{"id":"https://openalex.org/W4415102149","doi":"https://doi.org/10.1109/iccv51701.2025.02411","title":"Noise2Score3D: Tweedie's Approach for Unsupervised Point Cloud Denoising","display_name":"Noise2Score3D: Tweedie's Approach for Unsupervised Point Cloud Denoising","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4415102149","doi":"https://doi.org/10.1109/iccv51701.2025.02411"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51701.2025.02411","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.02411","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2503.09283","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Xiangbin Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiangbin Wei","raw_affiliation_strings":["Shenzhen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen University","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100635366","display_name":"Yuanfeng Wang","orcid":"https://orcid.org/0000-0003-3743-4008"},"institutions":[{"id":"https://openalex.org/I4400600918","display_name":"Quantum Science Center of Guangdong-Hong Kong-Macao Greater Bay Area","ror":"https://ror.org/03qb6k992","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4400600918"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanfeng Wang","raw_affiliation_strings":["Quantum Science Center of Guangdong-Hong Kong-Macao Greater Bay Area"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Quantum Science Center of Guangdong-Hong Kong-Macao Greater Bay Area","institution_ids":["https://openalex.org/I4400600918"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011867852","display_name":"Ao Xu","orcid":"https://orcid.org/0000-0002-9939-2010"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ao Xu","raw_affiliation_strings":["Research Institute of Tsinghua University in Shenzhen"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Institute of Tsinghua University in Shenzhen","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058047174","display_name":"Lingyun Zhu","orcid":"https://orcid.org/0000-0001-7391-1866"},"institutions":[{"id":"https://openalex.org/I4210153682","display_name":"Intelligent Health (United Kingdom)","ror":"https://ror.org/0576zak10","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210153682"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Lingyu Zhu","raw_affiliation_strings":["YunJi Intelligent Engineering Co., Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"YunJi Intelligent Engineering Co., Ltd","institution_ids":["https://openalex.org/I4210153682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034640711","display_name":"Dongxian Sun","orcid":"https://orcid.org/0000-0002-4654-3487"},"institutions":[{"id":"https://openalex.org/I4210153682","display_name":"Intelligent Health (United Kingdom)","ror":"https://ror.org/0576zak10","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210153682"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Dongyong Sun","raw_affiliation_strings":["YunJi Intelligent Engineering Co., Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"YunJi Intelligent Engineering Co., Ltd","institution_ids":["https://openalex.org/I4210153682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076320945","display_name":"Keren Li","orcid":"https://orcid.org/0000-0001-5559-0421"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Keren Li","raw_affiliation_strings":["Shenzhen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen University","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100421802","display_name":"Yang Li","orcid":"https://orcid.org/0000-0003-4022-7341"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Li","raw_affiliation_strings":["Nanjing University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018928091","display_name":"Qi Qin","orcid":"https://orcid.org/0000-0002-3019-2061"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Qin","raw_affiliation_strings":["Shenzhen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen University","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28142594,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"25993","last_page":"26003"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9934999942779541,"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":0.9934999942779541,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9916999936103821,"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":0.9901999831199646,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.659600019454956},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.652999997138977},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.609000027179718},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5648000240325928},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.5504999756813049},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5130000114440918},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4235999882221222},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.37549999356269836}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6672999858856201},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.659600019454956},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.652999997138977},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.609000027179718},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6025000214576721},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5648000240325928},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.5504999756813049},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5130000114440918},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4235999882221222},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40290001034736633},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.37549999356269836},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3709999918937683},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.35679998993873596},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.32190001010894775},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.305400013923645},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2872999906539917},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.2815000116825104},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.27489998936653137},{"id":"https://openalex.org/C30814859","wikidata":"https://www.wikidata.org/wiki/Q4119603","display_name":"Video denoising","level":5,"score":0.27090001106262207},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.26649999618530273},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.26350000500679016},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.2515000104904175}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv51701.2025.02411","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.02411","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2503.09283","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2503.09283","pdf_url":"https://arxiv.org/pdf/2503.09283","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2503.09283","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2503.09283","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2503.09283","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2503.09283","pdf_url":"https://arxiv.org/pdf/2503.09283","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Building":[0],"on":[1,100],"recent":[2],"advances":[3],"in":[4,51,60,107,137,149],"Bayesian":[5],"statistics":[6],"and":[7,68,110,129],"image":[8],"denoising,":[9],"we":[10,71],"propose":[11],"Noise2Score3D,":[12],"a":[13,52,79],"fully":[14],"unsupervised":[15,62,104],"framework":[16],"for":[17,39,75,85,143],"point":[18,29,145],"cloud":[19,30,146],"denoising.":[20],"Noise2Score3D":[21,96,113],"learns":[22],"the":[23,27,37,56,86,126,132,141],"score":[24],"function":[25],"of":[26,88,131,134],"underlying":[28],"distribution":[31],"directly":[32],"from":[33],"noisy":[34],"data,":[35],"eliminating":[36],"need":[38],"clean":[40,135],"data":[41,136],"during":[42],"training.":[43],"Using":[44],"Tweedie's":[45],"formula,":[46],"our":[47],"method":[48],"performs":[49],"denoising":[50,80,147],"single":[53],"step,":[54],"avoiding":[55],"iterative":[57],"processes":[58],"used":[59],"existing":[61],"methods,":[63,139],"thus":[64],"improving":[65],"both":[66],"accuracy":[67],"efficiency.":[69],"Additionally,":[70],"introduce":[72],"Total":[73],"Variation":[74],"Point":[76],"Clouds":[77],"as":[78],"quality":[81],"metric,":[82],"which":[83],"allows":[84],"estimation":[87],"unknown":[89],"noise":[90],"parameters.":[91],"Experimental":[92],"results":[93],"demonstrate":[94],"that":[95],"achieves":[97],"state-of-the-art":[98],"performance":[99],"standard":[101],"benchmarks":[102],"among":[103],"learning":[105],"methods":[106,148],"Chamfer":[108],"distance":[109],"point-to-mesh":[111],"metrics.":[112],"also":[114],"demonstrates":[115],"strong":[116],"generalization":[117,127],"ability":[118],"beyond":[119],"training":[120],"datasets.":[121],"Our":[122],"method,":[123],"by":[124],"addressing":[125],"issue":[128],"challenge":[130],"absence":[133],"learning-based":[138,144],"paves":[140],"way":[142],"real-world":[150],"applications.":[151]},"counts_by_year":[],"updated_date":"2026-05-06T06:03:25.996018","created_date":"2025-10-13T00:00:00"}