4416250540","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227741","title":"ELFSurf: Explicit Latent Fusion for Implicit Surface Reconstruction","display_name":"ELFSurf: Explicit Latent Fusion for Implicit Surface Reconstruction","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416250540","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227741"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11227741","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227741","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5102482824","display_name":"Jijun Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jijun Zhou","raw_affiliation_strings":["South China University of Technology,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China University of Technology,Guangzhou,China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102272379","display_name":"Zhuhua Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210133882","display_name":"China Railway Construction Corporation (China)","ror":"https://ror.org/03gyssm79","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210133882"]},{"id":"https://openalex.org/I4210135994","display_name":"China Railway Group (China)","ror":"https://ror.org/03za3eq42","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210135994"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuhua Yang","raw_affiliation_strings":["China Railway Liuyuan Group Co., Ltd.,Tianjin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Railway Liuyuan Group Co., Ltd.,Tianjin,China","institution_ids":["https://openalex.org/I4210135994","https://openalex.org/I4210133882"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101388173","display_name":"Lingyu Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingyu Liang","raw_affiliation_strings":["South China University of Technology,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China University of Technology,Guangzhou,China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100610537","display_name":"Chi Zhang","orcid":"https://orcid.org/0000-0001-8409-1189"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chi Zhang","raw_affiliation_strings":["South China University of Technology,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China University of Technology,Guangzhou,China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109149768","display_name":"Yutian Yang","orcid":"https://orcid.org/0009-0004-3809-6973"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yutian Yang","raw_affiliation_strings":["South China University of Technology,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China University of Technology,Guangzhou,China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100563672","display_name":"Yong Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Xu","raw_affiliation_strings":["South China University of Technology,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China University of Technology,Guangzhou,China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9715999960899353,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9715999960899353,"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":0.007499999832361937,"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"}},{"id":"https://openalex.org/T11245","display_name":"Advanced Numerical Analysis Techniques","score":0.005900000222027302,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6294999718666077},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.5760999917984009},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.5590999722480774},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.5407999753952026},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.49619999527931213},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47940000891685486},{"id":"https://openalex.org/keywords/surface-reconstruction","display_name":"Surface reconstruction","score":0.4480000138282776},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4408999979496002},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.40939998626708984}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6294999718666077},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6053000092506409},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.5760999917984009},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.5590999722480774},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.5407999753952026},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5313000082969666},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5238999724388123},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.49619999527931213},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47940000891685486},{"id":"https://openalex.org/C20885615","wikidata":"https://www.wikidata.org/wiki/Q825595","display_name":"Surface reconstruction","level":3,"score":0.4480000138282776},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4408999979496002},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.40939998626708984},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40709999203681946},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4068000018596649},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.396699994802475},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3930000066757202},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.35839998722076416},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.3230000138282776},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.322299987077713},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.30649998784065247},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.30559998750686646},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.2987000048160553},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2849000096321106},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.27720001339912415},{"id":"https://openalex.org/C43173174","wikidata":"https://www.wikidata.org/wiki/Q2646942","display_name":"Regular grid","level":3,"score":0.2759999930858612},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.27140000462532043},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11227741","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227741","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1992642990","https://openalex.org/W2121535648","https://openalex.org/W2464708700","https://openalex.org/W2905288042","https://openalex.org/W2963627347","https://openalex.org/W2963926543","https://openalex.org/W2972931660","https://openalex.org/W2973014570","https://openalex.org/W3028314732","https://openalex.org/W3034395814","https://openalex.org/W3034961469","https://openalex.org/W3035515538","https://openalex.org/W3044134703","https://openalex.org/W3095682719","https://openalex.org/W3117476483","https://openalex.org/W3119331429","https://openalex.org/W3119816767","https://openalex.org/W3197617697","https://openalex.org/W4224434530","https://openalex.org/W4233857083","https://openalex.org/W4312597904","https://openalex.org/W4386076147","https://openalex.org/W4386076153","https://openalex.org/W4390827909","https://openalex.org/W4393149117"],"related_works":[],"abstract_inverted_index":{"Implicit":[0],"neural":[1],"networks":[2],"are":[3,50,59,75,81,87,139],"widely":[4],"used":[5],"to":[6,16,94,109,155,162,173,198],"reconstruct":[7],"3D":[8,116,186],"surfaces":[9],"from":[10],"noisy":[11],"point":[12,25,33,65,129],"clouds.":[13],"In":[14,71,92,146],"order":[15,93],"construct":[17],"accurate":[18,115,185],"implicit":[19],"fields,":[20],"existing":[21],"methods":[22],"encode":[23],"input":[24],"clouds":[26],"into":[27],"either":[28],"feature":[29,125],"vectors":[30,126],"for":[31,52,113,127],"each":[32,128],"(point":[34],"latents)":[35],"or":[36],"regular":[37],"grid":[38,73,137],"features":[39,48,138,161,172],"(grid":[40],"latents).":[41],"Point":[42,132],"latents":[43,74],"can":[44,182],"capture":[45],"higher":[46],"frequency":[47],"and":[49,64,77,90,157,191],"good":[51],"detailed":[53],"reconstruction.":[54,70],"However,":[55],"the":[56,84,124,159,164,171,199],"reconstruction":[57,85,188],"results":[58,86],"easily":[60],"affected":[61],"by":[62,130,141],"noise":[63],"distribution,":[66],"resulting":[67],"in":[68],"incomplete":[69],"contrast,":[72],"coarser":[76],"therefore":[78],"some":[79],"details":[80],"lost,":[82],"but":[83],"more":[88,114,184],"complete":[89],"smoother.":[91],"make":[95],"full":[96],"use":[97],"of":[98,102],"these":[99],"two":[100],"types":[101],"latents,":[103],"we":[104,148],"propose":[105],"a":[106,150],"new":[107],"method":[108,181],"explicit":[110],"fuse":[111,158],"them":[112],"surface":[117,187],"reconstruction,":[118],"called":[119],"ELFSurf.":[120],"Specifically,":[121],"ELFSurf":[122],"obtains":[123],"our":[131,180],"Convolution":[133],"Module":[134,144,153],"(PCM).":[135],"The":[136,167,176],"obtained":[140],"Grid":[142],"Transformer":[143],"(GTM).":[145],"addition,":[147],"design":[149],"Sparse":[151],"Decoding":[152],"(SDM)":[154],"sparsify":[156],"extracted":[160],"improve":[163],"decoding":[165],"performance.":[166],"decoder":[168],"finally":[169],"maps":[170],"occupancy":[174],"probabilities.":[175],"experiments":[177],"demonstrate":[178],"that":[179],"achieve":[183],"on":[189],"object-level":[190],"scene-level":[192],"datasets":[193],"with":[194],"better":[195],"generalization":[196],"compared":[197],"state-of-the-art":[200],"approaches.":[201]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-14T00:00:00"}
