{"id":"https://openalex.org/W7161740502","doi":"https://doi.org/10.48550/arxiv.2605.17197","title":"OPTNet: Ordering Point Transformer Network for Post-disaster 3D Semantic Segmentation","display_name":"OPTNet: Ordering Point Transformer Network for Post-disaster 3D Semantic Segmentation","publication_year":2026,"publication_date":"2026-05-16","ids":{"openalex":"https://openalex.org/W7161740502","doi":"https://doi.org/10.48550/arxiv.2605.17197"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.17197","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17197","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.2605.17197","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109091237","display_name":"Nhut Le","orcid":"https://orcid.org/0000-0003-4745-4600"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Le, Nhut","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116731132","display_name":"Ehsan Karimi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Karimi, Ehsan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5010792548","display_name":"Maryam Rahnemoonfar","orcid":"https://orcid.org/0000-0001-9358-2836"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rahnemoonfar, Maryam","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/T10036","display_name":"Advanced Neural Network Applications","score":0.18559999763965607,"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":0.18559999763965607,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.17790000140666962,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.1257999986410141,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6771000027656555},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6166999936103821},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.567799985408783},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.5437999963760376},{"id":"https://openalex.org/keywords/serialization","display_name":"Serialization","score":0.4050000011920929},{"id":"https://openalex.org/keywords/point-process","display_name":"Point process","score":0.3828999996185303},{"id":"https://openalex.org/keywords/hilbert-curve","display_name":"Hilbert curve","score":0.33329999446868896}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6771000027656555},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6600000262260437},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6166999936103821},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.567799985408783},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.5437999963760376},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45879998803138733},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4097000062465668},{"id":"https://openalex.org/C52723943","wikidata":"https://www.wikidata.org/wiki/Q1127410","display_name":"Serialization","level":2,"score":0.4050000011920929},{"id":"https://openalex.org/C88871306","wikidata":"https://www.wikidata.org/wiki/Q7208287","display_name":"Point process","level":2,"score":0.3828999996185303},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34220001101493835},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33709999918937683},{"id":"https://openalex.org/C2781142347","wikidata":"https://www.wikidata.org/wiki/Q1366592","display_name":"Hilbert curve","level":2,"score":0.33329999446868896},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.33090001344680786},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.3158000111579895},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3043000102043152},{"id":"https://openalex.org/C21308566","wikidata":"https://www.wikidata.org/wiki/Q7169365","display_name":"Permutation (music)","level":2,"score":0.3019999861717224},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C174440990","wikidata":"https://www.wikidata.org/wiki/Q681349","display_name":"Point-to-point","level":2,"score":0.2800999879837036},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.2646999955177307}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.17197","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17197","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.2605.17197","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17197","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":[{"display_name":"Sustainable cities and communities","score":0.45315447449684143,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Post-disaster":[0],"damage":[1],"assessment":[2],"requires":[3],"rapid":[4],"and":[5,21,36],"accurate":[6],"semantic":[7],"segmentation":[8],"of":[9,80,116],"3D":[10],"point":[11],"clouds":[12],"to":[13,61,106],"identify":[14],"critical":[15],"infrastructure":[16],"such":[17,55],"as":[18,56],"damaged":[19],"buildings":[20],"roads.":[22],"Early":[23],"Point":[24,38,47,90,97],"Transformers":[25],"(e.g.,":[26],"PTv1,":[27],"PTv2)":[28],"relied":[29],"on":[30,124],"computationally":[31],"expensive":[32],"neighbor":[33],"searching":[34],"(k-NN)":[35],"Farthest":[37],"Sampling":[39],"(FPS).":[40],"To":[41],"improve":[42],"efficiency,":[43],"recent":[44],"architectures":[45],"like":[46],"Transformer":[48,91],"V3":[49],"(PTv3)":[50],"adopted":[51],"static":[52],"serialization":[53],"methods,":[54],"Hilbert":[57],"curves":[58],"or":[59],"Z-order,":[60],"organize":[62],"unstructured":[63],"points":[64],"for":[65,75],"window-based":[66],"attention.":[67],"However,":[68],"these":[69],"fixed":[70],"orderings":[71],"are":[72],"not":[73],"optimal":[74,110],"capturing":[76],"the":[77,114,117,125],"complex":[78],"geometry":[79],"disaster":[81],"scenes.":[82],"In":[83],"this":[84],"paper,":[85],"we":[86],"propose":[87],"OPTNet":[88,100],"(Ordering":[89],"Network),":[92],"which":[93],"introduces":[94],"a":[95,102],"learnable":[96],"Sorter":[98],"module.":[99],"utilizes":[101],"self-supervised":[103],"ordering":[104],"loss":[105],"dynamically":[107],"predict":[108],"an":[109],"permutation":[111],"that":[112],"maximizes":[113],"locality":[115],"attention":[118],"mechanism.":[119],"We":[120],"evaluate":[121],"our":[122],"method":[123],"3DAeroRelief":[126],"dataset,":[127],"significantly":[128],"outperforming":[129],"state-of-the-art":[130],"baselines.":[131]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-20T00:00:00"}
