{"id":"https://openalex.org/W7117983376","doi":"https://doi.org/10.1109/tpami.2025.3650165","title":"GrowSP++: Growing Superpoints and Primitives for Unsupervised 3D Semantic Segmentation","display_name":"GrowSP++: Growing Superpoints and Primitives for Unsupervised 3D Semantic Segmentation","publication_year":2026,"publication_date":"2026-01-02","ids":{"openalex":"https://openalex.org/W7117983376","doi":"https://doi.org/10.1109/tpami.2025.3650165","pmid":"https://pubmed.ncbi.nlm.nih.gov/41481405"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2025.3650165","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3650165","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5121823046","display_name":"Zihui Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Zihui Zhang","raw_affiliation_strings":["Hong Kong Polytechnic University Shenzhen Technology and Innovation Research Institute (Futian), the Hong Kong Polytechnic University Shenzhen Research Institute, the Hong Kong Poytechnic University vLAR group, Hong Kong SAR, China"],"raw_orcid":"https://orcid.org/0000-0002-1891-8253","affiliations":[{"raw_affiliation_string":"Hong Kong Polytechnic University Shenzhen Technology and Innovation Research Institute (Futian), the Hong Kong Polytechnic University Shenzhen Research Institute, the Hong Kong Poytechnic University vLAR group, Hong Kong SAR, China","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Weisheng Dai","orcid":"https://orcid.org/0009-0006-2862-5813"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Weisheng Dai","raw_affiliation_strings":["Hong Kong Polytechnic University Shenzhen Technology and Innovation Research Institute (Futian), the Hong Kong Polytechnic University Shenzhen Research Institute, the Hong Kong Poytechnic University vLAR group, Hong Kong SAR, China"],"raw_orcid":"https://orcid.org/0009-0006-2862-5813","affiliations":[{"raw_affiliation_string":"Hong Kong Polytechnic University Shenzhen Technology and Innovation Research Institute (Futian), the Hong Kong Polytechnic University Shenzhen Research Institute, the Hong Kong Poytechnic University vLAR group, Hong Kong SAR, China","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100382504","display_name":"Bing Wang","orcid":"https://orcid.org/0000-0002-3134-6763"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Bing Wang","raw_affiliation_strings":["Hong Kong Polytechnic University, Hong Kong SAR, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hong Kong Polytechnic University, Hong Kong SAR, China","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Bo Li","orcid":"https://orcid.org/0000-0001-7500-8355"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Bo Li","raw_affiliation_strings":["Hong Kong Polytechnic University, Hong Kong SAR, China"],"raw_orcid":"https://orcid.org/0000-0001-7500-8355","affiliations":[{"raw_affiliation_string":"Hong Kong Polytechnic University, Hong Kong SAR, China","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121813993","display_name":"Bo Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Bo Yang","raw_affiliation_strings":["Hong Kong Polytechnic University Shenzhen Technology and Innovation Research Institute (Futian), the Hong Kong Polytechnic University Shenzhen Research Institute, the Hong Kong Poytechnic University vLAR group, Hong Kong SAR, China"],"raw_orcid":"https://orcid.org/0000-0002-2419-4140","affiliations":[{"raw_affiliation_string":"Hong Kong Polytechnic University Shenzhen Technology and Innovation Research Institute (Futian), the Hong Kong Polytechnic University Shenzhen Research Institute, the Hong Kong Poytechnic University vLAR group, Hong Kong SAR, China","institution_ids":["https://openalex.org/I14243506"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5121823046"],"corresponding_institution_ids":["https://openalex.org/I14243506"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01958337,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"48","issue":"5","first_page":"5016","last_page":"5031"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.86080002784729,"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"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.86080002784729,"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":0.06859999895095825,"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"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.012500000186264515,"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/extractor","display_name":"Extractor","score":0.645799994468689},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6083999872207642},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5649999976158142},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.51419997215271},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.49720001220703125},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.48330000042915344},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.4523000121116638},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4449999928474426}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8497999906539917},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6908000111579895},{"id":"https://openalex.org/C117978034","wikidata":"https://www.wikidata.org/wiki/Q5422192","display_name":"Extractor","level":2,"score":0.645799994468689},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6083999872207642},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5649999976158142},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.51419997215271},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.49720001220703125},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.48330000042915344},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.4523000121116638},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4449999928474426},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.4359000027179718},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.38830000162124634},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3723999857902527},{"id":"https://openalex.org/C2777946921","wikidata":"https://www.wikidata.org/wiki/Q7449044","display_name":"Semantic analysis (machine learning)","level":2,"score":0.2906000018119812},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.28459998965263367},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.27950000762939453},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.26429998874664307},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.2621999979019165},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.260699987411499},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.25279998779296875},{"id":"https://openalex.org/C2778493491","wikidata":"https://www.wikidata.org/wiki/Q7449072","display_name":"Semantic matching","level":3,"score":0.251800000667572}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2025.3650165","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3650165","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:41481405","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41481405","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.6081165671348572,"id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G2194189513","display_name":null,"funder_award_id":"62271431","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322598","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,128,147],"study":[1],"the":[2,95,100,111,124],"problem":[3],"of":[4,22,51,58],"3D":[5,45,120,158],"semantic":[6,39,81,108,126,159],"segmentation":[7],"from":[8],"raw":[9],"point":[10,43],"clouds.":[11],"Unlike":[12],"existing":[13],"methods":[14,155],"which":[15],"primarily":[16],"rely":[17],"on":[18,104,133],"a":[19,63,71,80],"large":[20],"amount":[21],"human":[23,52],"annotations":[24],"for":[25,41,119,156],"training":[26],"neural":[27],"networks,":[28],"we":[29],"proposes":[30],"GrowSP++,":[31],"an":[32,85],"unsupervised":[33,145,157],"method":[34,55,93,132],"to":[35,91,114,123],"successfully":[36],"identify":[37],"complex":[38],"classes":[40],"every":[42],"in":[44],"scenes,":[46],"without":[47],"needing":[48],"any":[49],"type":[50],"labels.":[53],"Our":[54],"is":[56,94],"composed":[57],"three":[59],"major":[60],"components:":[61],"1)":[62],"feature":[64,68,112],"extractor":[65,113],"incorporating":[66],"2D-3D":[67],"distillation,":[69],"2)":[70],"superpoint":[72,96],"constructor":[73,83,97],"featuring":[74],"progressively":[75,115],"growing":[76,87,102],"superpoints,":[77],"and":[78,107,137],"3)":[79],"primitive":[82],"with":[84,99],"additional":[86],"strategy.":[88],"The":[89],"key":[90],"our":[92,131,149],"together":[98],"progressive":[101],"strategy":[103],"both":[105],"superpoints":[106],"primitives,":[109],"driving":[110],"learn":[116],"similar":[117],"features":[118],"points":[121],"belonging":[122],"same":[125],"class.":[127],"extensively":[129],"evaluate":[130],"five":[134],"challenging":[135],"indoor":[136],"outdoor":[138],"datasets,":[139],"demonstrating":[140],"state-of-the-art":[141],"performance":[142],"over":[143],"all":[144],"baselines.":[146],"hope":[148],"work":[150],"could":[151],"inspire":[152],"more":[153],"advanced":[154],"learning.":[160]},"counts_by_year":[],"updated_date":"2026-04-04T06:10:10.580331","created_date":"2026-01-02T00:00:00"}