{"id":"https://openalex.org/W7167612395","doi":"https://doi.org/10.48550/arxiv.2607.04256","title":"AdaptiveSplat:Texture Aware Controllable 3D Gaussian Allocation for Feed-Forward Reconstruction","display_name":"AdaptiveSplat:Texture Aware Controllable 3D Gaussian Allocation for Feed-Forward Reconstruction","publication_year":2026,"publication_date":"2026-07-05","ids":{"openalex":"https://openalex.org/W7167612395","doi":"https://doi.org/10.48550/arxiv.2607.04256"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.04256","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.04256","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.04256","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110580217","display_name":"Badrinath Singhal","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Singhal, Badrinath","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140213898","display_name":"Srihari K G","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"G, Srihari K","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140221124","display_name":"Sreehari Iyer","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Iyer, Sreehari","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062494269","display_name":"Ankit Dhiman","orcid":"https://orcid.org/0000-0002-9451-2052"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dhiman, Ankit","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5062096014","display_name":"Venkatesh Babu Radhakrishnan","orcid":"https://orcid.org/0000-0002-1926-1804"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Radhakrishnan, Venkatesh Babu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.26660001277923584,"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"}},"topics":[{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.26660001277923584,"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":0.21199999749660492,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.07859999686479568,"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/gaussian","display_name":"Gaussian","score":0.6388999819755554},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.6384999752044678},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.585099995136261},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4756999909877777},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.47269999980926514},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.45750001072883606},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4174000024795532},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.361299991607666}],"concepts":[{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6388999819755554},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.6384999752044678},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6172000169754028},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.585099995136261},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5256999731063843},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4756999909877777},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.47269999980926514},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.45750001072883606},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4449999928474426},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4174000024795532},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38960000872612},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.361299991607666},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.34619998931884766},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.3384999930858612},{"id":"https://openalex.org/C50494287","wikidata":"https://www.wikidata.org/wiki/Q658467","display_name":"Texture synthesis","level":5,"score":0.32600000500679016},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.3098999857902527},{"id":"https://openalex.org/C166550679","wikidata":"https://www.wikidata.org/wiki/Q263400","display_name":"Gaussian network model","level":3,"score":0.29980000853538513},{"id":"https://openalex.org/C148043351","wikidata":"https://www.wikidata.org/wiki/Q4456944","display_name":"Current (fluid)","level":2,"score":0.29350000619888306},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.2741999924182892},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2720000147819519},{"id":"https://openalex.org/C13670688","wikidata":"https://www.wikidata.org/wiki/Q3500548","display_name":"Space partitioning","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.2563000023365021}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.04256","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.04256","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.04256","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.04256","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":false,"raw_source_name":null,"raw_type":"Preprint"},"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":{"Current":[0],"feed-forward":[1,38,129],"3D":[2],"reconstruction":[3],"methods":[4],"predict":[5],"pixel":[6],"aligned":[7],"Gaussian":[8,49,115],"primitives,":[9,50],"resulting":[10],"in":[11,97],"highly":[12],"redundant":[13,22,105],"representations.":[14],"A":[15],"natural":[16],"solution":[17],"is":[18],"to":[19,70,93],"prune":[20],"the":[21,37,73,119,123,128,142,151],"Gaussians,":[23],"but":[24],"naive":[25],"pruning":[26,102],"introduces":[27],"severe":[28],"artifacts":[29],"and":[30,111,137,139],"often":[31],"requires":[32],"inference":[33],"time":[34],"fine-tuning,":[35],"breaking":[36,127],"paradigm.":[39,130],"Based":[40],"on":[41,132],"previous":[42],"works,":[43],"high":[44],"frequency":[45,53,109],"regions":[46,54],"require":[47],"more":[48],"while":[51,147],"low":[52,108],"can":[55],"be":[56],"represented":[57],"with":[58],"significantly":[59],"fewer":[60],"primitives.":[61],"Motivated":[62],"by":[63,77],"this,":[64],"we":[65],"propose":[66],"a":[67],"novel":[68],"approach":[69,83],"explicitly":[71],"control":[72],"number":[74],"of":[75,122,144,153],"Gaussians":[76,106],"leveraging":[78],"local":[79],"texture":[80,91],"information.":[81],"Our":[82],"achieves":[84],"this":[85],"through":[86],"three":[87],"key":[88,155],"components:":[89],"(1)":[90],"estimation":[92],"capture":[94],"spatial":[95],"variation":[96],"scene":[98],"detail,":[99],"(2)":[100],"texture-aware":[101],"that":[103,117],"removes":[104],"from":[107],"regions,":[110],"(3)":[112],"an":[113],"adaptive":[114],"head":[116],"predicts":[118],"modified":[120],"attributes":[121],"retained":[124],"primitives":[125],"without":[126],"Experiments":[131],"RE10K,":[133],"ACID,":[134],"DL3DV,":[135],"Tanks":[136],"Temples,":[138],"DTU":[140],"demonstrate":[141],"effectiveness":[143],"our":[145],"approach,":[146],"ablation":[148],"studies":[149],"validate":[150],"contributions":[152],"its":[154],"components.":[156]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-08T00:00:00"}