{"id":"https://openalex.org/W4417281296","doi":"https://doi.org/10.1109/iccv51701.2025.02327","title":"RI3D: Few-Shot Gaussian Splatting with Repair and Inpainting Diffusion Priors","display_name":"RI3D: Few-Shot Gaussian Splatting with Repair and Inpainting Diffusion Priors","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4417281296","doi":"https://doi.org/10.1109/iccv51701.2025.02327"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51701.2025.02327","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.02327","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/2503.10860","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006402988","display_name":"Avinash Paliwal","orcid":"https://orcid.org/0000-0002-9090-6142"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Avinash Paliwal","raw_affiliation_strings":["Texas A&M University,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Texas A&M University,USA","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018391842","display_name":"Xilong Zhou","orcid":"https://orcid.org/0000-0002-8964-5854"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xilong Zhou","raw_affiliation_strings":["Texas A&M University,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Texas A&M University,USA","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100448687","display_name":"Wei Ye","orcid":"https://orcid.org/0000-0002-3514-1626"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Ye","raw_affiliation_strings":["Meta Reality Labs,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meta Reality Labs,USA","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074593436","display_name":"Jinhui Xiong","orcid":"https://orcid.org/0000-0002-1507-6070"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jinhui Xiong","raw_affiliation_strings":["Meta Reality Labs,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meta Reality Labs,USA","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101970448","display_name":"Rakesh Ranjan","orcid":"https://orcid.org/0000-0003-3317-8473"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rakesh Ranjan","raw_affiliation_strings":["Meta Reality Labs,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meta Reality Labs,USA","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008433002","display_name":"Nima Khademi Kalantari","orcid":"https://orcid.org/0000-0002-2588-9219"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nima Khademi Kalantari","raw_affiliation_strings":["Texas A&M University,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Texas A&M University,USA","institution_ids":["https://openalex.org/I91045830"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5006402988"],"corresponding_institution_ids":["https://openalex.org/I91045830"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37939708,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"25094","last_page":"25103"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.5503000020980835,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.5503000020980835,"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/T11019","display_name":"Image Enhancement Techniques","score":0.12620000541210175,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.12139999866485596,"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/inpainting","display_name":"Inpainting","score":0.9172999858856201},{"id":"https://openalex.org/keywords/hallucinating","display_name":"Hallucinating","score":0.838699996471405},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.6588000059127808},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.6018999814987183},{"id":"https://openalex.org/keywords/filling-in","display_name":"Filling-in","score":0.48969998955726624},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4542999863624573},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.421099990606308},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.42080000042915344},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4140999913215637}],"concepts":[{"id":"https://openalex.org/C11727466","wikidata":"https://www.wikidata.org/wiki/Q1628157","display_name":"Inpainting","level":3,"score":0.9172999858856201},{"id":"https://openalex.org/C2911011789","wikidata":"https://www.wikidata.org/wiki/Q130741","display_name":"Hallucinating","level":2,"score":0.838699996471405},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6969000101089478},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6736999750137329},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.6588000059127808},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.6018999814987183},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49219998717308044},{"id":"https://openalex.org/C200873422","wikidata":"https://www.wikidata.org/wiki/Q5448821","display_name":"Filling-in","level":2,"score":0.48969998955726624},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4542999863624573},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.421099990606308},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.42080000042915344},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4140999913215637},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.41260001063346863},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40389999747276306},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.3982999920845032},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.38190001249313354},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.37619999051094055},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3732999861240387},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.34790000319480896},{"id":"https://openalex.org/C50494287","wikidata":"https://www.wikidata.org/wiki/Q658467","display_name":"Texture synthesis","level":5,"score":0.3411000072956085},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3231000006198883},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.3102000057697296},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2962000072002411},{"id":"https://openalex.org/C129315195","wikidata":"https://www.wikidata.org/wiki/Q1121886","display_name":"Compositing","level":3,"score":0.29429998993873596},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.29350000619888306},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2791000008583069},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.27619999647140503},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.2590000033378601},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.2533000111579895},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.25049999356269836}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv51701.2025.02327","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.02327","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:2503.10860","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2503.10860","pdf_url":"https://arxiv.org/pdf/2503.10860","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.2503.10860","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2503.10860","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2503.10860","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2503.10860","pdf_url":"https://arxiv.org/pdf/2503.10860","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":[{"id":"https://openalex.org/F4320334350","display_name":"High Performance Research Computing, Texas A and M University","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,110,144,188],"propose":[4],"RI3D,":[5],"a":[6,23,67,84,112,149,205],"novel":[7,20,150],"3DGS-based":[8],"approach":[9],"that":[10,154,171,200],"harnesses":[11],"the":[12,34,74,91,116,123,127,134,146,174,183],"power":[13],"of":[14,26,41,59,208],"diffusion":[15,53],"models":[16,108],"to":[17,57,89],"reconstruct":[18],"high-quality":[19,76],"views":[21],"given":[22],"sparse":[24,212],"set":[25,207],"input":[27,71],"images.":[28],"Our":[29],"key":[30],"contribution":[31],"is":[32,81],"separating":[33,173],"view":[35],"synthesis":[36],"process":[37,175],"into":[38,176],"two":[39,51,177],"tasks":[40,178],"reconstructing":[42],"visible":[43,120,196],"regions":[44,132,199],"and":[45,49,72,126,161,179,185,197],"hallucinating":[46,100],"missing":[47,131,198],"regions,":[48],"introducing":[50],"personalized":[52],"models,":[54,187],"each":[55],"tailored":[56],"one":[58,63],"these":[60,107],"tasks.":[61],"Specifically,":[62],"model":[64,95,136],"('repair')":[65],"takes":[66],"rendered":[68],"image":[69,88],"as":[70,83],"predicts":[73],"corresponding":[75],"image,":[77],"which":[78],"in":[79,102,194],"turn":[80],"used":[82],"pseudo":[85],"ground":[86],"truth":[87],"constrain":[90],"optimization.":[92,142],"The":[93],"other":[94],"('inpainting')":[96],"primarily":[97],"focuses":[98],"on":[99,204],"details":[101],"unobserved":[103],"areas.":[104],"To":[105],"integrate":[106],"effectively,":[109],"introduce":[111],"two-stage":[113],"optimization":[114,147],"strategy:":[115],"first":[117],"stage":[118,129],"reconstructs":[119,130],"areas":[121],"using":[122],"repair":[124,184],"model,":[125],"second":[128],"with":[133,148,164,182,191,210],"inpainting":[135,186],"while":[137],"ensuring":[138],"coherence":[139],"through":[140],"further":[141],"Moreover,":[143],"augment":[145],"Gaussian":[151],"initialization":[152],"method":[153],"obtains":[155],"per-image":[156],"depth":[157,163],"by":[158,172],"combining":[159],"3D-consistent":[160],"smooth":[162],"highly":[165],"detailed":[166,192],"relative":[167],"depth.":[168],"We":[169],"demonstrate":[170],"addressing":[180],"them":[181],"produce":[189],"results":[190],"textures":[193],"both":[195],"outperform":[201],"state-of-the-art":[202],"approaches":[203],"diverse":[206],"scenes":[209],"extremely":[211],"inputs.":[213]},"counts_by_year":[],"updated_date":"2026-05-06T06:03:25.996018","created_date":"2025-10-10T00:00:00"}