{"id":"https://openalex.org/W7162491145","doi":"https://doi.org/10.1109/3dv69130.2026.00154","title":"ConTiCoM-3D: A Continuous-Time Consistency Model for 3D Point Cloud Generation","display_name":"ConTiCoM-3D: A Continuous-Time Consistency Model for 3D Point Cloud Generation","publication_year":2026,"publication_date":"2026-03-20","ids":{"openalex":"https://openalex.org/W7162491145","doi":"https://doi.org/10.1109/3dv69130.2026.00154"},"language":null,"primary_location":{"id":"doi:10.1109/3dv69130.2026.00154","is_oa":false,"landing_page_url":"https://doi.org/10.1109/3dv69130.2026.00154","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/A5087562937","display_name":"Sebastian Eilermann","orcid":null},"institutions":[{"id":"https://openalex.org/I190134885","display_name":"Helmut Schmidt University","ror":"https://ror.org/04e8jbs38","country_code":"DE","type":"education","lineage":["https://openalex.org/I190134885"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sebastian Eilermann","raw_affiliation_strings":["Institute for Artificial Intelligence, Helmut Schmidt University,Hamburg,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Artificial Intelligence, Helmut Schmidt University,Hamburg,Germany","institution_ids":["https://openalex.org/I190134885"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007982480","display_name":"Ren\u00e9 Heesch","orcid":"https://orcid.org/0000-0003-1147-8205"},"institutions":[{"id":"https://openalex.org/I190134885","display_name":"Helmut Schmidt University","ror":"https://ror.org/04e8jbs38","country_code":"DE","type":"education","lineage":["https://openalex.org/I190134885"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ren\u00e9 Heesch","raw_affiliation_strings":["Institute for Artificial Intelligence, Helmut Schmidt University,Hamburg,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Artificial Intelligence, Helmut Schmidt University,Hamburg,Germany","institution_ids":["https://openalex.org/I190134885"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012395966","display_name":"Oliver Niggemann","orcid":"https://orcid.org/0000-0001-8747-3596"},"institutions":[{"id":"https://openalex.org/I190134885","display_name":"Helmut Schmidt University","ror":"https://ror.org/04e8jbs38","country_code":"DE","type":"education","lineage":["https://openalex.org/I190134885"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Oliver Niggemann","raw_affiliation_strings":["Institute for Artificial Intelligence, Helmut Schmidt University,Hamburg,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Artificial Intelligence, Helmut Schmidt University,Hamburg,Germany","institution_ids":["https://openalex.org/I190134885"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"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":0.83675841,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1619","last_page":"1628"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9068999886512756,"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":0.9068999886512756,"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/T12290","display_name":"Human Motion and Animation","score":0.01489999983459711,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10653","display_name":"Robot Manipulation and Learning","score":0.006300000008195639,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/consistency","display_name":"Consistency (knowledge bases)","score":0.4487999975681305},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.3831999897956848},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.3806000053882599},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.31349998712539673},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.2808000147342682}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49880000948905945},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.4487999975681305},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39820000529289246},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.3831999897956848},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.3806000053882599},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31610000133514404},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.31349998712539673},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29280000925064087},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.2808000147342682},{"id":"https://openalex.org/C93361087","wikidata":"https://www.wikidata.org/wiki/Q4426698","display_name":"Data consistency","level":2,"score":0.27950000762939453},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2694000005722046}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/3dv69130.2026.00154","is_oa":false,"landing_page_url":"https://doi.org/10.1109/3dv69130.2026.00154","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":[{"display_name":"Climate action","id":"https://metadata.un.org/sdg/13","score":0.4621150493621826}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2143668817","https://openalex.org/W2560722161","https://openalex.org/W2962785568","https://openalex.org/W2985683375","https://openalex.org/W2986615800","https://openalex.org/W3045146419","https://openalex.org/W3108645709","https://openalex.org/W3108944788","https://openalex.org/W3117476483","https://openalex.org/W3141954417","https://openalex.org/W3166584442","https://openalex.org/W3180196270","https://openalex.org/W4229944339","https://openalex.org/W4239863109","https://openalex.org/W4385245566","https://openalex.org/W4386065690","https://openalex.org/W4386076564","https://openalex.org/W4387226000","https://openalex.org/W4403446794","https://openalex.org/W4403447096","https://openalex.org/W7133237268","https://openalex.org/W7160052779"],"related_works":[],"abstract_inverted_index":{"Fast":[0],"and":[1,18,125,132],"accurate":[2],"3D":[3,31,142],"shape":[4,143],"generation":[5],"from":[6],"point":[7,35,68],"clouds":[8],"is":[9],"essential":[10],"for":[11,140],"real-world":[12],"applications":[13],"such":[14],"as":[15,136],"robotics,":[16],"AR/VR,":[17],"digital":[19],"content":[20],"creation.":[21],"We":[22],"present":[23],"ConTiCoM-3D,":[24],"a":[25,52,58,103,137],"continuous-time":[26],"consistency":[27,127],"model":[28],"that":[29,89,117],"generates":[30],"shapes":[32],"directly":[33],"in":[34,66,99,129],"space,":[36],"without":[37],"relying":[38],"on":[39,112],"discretized":[40],"diffusion":[41,124],"steps,":[42],"pre-trained":[43],"teacher":[44],"models,":[45],"or":[46,93,121],"latent-space":[47],"encodings.":[48],"Our":[49],"approach":[50],"combines":[51],"TrigFlow-inspired":[53],"continuous":[54,100],"noise":[55],"schedule":[56],"with":[57,82,102],"Chamfer":[59],"Distance-based":[60],"geometric":[61,84],"loss,":[62],"providing":[63],"stable":[64],"training":[65],"high-dimensional":[67],"sets":[69],"while":[70],"avoiding":[71],"costly":[72],"Jacobian-vector":[73],"products.":[74],"This":[75],"enables":[76],"efficient":[77],"one-":[78],"to":[79],"two-step":[80],"inference":[81],"high":[83],"fidelity.":[85],"Unlike":[86],"previous":[87],"methods":[88],"require":[90],"iterative":[91],"denoising":[92],"latent":[94,126],"decoders,":[95],"ConTiCoM-3D":[96,135],"operates":[97],"entirely":[98],"time":[101],"time-conditioned":[104],"neural":[105],"network,":[106],"achieving":[107],"fast":[108],"generation.":[109,144],"Extensive":[110],"experiments":[111],"the":[113],"ShapeNet":[114],"benchmark":[115],"demonstrate":[116],"our":[118],"method":[119],"matches":[120],"surpasses":[122],"leading":[123],"models":[128],"both":[130],"quality":[131],"efficiency,":[133],"establishing":[134],"practical":[138],"solution":[139],"scalable":[141]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-28T00:00:00"}