{"id":"https://openalex.org/W7162067601","doi":"https://doi.org/10.1145/3799902.3811215","title":"CAdam: Context-Adaptive Moment Estimation for 3D Gaussian Densification in Generative Distillation","display_name":"CAdam: Context-Adaptive Moment Estimation for 3D Gaussian Densification in Generative Distillation","publication_year":2026,"publication_date":"2026-07-16","ids":{"openalex":"https://openalex.org/W7162067601","doi":"https://doi.org/10.1145/3799902.3811215"},"language":null,"primary_location":{"id":"doi:10.1145/3799902.3811215","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3799902.3811215","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Special Interest Group on Computer Graphics and Interactive Techniques Conference Conference Papers","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3799902.3811215","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028999524","display_name":"SeungJeh Chung","orcid":null},"institutions":[{"id":"https://openalex.org/I35928602","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218","country_code":"KR","type":"education","lineage":["https://openalex.org/I35928602"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"SeungJeh Chung","raw_affiliation_strings":["IIIXR Lab, Kyung Hee University, Yongin, Republic of Korea"],"raw_orcid":"https://orcid.org/0009-0000-5306-6896","affiliations":[{"raw_affiliation_string":"IIIXR Lab, Kyung Hee University, Yongin, Republic of Korea","institution_ids":["https://openalex.org/I35928602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136686210","display_name":"Geonho Park","orcid":null},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Geonho Park","raw_affiliation_strings":["IIIXR Lab, Korea University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0009-0005-7727-379X","affiliations":[{"raw_affiliation_string":"IIIXR Lab, Korea University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136632383","display_name":"Misong Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I35928602","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218","country_code":"KR","type":"education","lineage":["https://openalex.org/I35928602"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Misong Kim","raw_affiliation_strings":["IIIXR Lab, Kyung Hee University, Yongin, Republic of Korea"],"raw_orcid":"https://orcid.org/0009-0009-3714-4685","affiliations":[{"raw_affiliation_string":"IIIXR Lab, Kyung Hee University, Yongin, Republic of Korea","institution_ids":["https://openalex.org/I35928602"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011229651","display_name":"HyeongYeop Kang","orcid":"https://orcid.org/0000-0001-5292-4342"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"HyeongYeop Kang","raw_affiliation_strings":["IIIXR Lab, Korea University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0001-5292-4342","affiliations":[{"raw_affiliation_string":"IIIXR Lab, Korea University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I197347611"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"12"},"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":0.7821000218391418,"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":0.7821000218391418,"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":0.039400000125169754,"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/T11448","display_name":"Face recognition and analysis","score":0.020099999383091927,"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/generative-grammar","display_name":"Generative grammar","score":0.6008999943733215},{"id":"https://openalex.org/keywords/moment","display_name":"Moment (physics)","score":0.5946999788284302},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5896000266075134},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.542900025844574},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4821999967098236},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.48030000925064087},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.41190001368522644},{"id":"https://openalex.org/keywords/constructive","display_name":"Constructive","score":0.4023999869823456}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6438999772071838},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6008999943733215},{"id":"https://openalex.org/C179254644","wikidata":"https://www.wikidata.org/wiki/Q13222844","display_name":"Moment (physics)","level":2,"score":0.5946999788284302},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5896000266075134},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.542900025844574},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4821999967098236},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.48030000925064087},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4440000057220459},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41290000081062317},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.41190001368522644},{"id":"https://openalex.org/C2778701210","wikidata":"https://www.wikidata.org/wiki/Q28130034","display_name":"Constructive","level":3,"score":0.4023999869823456},{"id":"https://openalex.org/C169334058","wikidata":"https://www.wikidata.org/wiki/Q353292","display_name":"Additive white Gaussian