{"id":"https://openalex.org/W7162529893","doi":"https://doi.org/10.1109/3dv69130.2026.00066","title":"Seeing Through Clutter Structured 3D Scene Reconstruction via Iterative Object Removal","display_name":"Seeing Through Clutter Structured 3D Scene Reconstruction via Iterative Object Removal","publication_year":2026,"publication_date":"2026-03-20","ids":{"openalex":"https://openalex.org/W7162529893","doi":"https://doi.org/10.1109/3dv69130.2026.00066"},"language":null,"primary_location":{"id":"doi:10.1109/3dv69130.2026.00066","is_oa":false,"landing_page_url":"https://doi.org/10.1109/3dv69130.2026.00066","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on 3D Vision (3DV)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092814513","display_name":"Rio Aguina-Kang","orcid":null},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rio Aguina-Kang","raw_affiliation_strings":["University of California,San Diego"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California,San Diego","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125128646","display_name":"Kevin James Blackburn-Matzen","orcid":null},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kevin James Blackburn-Matzen","raw_affiliation_strings":["Adobe Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Adobe Research","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030505287","display_name":"Thibault Groueix","orcid":"https://orcid.org/0000-0002-7984-8252"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thibault Groueix","raw_affiliation_strings":["Adobe Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Adobe Research","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125189530","display_name":"Vladimir Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vladimir Kim","raw_affiliation_strings":["Adobe Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Adobe Research","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5137089809","display_name":"Matheus Gadelha","orcid":null},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matheus Gadelha","raw_affiliation_strings":["Adobe Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Adobe Research","institution_ids":["https://openalex.org/I1306409833"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.85365951,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"630","last_page":"639"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.580299973487854,"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":0.580299973487854,"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/T11019","display_name":"Image Enhancement Techniques","score":0.05270000174641609,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.045099999755620956,"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/clutter","display_name":"Clutter","score":0.7501000165939331},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.565500020980835},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.3781000077724457},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.3628000020980835},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.30059999227523804},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.29899999499320984}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7508000135421753},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.7501000165939331},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7038000226020813},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6144999861717224},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.565500020980835},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.3781000077724457},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.3628000020980835},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.30059999227523804},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.27900001406669617},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.2597000002861023},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.25440001487731934},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/3dv69130.2026.00066","is_oa":false,"landing_page_url":"https://doi.org/10.1109/3dv69130.2026.00066","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on 3D Vision (3DV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5799521803855896,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W2507296351","https://openalex.org/W2561196672","https://openalex.org/W2737258237","https://openalex.org/W2990578762","https://openalex.org/W3174541782","https://openalex.org/W3199003182","https://openalex.org/W4298187450","https://openalex.org/W4312933868","https://openalex.org/W4386065887","https://openalex.org/W4389539488","https://openalex.org/W4390874575","https://openalex.org/W4402716288","https://openalex.org/W4402716421","https://openalex.org/W4403049377","https://openalex.org/W4403770461","https://openalex.org/W4404612908","https://openalex.org/W4409347657","https://openalex.org/W4409434838","https://openalex.org/W4412673735","https://openalex.org/W4413145529","https://openalex.org/W4413146238","https://openalex.org/W4413558616","https://openalex.org/W4415798086","https://openalex.org/W4415800665","https://openalex.org/W7110049051","https://openalex.org/W7160090142"],"related_works":[],"abstract_inverted_index":{"We":[0,46,88,120],"present":[1],"SeeingThroughClutter,":[2],"a":[3,63,78],"method":[4,106],"for":[5,94],"reconstructing":[6],"structured":[7],"3D":[8,86],"representations":[9],"from":[10,114],"single":[11],"images":[12],"by":[13,49],"segmenting":[14],"and":[15,29,44,55,85,111,126],"modeling":[16],"objects":[17,73,92],"individually.":[18],"Prior":[19],"approaches":[20],"rely":[21],"on":[22,124],"intermediate":[23],"tasks":[24],"such":[25],"as":[26,70],"semantic":[27],"segmentation":[28],"depth":[30],"estimation,":[31],"which":[32],"often":[33],"underperform":[34],"in":[35,39,101,117],"complex":[36,60],"scenes,":[37],"particularly":[38],"the":[40],"presence":[41],"of":[42,65,97],"occlusion":[43],"clutter.":[45],"address":[47],"this":[48],"introducing":[50],"an":[51],"iterative":[52],"object":[53,83],"removal":[54],"reconstruction":[56],"pipeline":[57],"that":[58,90],"decomposes":[59],"scenes":[61],"into":[62],"sequence":[64],"simpler":[66],"subtasks.":[67],"Using":[68],"VLMs":[69],"orchestrators,":[71],"foreground":[72],"are":[74],"removed":[75],"one":[76],"at":[77],"time":[79],"via":[80],"detection,":[81],"segmentation,":[82],"removal,":[84],"fitting.":[87],"show":[89],"removing":[91],"allows":[93],"cleaner":[95],"segmentations":[96],"subsequent":[98],"objects,":[99],"even":[100],"highly":[102],"occluded":[103],"scenes.":[104],"Our":[105],"requires":[107],"no":[108],"task-specific":[109],"training":[110],"benefits":[112],"directly":[113],"ongoing":[115],"advances":[116],"foundation":[118],"models.":[119],"demonstrate":[121],"state-of-the-art":[122],"robustness":[123],"3D-Front":[125],"ADE20K":[127],"datasets.":[128],"Project":[129],"Page:":[130],"https://rioak.github.io/seeingthroughclutter/":[131]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-28T00:00:00"}