{"id":"https://openalex.org/W7154243039","doi":"https://doi.org/10.48550/arxiv.2604.09862","title":"FF3R: Feedforward Feature 3D Reconstruction from Unconstrained views","display_name":"FF3R: Feedforward Feature 3D Reconstruction from Unconstrained views","publication_year":2026,"publication_date":"2026-04-10","ids":{"openalex":"https://openalex.org/W7154243039","doi":"https://doi.org/10.48550/arxiv.2604.09862"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.09862","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09862","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2604.09862","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133604857","display_name":"Chaoyi Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Chaoyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133597311","display_name":"Run Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Run","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133611483","display_name":"Feng Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Feng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133560055","display_name":"Mert D. Pes\u00e9","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pes\u00e9, Mert D.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133597197","display_name":"Zhiwen Fan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan, Zhiwen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078507915","display_name":"\u949f\u76ca\u5947","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhong, Yiqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133568863","display_name":"Siyu Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Siyu","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/T10531","display_name":"Advanced Vision and Imaging","score":0.36399999260902405,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.36399999260902405,"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":0.3100999891757965,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.23569999635219574,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/image-warping","display_name":"Image warping","score":0.5105999708175659},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.5098999738693237},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46209999918937683},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.40470001101493835},{"id":"https://openalex.org/keywords/semantic-feature","display_name":"Semantic feature","score":0.3781000077724457},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.3668999969959259},{"id":"https://openalex.org/keywords/semantic-mapping","display_name":"Semantic mapping","score":0.35190001130104065},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.33239999413490295},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.3034999966621399}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.741599977016449},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6306999921798706},{"id":"https://openalex.org/C157202957","wikidata":"https://www.wikidata.org/wiki/Q1659609","display_name":"Image warping","level":2,"score":0.5105999708175659},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.5098999738693237},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4672999978065491},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46209999918937683},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.40470001101493835},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.3781000077724457},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.3668999969959259},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.35190001130104065},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.33239999413490295},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.3034999966621399},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2971999943256378},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.29120001196861267},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.29120001196861267},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.28850001096725464},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2867000102996826},{"id":"https://openalex.org/C2983787585","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature matching","level":3,"score":0.2822999954223633},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.28040000796318054},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2687999904155731},{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.2648000121116638},{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.2531000077724457},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.09862","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09862","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.09862","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09862","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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":{"Recent":[0],"advances":[1],"in":[2,22,90,151],"vision":[3],"foundation":[4],"models":[5],"have":[6],"revolutionized":[7],"geometry":[8,114],"reconstruction":[9,93],"and":[10,28,43,72,99,121,145,157,177],"semantic":[11,44,63,97,117,155,178],"understanding.":[12,179],"Yet,":[13],"most":[14],"of":[15],"the":[16,167],"existing":[17],"approaches":[18],"treat":[19],"these":[20],"capabilities":[21],"isolation,":[23],"leading":[24],"to":[25,163],"redundant":[26],"pipelines":[27],"compounded":[29],"errors.":[30],"This":[31],"paper":[32],"introduces":[33],"FF3R,":[34],"a":[35,76,108,123],"fully":[36],"annotation-free":[37],"feed-forward":[38],"framework":[39],"that":[40,112,173],"unifies":[41],"geometric":[42],"reasoning":[45],"from":[46],"unconstrained":[47],"multi-view":[48],"image":[49],"sequences.":[50],"Unlike":[51],"previous":[52],"methods,":[53],"FF3R":[54],"does":[55],"not":[56],"require":[57],"camera":[58],"poses,":[59],"depth":[60,158],"maps,":[61,74],"or":[62],"labels,":[64],"relying":[65],"solely":[66],"on":[67,143],"rendering":[68],"supervision":[69],"for":[70,79,132,138,169],"RGB":[71],"feature":[73,92,130],"establishing":[75],"scalable":[77],"paradigm":[78],"unified":[80],"3D":[81],"reasoning.":[82],"In":[83],"addition,":[84],"we":[85],"address":[86],"two":[87,104],"critical":[88],"challenges":[89],"feedforward":[91],"pipelines,":[94],"namely":[95],"global":[96,133],"inconsistency":[98],"local":[100,139],"structural":[101],"inconsistency,":[102],"through":[103],"key":[105],"innovations:":[106],"(i)":[107],"Token-wise":[109],"Fusion":[110],"Module":[111],"enriches":[113],"tokens":[115],"with":[116,135,160],"context":[118],"via":[119],"cross-attention,":[120],"(ii)":[122],"Semantic-Geometry":[124],"Mutual":[125],"Boosting":[126],"mechanism":[127],"combining":[128],"geometry-guided":[129],"warping":[131],"consistency":[134],"semantic-aware":[136],"voxelization":[137],"coherence.":[140],"Extensive":[141],"experiments":[142],"ScanNet":[144],"DL3DV-10K":[146],"demonstrate":[147],"FF3R's":[148],"superior":[149],"performance":[150],"novel-view":[152],"synthesis,":[153],"open-vocabulary":[154],"segmentation,":[156],"estimation,":[159],"strong":[161],"generalization":[162],"in-the-wild":[164],"scenarios,":[165],"paving":[166],"way":[168],"embodied":[170],"intelligence":[171],"systems":[172],"demand":[174],"both":[175],"spatial":[176]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-15T00:00:00"}