noise","level":3,"score":0.34220001101493835},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.3418000042438507},{"id":"https://openalex.org/C2777964439","wikidata":"https://www.wikidata.org/wiki/Q5884201","display_name":"Holonomic","level":2,"score":0.33090001344680786},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.3246999979019165},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3244999945163727},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.3149000108242035},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.31119999289512634},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.30309998989105225},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.28139999508857727},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2809999883174896},{"id":"https://openalex.org/C184408114","wikidata":"https://www.wikidata.org/wiki/Q1502022","display_name":"Generative Design","level":3,"score":0.2768000066280365},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2721000015735626},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.26019999384880066},{"id":"https://openalex.org/C61062188","wikidata":"https://www.wikidata.org/wiki/Q835065","display_name":"Second moment of area","level":2,"score":0.2563000023365021}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3799902.3811215","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3799902.3811215","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Special Interest Group on Computer Graphics and Interactive Techniques Conference Conference Papers","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2605.20872","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2605.20872","pdf_url":"https://arxiv.org/pdf/2605.20872","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3799902.3811215","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3799902.3811215","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Special Interest Group on Computer Graphics and Interactive Techniques Conference Conference Papers","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6836845874786377,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1704729159","display_name":null,"funder_award_id":"IITP-2025-RS-2020-II201819","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"},{"id":"https://openalex.org/G7542792045","display_name":null,"funder_award_id":"IITP-2025-RS-2020-II201819","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Adaptive":[0],"densification":[1,85,184],"is":[2,130],"the":[3,14,43,49,95,102,121,125,155],"engine":[4],"of":[5,46,98,158],"3D":[6],"Gaussian":[7,177],"Splatting":[8],"(3DGS).":[9],"However,":[10],"when":[11],"transposed":[12],"to":[13,63,100,182,201],"optimization-based":[15,206],"Generative":[16],"Distillation":[17],"paradigm,":[18],"this":[19,35],"reconstruction-native":[20],"mechanism":[21],"reveals":[22],"fundamental":[23],"limitations,":[24],"resulting":[25],"in":[26,205],"inefficient":[27],"representations":[28],"cluttered":[29],"with":[30],"redundant":[31],"primitives.":[32],"We":[33],"diagnose":[34],"failure":[36],"as":[37,86,197],"a":[38,65,80,87,134,198],"Densification":[39],"Dilemma":[40],"stemming":[41],"from":[42,124],"stochastic":[44,105],"nature":[45],"generative":[47,126,170,207],"guidance:":[48],"standard":[50,183],"magnitude-based":[51],"accumulation":[52],"indiscriminately":[53],"aggregates":[54],"transient":[55],"noise":[56,127],"alongside":[57],"geometric":[58,114],"signals,":[59],"making":[60],"it":[61],"difficult":[62],"strike":[64],"balance":[66],"between":[67],"over-densification":[68],"and":[69,138,153,168],"under-fitting.":[70],"To":[71],"resolve":[72],"this,":[73],"we":[74],"introduce":[75],"Context-Adaptive":[76],"Moment":[77],"Estimation":[78],"(CAdam),":[79],"novel":[81],"framework":[82],"that":[83,174],"reinterprets":[84],"statistically":[88],"grounded":[89],"signal":[90,123],"verification":[91],"problem.":[92],"CAdam":[93,175],"leverages":[94],"first":[96],"moment":[97],"gradients":[99],"exploit":[101],"interference":[103,111],"principle\u2014where":[104],"fluctuations":[106],"cancel":[107],"out":[108],"via":[109,117],"destructive":[110],"while":[112,185],"consistent":[113],"drifts":[115],"accumulate":[116],"constructive":[118],"interference\u2014effectively":[119],"disentangling":[120],"underlying":[122],"floor.":[128],"This":[129],"further":[131],"augmented":[132],"by":[133,179],"quantile-based":[135],"context":[136],"awareness":[137],"an":[139],"intrinsic":[140],"Signal-to-Noise":[141],"Ratio":[142],"(SNR)":[143],"gating":[144],"mechanism,":[145],"which":[146],"ensure":[147],"robust":[148],"adaptation":[149],"across":[150,162],"optimization":[151],"stages":[152],"enable":[154],"soft":[156],"termination":[157],"densification.":[159],"Extensive":[160],"experiments":[161],"diverse":[163],"objectives":[164],"(SDS,":[165],"ISM,":[166],"VFDS)":[167],"strong":[169],"3DGS":[171],"backbones":[172],"show":[173],"reduces":[176],"count":[178],"85%\u201397%":[180],"relative":[181],"preserving":[186],"overall":[187],"comparable":[188],"perceptual":[189],"quality.":[190],"These":[191],"results":[192],"highlight":[193],"signal-aware":[194],"density":[195],"control":[196],"practical":[199],"way":[200],"improve":[202],"memory":[203],"efficiency":[204],"distillation.":[208]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-23T00:00:00"}
