{"id":"https://openalex.org/W7140292746","doi":"https://doi.org/10.48550/arxiv.2603.23478","title":"UniFunc3D: Unified Active Spatial-Temporal Grounding for 3D Functionality Segmentation","display_name":"UniFunc3D: Unified Active Spatial-Temporal Grounding for 3D Functionality Segmentation","publication_year":2026,"publication_date":"2026-03-24","ids":{"openalex":"https://openalex.org/W7140292746","doi":"https://doi.org/10.48550/arxiv.2603.23478"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.23478","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23478","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.2603.23478","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130549560","display_name":"Jiaying Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Jiaying","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130577061","display_name":"Dan Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Dan","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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.6075999736785889,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.6075999736785889,"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":0.12300000339746475,"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":0.07890000194311142,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6204000115394592},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5555999875068665},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5291000008583069},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5134000182151794},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.4837000072002411},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.4794999957084656},{"id":"https://openalex.org/keywords/ground","display_name":"Ground","score":0.46810001134872437},{"id":"https://openalex.org/keywords/active-vision","display_name":"Active vision","score":0.4498000144958496},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.3939000070095062}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7728999853134155},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6413999795913696},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6204000115394592},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5555999875068665},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5291000008583069},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5134000182151794},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.4837000072002411},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4828000068664551},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.4794999957084656},{"id":"https://openalex.org/C168993435","wikidata":"https://www.wikidata.org/wiki/Q6501125","display_name":"Ground","level":2,"score":0.46810001134872437},{"id":"https://openalex.org/C193611912","wikidata":"https://www.wikidata.org/wiki/Q4677596","display_name":"Active vision","level":2,"score":0.4498000144958496},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.3939000070095062},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.3828999996185303},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.37929999828338623},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.33489999175071716},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3264000117778778},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.3061000108718872},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2930999994277954},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.28459998965263367},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.2759999930858612},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.25949999690055847},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.25780001282691956},{"id":"https://openalex.org/C2776863239","wikidata":"https://www.wikidata.org/wiki/Q7936601","display_name":"Visual hull","level":3,"score":0.25760000944137573},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.2563000023365021},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.2522999942302704}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.23478","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23478","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.2603.23478","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23478","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Functionality":[0],"segmentation":[1],"in":[2,88],"3D":[3],"scenes":[4],"requires":[5],"an":[6,65],"agent":[7],"to":[8,84,106],"ground":[9,85],"implicit":[10],"natural-language":[11],"instructions":[12],"into":[13,75],"precise":[14],"masks":[15],"of":[16],"fine-grained":[17],"interactive":[18,116],"elements.":[19],"Existing":[20],"methods":[21,39,137],"rely":[22],"on":[23,114,156],"fragmented":[24],"pipelines":[25],"that":[26,37,57],"suffer":[27],"from":[28],"visual":[29,90],"blindness":[30],"during":[31],"initial":[32],"task":[33,86],"parsing.":[34],"We":[35,49],"observe":[36],"these":[38],"are":[40],"limited":[41],"by":[42,138],"single-scale,":[43],"passive":[44],"and":[45,54,72,112,135],"heuristic":[46],"frame":[47],"selection.":[48],"present":[50],"UniFunc3D,":[51],"a":[52,76,99,139,143],"unified":[53],"training-free":[55,134],"framework":[56],"treats":[58],"the":[59,104,120],"multimodal":[60],"large":[61,140],"language":[62],"model":[63,105],"as":[64],"active":[66,95],"observer.":[67],"By":[68],"consolidating":[69],"semantic,":[70],"temporal,":[71],"spatial":[73],"reasoning":[74,83],"single":[77],"forward":[78],"pass,":[79],"UniFunc3D":[80,128],"performs":[81],"joint":[82],"decomposition":[87],"direct":[89],"evidence.":[91],"Our":[92],"approach":[93],"introduces":[94],"spatial-temporal":[96],"grounding":[97],"with":[98,142],"coarse-to-fine":[100],"strategy.":[101],"This":[102],"allows":[103],"select":[107],"correct":[108],"video":[109],"frames":[110],"adaptively":[111],"focus":[113],"high-detail":[115],"parts":[117],"while":[118],"preserving":[119],"global":[121],"context":[122],"necessary":[123],"for":[124],"disambiguation.":[125],"On":[126],"SceneFun3D,":[127],"achieves":[129],"state-of-the-art":[130],"performance,":[131],"surpassing":[132],"both":[133],"training-based":[136],"margin":[141],"relative":[144],"59.9\\%":[145],"mIoU":[146],"improvement,":[147],"without":[148],"any":[149],"task-specific":[150],"training.":[151],"Code":[152],"will":[153],"be":[154],"released":[155],"our":[157],"project":[158],"page:":[159],"https://jiaying.link/unifunc3d.":[160]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-26T00:00:00"}
