{"id":"https://openalex.org/W4390872147","doi":"https://doi.org/10.1109/iccv51070.2023.01987","title":"DDP: Diffusion Model for Dense Visual Prediction","display_name":"DDP: Diffusion Model for Dense Visual Prediction","publication_year":2023,"publication_date":"2023-10-01","ids":{"openalex":"https://openalex.org/W4390872147","doi":"https://doi.org/10.1109/iccv51070.2023.01987"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51070.2023.01987","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51070.2023.01987","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF International Conference on Computer Vision (ICCV)","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/A5034586348","display_name":"Yuanfeng Ji","orcid":null},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Yuanfeng Ji","raw_affiliation_strings":["The University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100457637","display_name":"Zhe Chen","orcid":"https://orcid.org/0000-0001-5004-8975"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhe Chen","raw_affiliation_strings":["Nanjing University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041031140","display_name":"Enze Xie","orcid":"https://orcid.org/0000-0001-6890-1049"},"institutions":[{"id":"https://openalex.org/I4210159102","display_name":"Huawei Technologies (Sweden)","ror":"https://ror.org/0500fyd17","country_code":"SE","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210159102"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Enze Xie","raw_affiliation_strings":["Huawei Noah’s Ark Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Noah’s Ark Lab","institution_ids":["https://openalex.org/I4210159102"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003882618","display_name":"Lanqing Hong","orcid":"https://orcid.org/0000-0003-2752-5942"},"institutions":[{"id":"https://openalex.org/I4210159102","display_name":"Huawei Technologies (Sweden)","ror":"https://ror.org/0500fyd17","country_code":"SE","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210159102"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Lanqing Hong","raw_affiliation_strings":["Huawei Noah’s Ark Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Noah’s Ark Lab","institution_ids":["https://openalex.org/I4210159102"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027234036","display_name":"Xihui Liu","orcid":"https://orcid.org/0000-0002-1791-8745"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xihui Liu","raw_affiliation_strings":["The University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085689370","display_name":"Zhaoqiang Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210159102","display_name":"Huawei Technologies (Sweden)","ror":"https://ror.org/0500fyd17","country_code":"SE","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210159102"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Zhaoqiang Liu","raw_affiliation_strings":["Huawei Noah’s Ark Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Noah’s Ark Lab","institution_ids":["https://openalex.org/I4210159102"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061696740","display_name":"Tong L\u00fc","orcid":"https://orcid.org/0000-0002-7051-5347"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Lu","raw_affiliation_strings":["Nanjing University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103196797","display_name":"Zhenguo Li","orcid":"https://orcid.org/0000-0002-8492-3069"},"institutions":[{"id":"https://openalex.org/I4210159102","display_name":"Huawei Technologies (Sweden)","ror":"https://ror.org/0500fyd17","country_code":"SE","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210159102"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Zhenguo Li","raw_affiliation_strings":["Huawei Noah’s Ark Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Noah’s Ark Lab","institution_ids":["https://openalex.org/I4210159102"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100752686","display_name":"Ping Luo","orcid":"https://orcid.org/0000-0002-6685-7950"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]},{"id":"https://openalex.org/I4391012619","display_name":"Shanghai Artificial Intelligence Laboratory","ror":"https://ror.org/03wkvpx79","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391012619"]},{"id":"https://openalex.org/I4210122302","display_name":"ShangHai JiAi Genetics & IVF Institute","ror":"https://ror.org/02rgbry52","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210122302"]}],"countries":["CN","HK"],"is_corresponding":false,"raw_author_name":"Ping Luo","raw_affiliation_strings":["The University of Hong Kong","Shanghai AI Laboratory"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Hong Kong","institution_ids":["https://openalex.org/I889458895"]},{"raw_affiliation_string":"Shanghai AI