{"id":"https://openalex.org/W4415971849","doi":"https://doi.org/10.1109/iccv51701.2025.01472","title":"SegmentDreamer: Towards High-Fidelity Text-to-3D Synthesis with Segmented Consistency Trajectory Distillation","display_name":"SegmentDreamer: Towards High-Fidelity Text-to-3D Synthesis with Segmented Consistency Trajectory Distillation","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4415971849","doi":"https://doi.org/10.1109/iccv51701.2025.01472"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51701.2025.01472","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.01472","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2507.05256","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013072634","display_name":"Jiahao Zhu","orcid":"https://orcid.org/0000-0001-8509-4744"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiahao Zhu","raw_affiliation_strings":["Sun Yat-sen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102742348","display_name":"Zixuan Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zixuan Chen","raw_affiliation_strings":["Sun Yat-sen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028380963","display_name":"Guangcong Wang","orcid":"https://orcid.org/0000-0002-6627-814X"},"institutions":[{"id":"https://openalex.org/I4396570619","display_name":"Great Bay University","ror":"https://ror.org/01hdgge16","country_code":null,"type":"education","lineage":["https://openalex.org/I4396570619"]}],"countries":[],"is_corresponding":false,"raw_author_name":"Guangcong Wang","raw_affiliation_strings":["Great Bay University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Great Bay University","institution_ids":["https://openalex.org/I4396570619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018298892","display_name":"Xiaohua Xie","orcid":"https://orcid.org/0000-0002-0310-4679"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohua Xie","raw_affiliation_strings":["Sun Yat-sen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005083930","display_name":"Yi Zhou","orcid":"https://orcid.org/0000-0001-7445-226X"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Zhou","raw_affiliation_strings":["Sun Yat-sen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5013072634"],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.30387361,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"15864","last_page":"15874"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.6956999897956848,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.6956999897956848,"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":0.12710000574588776,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.06930000334978104,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/consistency","display_name":"Consistency (knowledge bases)","score":0.734499990940094},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6938999891281128},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.652400016784668},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.40860000252723694},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.38589999079704285},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3626999855041504},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.3560999929904938},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.3472999930381775}],"concepts":[{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.734499990940094},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6938999891281128},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.652400016784668},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5921000242233276},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.42100000381469727},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.40860000252723694},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.38589999079704285},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3626999855041504},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.3560999929904938},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3472999930381775},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31700000166893005},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.3075999915599823},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29319998621940613},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.29280000925064087},{"id":"https://openalex.org/C51544822","wikidata":"https://www.wikidata.org/wiki/Q465274","display_name":"Ordinary differential equation","level":3,"score":0.29269999265670776},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2881999909877777},{"id":"https://openalex.org/C51955184","wikidata":"https://www.wikidata.org/wiki/Q1545585","display_name":"Stochastic differential equation","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C137105694","wikidata":"https://www.wikidata.org/wiki/Q3407510","display_name":"Local consistency","level":4,"score":0.2800999879837036},{"id":"https://openalex.org/C93361087","wikidata":"https://www.wikidata.org/wiki/Q4426698","display_name":"Data consistency","level":2,"score":0.2720000147819519},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.2705000042915344},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2630999982357025},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C93226319","wikidata":"https://www.wikidata.org/wiki/Q193137","display_name":"Differential (mechanical device)","level":2,"score":0.2590000033378601}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv51701.2025.01472","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.01472","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2507.05256","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.05256","pdf_url":"https://arxiv.org/pdf/2507.05256","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2507.05256","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2507.05256","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2507.05256","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.05256","pdf_url":"https://arxiv.org/pdf/2507.05256","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"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":{"Recent":[0],"advancements":[1],"in":[2,152],"text-to-3D":[3,70],"generation":[4,47],"improve":[5],"the":[6,29,63,77,86,92,101],"visual":[7,153],"quality":[8],"of":[9,65],"Score":[10],"Distillation":[11,21,82],"Sampling":[12],"(SDS)":[13],"and":[14,33,96,112,140],"its":[15],"variants":[16],"by":[17,89],"directly":[18],"connecting":[19],"Consistency":[20,80],"(CD)":[22],"to":[23,28,45,60],"score":[24],"distillation.":[25],"However,":[26],"due":[27],"imbalance":[30,87],"between":[31,94],"self-consistency":[32],"cross-consistency,":[34],"these":[35],"CD-based":[36],"methods":[37,151],"inherently":[38],"suffer":[39],"from":[40],"improper":[41],"conditional":[42],"guidance,":[43],"leading":[44],"sub-optimal":[46],"results.":[48],"To":[49],"address":[50],"this":[51],"issue,":[52],"we":[53,73,131],"present":[54],"SegmentDreamer,":[55],"a":[56,122,133,137],"novel":[57],"framework":[58],"designed":[59],"fully":[61],"unleash":[62],"potential":[64],"consistency":[66,114],"models":[67],"for":[68,136],"high-fidelity":[69,156],"generation.":[71,142],"Specifically,":[72],"reformulate":[74],"SDS":[75],"through":[76,160],"proposed":[78],"Segmented":[79],"Trajectory":[81],"(SCTD),":[83],"effectively":[84],"mitigating":[85],"issues":[88],"explicitly":[90],"defining":[91],"relationship":[93],"self-":[95],"cross-consistency.":[97],"Moreover,":[98],"SCTD":[99],"partitions":[100],"Probability":[102],"Flow":[103],"Ordinary":[104],"Differential":[105],"Equation":[106],"(PF-ODE)":[107],"trajectory":[108],"into":[109],"multiple":[110],"sub-trajectories":[111],"ensures":[113],"within":[115],"each":[116],"segment,":[117],"which":[118],"can":[119],"theoretically":[120],"provide":[121],"significantly":[123],"tighter":[124],"upper":[125],"bound":[126],"on":[127],"distillation":[128,134],"error.":[129],"Additionally,":[130],"propose":[132],"pipeline":[135],"more":[138],"swift":[139],"stable":[141],"Extensive":[143],"experiments":[144],"demonstrate":[145],"that":[146],"our":[147],"SegmentDreamer":[148],"outperforms":[149],"state-of-the-art":[150],"quality,":[154],"enabling":[155],"3D":[157,161],"asset":[158],"creation":[159],"Gaussian":[162],"Splatting":[163],"(3DGS).":[164]},"counts_by_year":[],"updated_date":"2026-05-06T06:03:25.996018","created_date":"2025-10-10T00:00:00"}
