{"id":"https://openalex.org/W7106656394","doi":"https://doi.org/10.48550/arxiv.2511.18672","title":"Sphinx: Efficiently Serving Novel View Synthesis using Regression-Guided Selective Refinement","display_name":"Sphinx: Efficiently Serving Novel View Synthesis using Regression-Guided Selective Refinement","publication_year":2025,"publication_date":"2025-11-24","ids":{"openalex":"https://openalex.org/W7106656394","doi":"https://doi.org/10.48550/arxiv.2511.18672"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2511.18672","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.18672","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":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.2511.18672","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Xia, Yuchen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xia, Yuchen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Kundu, Souvik","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kundu, Souvik","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Chowdhury, Mosharaf","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chowdhury, Mosharaf","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Talati, Nishil","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Talati, Nishil","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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.4203000068664551,"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":0.4203000068664551,"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":0.32330000400543213,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.07209999859333038,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6176000237464905},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.6128000020980835},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.4706999957561493},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.44920000433921814},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4341999888420105},{"id":"https://openalex.org/keywords/sphinx","display_name":"Sphinx","score":0.41200000047683716},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.3181999921798706}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8166999816894531},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6176000237464905},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.6128000020980835},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.4706999957561493},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.44920000433921814},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4341999888420105},{"id":"https://openalex.org/C2777299493","wikidata":"https://www.wikidata.org/wiki/Q151480","display_name":"Sphinx","level":2,"score":0.41200000047683716},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39410001039505005},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3346000015735626},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.3181999921798706},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.3158000111579895},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3147999942302704},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.31360000371932983},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.30329999327659607},{"id":"https://openalex.org/C49020025","wikidata":"https://www.wikidata.org/wiki/Q1059099","display_name":"Chaining","level":2,"score":0.2897999882698059},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28929999470710754},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.27709999680519104},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.25519999861717224}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2511.18672","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.18672","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2511.18672","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.18672","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":false,"raw_source_name":null,"raw_type":"Preprint"},"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":{"Novel":[0],"View":[1],"Synthesis":[2],"(NVS)":[3],"is":[4],"the":[5,21,49,94,98,126],"task":[6],"of":[7,11,20,52,125,159],"generating":[8],"new":[9,165],"images":[10],"a":[12,53,69,79,164],"scene":[13],"from":[14],"viewpoints":[15],"that":[16,74,144],"were":[17],"not":[18],"part":[19],"original":[22],"input.":[23],"Diffusion-based":[24],"NVS":[25,38,56,173],"can":[26],"generate":[27],"high-quality,":[28,54],"temporally":[29],"consistent":[30],"images,":[31],"however,":[32],"remains":[33],"computationally":[34],"prohibitive.":[35],"Conversely,":[36],"regression-based":[37,87],"offers":[39],"suboptimal":[40],"generation":[41],"quality":[42,169],"despite":[43],"requiring":[44],"significantly":[45,80],"lower":[46,81],"compute;":[47],"leaving":[48],"design":[50],"objective":[51],"inference-efficient":[55],"framework":[57,73],"an":[58,147],"open":[59],"challenge.":[60],"To":[61],"close":[62],"this":[63],"critical":[64],"gap,":[65],"we":[66],"present":[67],"Sphinx,":[68],"training-free":[70],"hybrid":[71],"inference":[72,139,154],"achieves":[75,146],"diffusion-level":[76],"fidelity":[77,134],"at":[78],"compute.":[82],"Sphinx":[83,120,145],"proposes":[84],"to":[85,90,113,121,131],"use":[86],"fast":[88],"initialization":[89],"guide":[91],"and":[92,116,133,170],"reduce":[93],"denoising":[95],"workload":[96],"for":[97,136],"diffusion":[99,152],"model.":[100],"Additionally,":[101],"it":[102],"integrates":[103],"selective":[104],"refinement":[105],"with":[106,155],"adaptive":[107],"noise":[108],"scheduling,":[109],"allowing":[110,129],"more":[111],"compute":[112],"uncertain":[114],"regions":[115],"frames.":[117],"This":[118],"enables":[119],"provide":[122],"flexible":[123],"navigation":[124],"performance-quality":[127],"trade-off,":[128],"adaptation":[130],"latency":[132,171],"requirements":[135],"dynamically":[137],"changing":[138],"scenarios.":[140],"Our":[141],"evaluation":[142],"shows":[143],"average":[148],"1.8x":[149],"speedup":[150],"over":[151],"model":[153],"negligible":[156],"perceptual":[157],"degradation":[158],"less":[160],"than":[161],"5%,":[162],"establishing":[163],"Pareto":[166],"frontier":[167],"between":[168],"in":[172],"serving.":[174]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-11-27T00:00:00"}