Laboratory","institution_ids":["https://openalex.org/I4210122302","https://openalex.org/I4391012619"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5034586348"],"corresponding_institution_ids":["https://openalex.org/I889458895"],"apc_list":null,"apc_paid":null,"fwci":14.9633,"has_fulltext":false,"cited_by_count":129,"citation_normalized_percentile":{"value":0.99410776,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"21684","last_page":"21695"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9990000128746033,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9990000128746033,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9988999962806702,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9984999895095825,"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/computer-science","display_name":"Computer science","score":0.740690290927887},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.7203152179718018},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.692108154296875},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6920136213302612},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6797506809234619},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5610511302947998},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4672080874443054},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4518080949783325},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.43682241439819336},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4358384609222412},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3895896375179291},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3578258752822876},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.25259822607040405},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08791375160217285}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.740690290927887},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7203152179718018},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.692108154296875},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6920136213302612},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6797506809234619},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5610511302947998},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4672080874443054},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4518080949783325},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.43682241439819336},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4358384609222412},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3895896375179291},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3578258752822876},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.25259822607040405},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08791375160217285},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccv51070.2023.01987","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51070.2023.01987","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7200000286102295,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":119,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W764651262","https://openalex.org/W1901129140","https://openalex.org/W1923184257","https://openalex.org/W2115579991","https://openalex.org/W2340897893","https://openalex.org/W2412782625","https://openalex.org/W2560023338","https://openalex.org/W2565639579","https://openalex.org/W2604505099","https://openalex.org/W2737258237","https://openalex.org/W2787091153","https://openalex.org/W2884822772","https://openalex.org/W2908510526","https://openalex.org/W2956805085","https://openalex.org/W2962960377","https://openalex.org/W2963073614","https://openalex.org/W2963118571","https://openalex.org/W2963488291","https://openalex.org/W2963917315","https://openalex.org/W2990946490","https://openalex.org/W3035461736","https://openalex.org/W3090204745","https://openalex.org/W3097217077","https://openalex.org/W3102961490","https://openalex.org/W3109395584","https://openalex.org/W3121370741","https://openalex.org/W3122239467","https://openalex.org/W3131500599","https://openalex.org/W3138516171","https://openalex.org/W3155072588","https://openalex.org/W3159637683","https://openalex.org/W3167695527","https://openalex.org/W3170841864","https://openalex.org/W3173727695","https://openalex.org/W3182978476","https://openalex.org/W3188511781","https://openalex.org/W3217727157","https://openalex.org/W4214520160","https://openalex.org/W4214893857","https://openalex.org/W4221146106","https://openalex.org/W4224035735","https://openalex.org/W4224259431","https://openalex.org/W4225949693","https://openalex.org/W4226000809","https://openalex.org/W4226125322","https://openalex.org/W4226401733","https://openalex.org/W4281485151","https://openalex.org/W4281632497","https://openalex.org/W4281702815","https://openalex.org/W4281781228","https://openalex.org/W4289283268","https