{"id":"https://openalex.org/W7203889628","doi":"https://doi.org/10.48550/arxiv.2608.19743","title":"Gallileo-4D: Frozen Backbone Ensemble for Dynamic 4D Reconstruction","display_name":"Gallileo-4D: Frozen Backbone Ensemble for Dynamic 4D Reconstruction","publication_year":2026,"publication_date":"2026-08-20","ids":{"openalex":"https://openalex.org/W7203889628","doi":"https://doi.org/10.48550/arxiv.2608.19743"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2608.19743","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.19743","pdf_url":"https://arxiv.org/pdf/2608.19743","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,"listed_in":[],"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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2608.19743","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050968498","display_name":"Nicol\u00f3 Savioli","orcid":"https://orcid.org/0000-0002-3382-0422","observed_orcids":["https://orcid.org/0000-0002-3382-0422"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Savioli, Nicol\u00f2","raw_affiliation_strings":["OdaxAI Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"OdaxAI Research","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5050968498"],"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.7724999785423279,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.7724999785423279,"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":0.05400000140070915,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.024800000712275505,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/4d-reconstruction","display_name":"4D reconstruction","score":0.8360000252723694},{"id":"https://openalex.org/keywords/dynamic-scene-reconstruction","display_name":"dynamic scene reconstruction","score":0.5600000023841858},{"id":"https://openalex.org/keywords/test-time-augmentation","display_name":"test-time augmentation","score":0.5879999995231628},{"id":"https://openalex.org/keywords/zero-shot-inference","display_name":"zero-shot inference","score":0.37700000405311584}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.642300009727478},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6126000285148621},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5533000230789185},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4961000084877014},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.45399999618530273},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4426000118255615},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.42179998755455017},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41449999809265137},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.3991999924182892},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.3776000142097473},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.37599998712539673},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.365200012922287},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.32190001010894775},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.313400000333786},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.31200000643730164},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.275299996137619},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.2678999900817871},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2655999958515167},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.26269999146461487},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25870001316070557},{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.2583000063896179}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2608.19743","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.19743","pdf_url":"https://arxiv.org/pdf/2608.19743","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,"listed_in":[],"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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2608.19743","doi":"https://doi.org/10.48550/arxiv.2608.19743","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2608.19743","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,"listed_in":[],"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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2608.19743","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.19743","pdf_url":"https://arxiv.org/pdf/2608.19743","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,"listed_in":[],"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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7203889628.pdf","grobid_xml":"https://content.openalex.org/works/W7203889628.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W1555759181","https://openalex.org/W1682403713","https://openalex.org/W2470139095","https://openalex.org/W2560321925","https://openalex.org/W2560647685","https://openalex.org/W2770882886","https://openalex.org/W2953937638","https://openalex.org/W3109585842","https://openalex.org/W3168867926","https://openalex.org/W3198675127","https://openalex.org/W3202033766","https://openalex.org/W4221149036","https://openalex.org/W4221155125","https://openalex.org/W4312339971","https://openalex.org/W4366208220","https://openalex.org/W4385318467","https://openalex.org/W4390871746","https://openalex.org/W4402728154","https://openalex.org/W4402816534","https://openalex.org/W4403906568","https://openalex.org/W4403928958","https://openalex.org/W4404002617","https://openalex.org/W4406060219","https://openalex.org/W4413146238","https://openalex.org/W4415277446","https://openalex.org/W4415796839","https://openalex.org/W4416063870","https://openalex.org/W4417091943","https://openalex.org/W4417297074","https://openalex.org/W7105740705","https://openalex.org/W7124293024","https://openalex.org/W7128627045","https://openalex.org/W7160556297"],"related_works":["https://openalex.org/W7137990153","https://openalex.org/W7203893846","https://openalex.org/W7154162106","https://openalex.org/W4416975812","https://openalex.org/W7163007065","https://openalex.org/W6910884504","https://openalex.org/W7106850701","https://openalex.org/W4404987508","https://openalex.org/W7212057536","https://openalex.org/W6910645446"],"abstract_inverted_index":{"We":[0,60],"describe":[1],"our":[2],"entry":[3],"to":[4,64,77],"the":[5,21,32,45,57,65,68,73,78,88,92,95,104,137],"PhysAI":[6],"Dynamic":[7],"4D":[8,41],"Reconstruction":[9],"Challenge,":[10],"which":[11],"placed":[12],"third":[13],"of":[14,34,38,50,67,72],"27":[15],"teams":[16],"at":[17,56,110,146],"0.58356":[18],"APD":[19,135],"on":[20],"final":[22],"leaderboard,":[23],"without":[24],"a":[25,39,128],"single":[26],"gradient":[27],"update.":[28],"This":[29],"was":[30],"not":[31],"plan:":[33],"thirteen":[35],"fine-tuning":[36],"configurations":[37,116],"pre-trained":[40,93],"backbone,":[42],"twelve":[43,52],"degraded":[44],"challenge":[46],"score,":[47],"and":[48,106,123],"eleven":[49],"those":[51],"improved":[53],"local":[54],"validation":[55],"same":[58],"time.":[59],"trace":[61],"this":[62],"inversion":[63],"structure":[66],"benchmark:":[69],"only":[70],"25%":[71],"evaluation":[74],"set":[75],"belongs":[76],"data":[79,90],"variant":[80],"released":[81],"for":[82],"training,":[83],"so":[84],"updates":[85],"that":[86],"fit":[87],"available":[89],"damage":[91],"features":[94],"remaining":[96],"75%":[97],"relies":[98],"on.":[99],"Our":[100],"system":[101],"therefore":[102],"freezes":[103],"backbone":[105],"spends":[107],"its":[108],"budget":[109],"inference":[111],"time,":[112],"fusing":[113],"three":[114],"decoding":[115],"--":[117,126],"temporal":[118],"stride-3,":[119],"horizontal-flip":[120],"test-time":[121],"augmentation,":[122],"dense":[124],"stride-1":[125],"under":[127],"convex":[129],"weighting.":[130],"The":[131],"ensemble":[132],"recovers":[133],"+0.041":[134],"over":[136],"frozen":[138],"baseline,":[139],"more":[140],"than":[141],"any":[142],"training":[143,148],"run":[144],"achieved,":[145],"zero":[147],"cost.":[149]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-08-22T00:00:00"}