{"id":"https://openalex.org/W7148532796","doi":"https://doi.org/10.48550/arxiv.2604.01030","title":"Diff3R: Feed-forward 3D Gaussian Splatting with Uncertainty-aware Differentiable Optimization","display_name":"Diff3R: Feed-forward 3D Gaussian Splatting with Uncertainty-aware Differentiable Optimization","publication_year":2026,"publication_date":"2026-04-01","ids":{"openalex":"https://openalex.org/W7148532796","doi":"https://doi.org/10.48550/arxiv.2604.01030"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.01030","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01030","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":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.01030","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090502979","display_name":"Yueh-Cheng Liu","orcid":"https://orcid.org/0000-0002-8053-9801"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Liu, Yueh-Cheng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132823461","display_name":"Jozef Hladk\u00fd","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hladk\u00fd, Jozef","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132828510","display_name":"Matthias Nie\u00dfner","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nie\u00dfner, Matthias","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5026634347","display_name":"Angela Dai","orcid":"https://orcid.org/0000-0002-6241-8782"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dai, Angela","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5090502979"],"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.29490000009536743,"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":0.29490000009536743,"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":0.17030000686645508,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.1354999989271164,"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/initialization","display_name":"Initialization","score":0.5989999771118164},{"id":"https://openalex.org/keywords/solver","display_name":"Solver","score":0.5630000233650208},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5572999715805054},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.5342000126838684},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4964999854564667},{"id":"https://openalex.org/keywords/differentiable-function","display_name":"Differentiable function","score":0.460099995136261},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.42590001225471497},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.41280001401901245},{"id":"https://openalex.org/keywords/robust-optimization","display_name":"Robust optimization","score":0.40230000019073486},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.3919999897480011}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7921000123023987},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.5989999771118164},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.5630000233650208},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5572999715805054},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5479000210762024},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.5342000126838684},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4964999854564667},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.460099995136261},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45910000801086426},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.42590001225471497},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.41280001401901245},{"id":"https://openalex.org/C193254401","wikidata":"https://www.wikidata.org/wiki/Q2160088","display_name":"Robust optimization","level":2,"score":0.40230000019073486},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.3919999897480011},{"id":"https://openalex.org/C177179195","wikidata":"https://www.wikidata.org/wiki/Q7268372","display_name":"Quadratic unconstrained binary optimization","level":4,"score":0.36820000410079956},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.366100013256073},{"id":"https://openalex.org/C2989514635","wikidata":"https://www.wikidata.org/wiki/Q5164377","display_name":"Constrained optimization problem","level":3,"score":0.3621000051498413},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3449999988079071},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.337799996137619},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.33009999990463257},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3264000117778778},{"id":"https://openalex.org/C164155591","wikidata":"https://www.wikidata.org/wiki/Q2067766","display_name":"Satisfiability modulo theories","level":2,"score":0.3237999975681305},{"id":"https://openalex.org/C2987595161","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Optimization algorithm","level":2,"score":0.32280001044273376},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.29809999465942383},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.29260000586509705},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.29030001163482666},{"id":"https://openalex.org/C149672232","wikidata":"https://www.wikidata.org/wiki/Q337048","display_name":"Adaptive optimization","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.2775000035762787},{"id":"https://openalex.org/C92995354","wikidata":"https://www.wikidata.org/wiki/Q5165499","display_name":"Continuous optimization","level":4,"score":0.27410000562667847},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C91873725","wikidata":"https://www.wikidata.org/wiki/Q3445816","display_name":"Function approximation","level":3,"score":0.2702000141143799},{"id":"https://openalex.org/C145671259","wikidata":"https://www.wikidata.org/wiki/Q1493786","display_name":"Discrete optimization","level":3,"score":0.26100000739097595},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.25529998540878296}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.01030","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01030","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":"doi:10.48550/arxiv.2604.01030","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01030","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":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,16,137],"3D":[3],"Gaussian":[4],"Splatting":[5],"(3DGS)":[6],"present":[7],"two":[8],"main":[9],"directions:":[10],"feed-forward":[11,44,163],"models":[12],"offer":[13],"fast":[14],"inference":[15],"sparse-view":[17],"settings,":[18],"while":[19],"per-scene":[20],"optimization":[21,54,71,87,117,149],"yields":[22],"high-quality":[23],"renderings":[24],"but":[25],"is":[26,151],"computationally":[27],"expensive.":[28],"To":[29,78],"combine":[30],"the":[31,58,80,86,94,116,124],"benefits":[32],"of":[33,83],"both,":[34],"we":[35,89,109,153],"introduce":[36],"Diff3R,":[37],"a":[38,51,74,99,111],"novel":[39],"framework":[40],"that":[41,155],"explicitly":[42],"bridges":[43],"prediction":[45],"and":[46,98,140,169],"test-time":[47,70,175],"optimization.":[48,107,131,176],"By":[49],"incorporating":[50],"differentiable":[52],"3DGS":[53,106,164],"layer":[55,150],"directly":[56],"into":[57,115,161],"training":[59],"loop,":[60],"our":[61,147],"network":[62],"learns":[63],"to":[64,128],"predict":[65],"an":[66],"optimal":[67],"initialization":[68],"for":[69,105,166,174],"rather":[72],"than":[73],"conventional":[75],"zero-shot":[76],"result.":[77],"overcome":[79],"computational":[81],"cost":[82],"backpropagating":[84],"through":[85],"steps,":[88],"propose":[90],"computing":[91],"gradients":[92],"via":[93],"Implicit":[95],"Function":[96],"Theorem":[97],"scalable,":[100],"matrix-free":[101],"PCG":[102],"solver":[103],"tailored":[104],"Additionally,":[108],"incorporate":[110],"data-driven":[112],"uncertainty":[113],"model":[114],"process":[118],"by":[119],"adaptively":[120],"controlling":[121],"how":[122],"much":[123],"parameters":[125],"are":[126],"allowed":[127],"change":[129],"during":[130],"This":[132],"approach":[133],"effectively":[134],"mitigates":[135],"overfitting":[136],"under-constrained":[138],"regions":[139],"increases":[141],"robustness":[142],"against":[143],"input":[144],"outliers.":[145],"Since":[146],"proposed":[148],"model-agnostic,":[152],"show":[154],"it":[156],"can":[157],"be":[158],"seamlessly":[159],"integrated":[160],"existing":[162],"architectures":[165],"both":[167],"pose-given":[168],"pose-free":[170],"methods,":[171],"providing":[172],"improvements":[173]},"counts_by_year":[],"updated_date":"2026-04-03T16:44:17.987007","created_date":"2026-04-03T00:00:00"}