://openalex.org/W4296957262","https://openalex.org/W4300425011","https://openalex.org/W4302307901","https://openalex.org/W4307416138","https://openalex.org/W4308023490","https://openalex.org/W4310561605","https://openalex.org/W4310695675","https://openalex.org/W4312443924","https://openalex.org/W4312641958","https://openalex.org/W4312815172","https://openalex.org/W4312933868","https://openalex.org/W4318348481","https://openalex.org/W4319300669","https://openalex.org/W4321393095","https://openalex.org/W4322760941","https://openalex.org/W4323338514","https://openalex.org/W4383066393","https://openalex.org/W4386071839","https://openalex.org/W4386076222","https://openalex.org/W4386723894","https://openalex.org/W4390872705","https://openalex.org/W4390873752","https://openalex.org/W6679045638","https://openalex.org/W6685261749","https://openalex.org/W6718379498","https://openalex.org/W6745560452","https://openalex.org/W6756392615","https://openalex.org/W6757817989","https://openalex.org/W6760782946","https://openalex.org/W6764350350","https://openalex.org/W6766261854","https://openalex.org/W6778946027","https://openalex.org/W6779823529","https://openalex.org/W6783713337","https://openalex.org/W6788990321","https://openalex.org/W6795288823","https://openalex.org/W6796767996","https://openalex.org/W6797399245","https://openalex.org/W6797784111","https://openalex.org/W6798837711","https://openalex.org/W6803556390","https://openalex.org/W6804703708","https://openalex.org/W6804954230","https://openalex.org/W6805335523","https://openalex.org/W6809665764","https://openalex.org/W6809885388","https://openalex.org/W6810240388","https://openalex.org/W6810361948","https://openalex.org/W6810661541","https://openalex.org/W6810793953","https://openalex.org/W6810940779","https://openalex.org/W6838393215","https://openalex.org/W6838400046","https://openalex.org/W6838639034","https://openalex.org/W6838738615","https://openalex.org/W6838785959","https://openalex.org/W6843567762","https://openalex.org/W6844872470","https://openalex.org/W6846033198","https://openalex.org/W6846258481","https://openalex.org/W6846341140","https://openalex.org/W6846598164","https://openalex.org/W6846611385","https://openalex.org/W6847190699","https://openalex.org/W6849390846","https://openalex.org/W6850292659","https://openalex.org/W6850346274"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W2356597680","https://openalex.org/W3103844505","https://openalex.org/W2163278254","https://openalex.org/W155708904","https://openalex.org/W1574213390","https://openalex.org/W4388446985","https://openalex.org/W4301042974"],"abstract_inverted_index":{"We":[0,97,147],"propose":[1],"a":[2,21,32,155],"simple,":[3],"efficient,":[4],"yet":[5],"powerful":[6],"framework":[7],"for":[8,25],"dense":[9,68],"visual":[10],"predictions":[11],"based":[12],"on":[13,101,117,131,138,145],"the":[14,38,46,51,122],"conditional":[15],"diffusion":[16,48],"pipeline.":[17,54],"Our":[18],"approach":[19,151],"follows":[20],"\"noise-to-map\"":[22],"generative":[23],"paradigm":[24],"prediction":[26,69],"by":[27,37],"progressively":[28],"removing":[29],"noise":[30],"from":[31],"random":[33],"Gaussian":[34],"distribution,":[35],"guided":[36],"image.":[39],"The":[40],"method,":[41],"called":[42],"DDP,":[43],"efficiently":[44],"extends":[45],"denoising":[47],"process":[49],"into":[50],"modern":[52],"perception":[53],"Without":[55],"task-specific":[56],"design":[57],"and":[58,74,87,140,158],"architecture":[59],"customization,":[60],"DDP":[61,79,111],"is":[62],"easy":[63],"to":[64,66,92,121],"generalize":[65],"most":[67],"tasks,":[70],"e.g.,":[71],"semantic":[72,127],"segmentation":[73,128,135],"depth":[75,141],"estimation.":[76],"In":[77],"addition,":[78],"shows":[80],"attractive":[81],"properties":[82],"such":[83],"as":[84,154],"dynamic":[85],"inference":[86],"uncertainty":[88],"awareness,":[89],"in":[90],"contrast":[91],"previous":[93],"single-step":[94],"discriminative":[95],"methods.":[96],"show":[98],"top":[99],"results":[100],"three":[102],"representative":[103],"tasks":[104],"with":[105],"six":[106],"diverse":[107],"benchmarks,":[108],"without":[109],"tricks,":[110],"achieves":[112],"state-of-the-art":[113],"or":[114],"competitive":[115],"performance":[116],"each":[118],"task":[119],"compared":[120],"specialist":[123],"counterparts.":[124],"For":[125],"example,":[126],"(83.9":[129],"mIoU":[130,137],"Cityscapes),":[132],"BEV":[133],"map":[134],"(70.6":[136],"nuScenes),":[139],"estimation":[142],"(0.05":[143],"REL":[144],"KITTI).":[146],"hope":[148],"that":[149],"our":[150],"will":[152],"serve":[153],"solid":[156],"baseline":[157],"facilitate":[159],"future":[160],"research.":[161]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":68},{"year":2024,"cited_by_count":52},{"year":2023,"cited_by_count":3}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}