{"id":"https://openalex.org/W2964621349","doi":"https://doi.org/10.24963/ijcai.2019/517","title":"Deep Cascade Generation on Point Sets","display_name":"Deep Cascade Generation on Point Sets","publication_year":2019,"publication_date":"2019-07-28","ids":{"openalex":"https://openalex.org/W2964621349","doi":"https://doi.org/10.24963/ijcai.2019/517","mag":"2964621349"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2019/517","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/517","pdf_url":"https://www.ijcai.org/proceedings/2019/0517.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2019/0517.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5115600316","display_name":"Kaiqi Wang","orcid":"https://orcid.org/0009-0008-5962-3647"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaiqi Wang","raw_affiliation_strings":["South China University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China University of Technology","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100649535","display_name":"Ke Chen","orcid":"https://orcid.org/0000-0003-0928-5199"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Chen","raw_affiliation_strings":["South China University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China University of Technology","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065964089","display_name":"Kui Jia","orcid":"https://orcid.org/0000-0003-2661-5700"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kui Jia","raw_affiliation_strings":["South China University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China University of Technology","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":6.7116,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.98274569,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3726","last_page":"3732"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":1.0,"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":1.0,"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":0.9983999729156494,"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"}},{"id":"https://openalex.org/T11245","display_name":"Advanced Numerical Analysis Techniques","score":0.9962000250816345,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.7795965671539307},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7099190354347229},{"id":"https://openalex.org/keywords/cascade","display_name":"Cascade","score":0.6326025128364563},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.617566704750061},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5740298628807068},{"id":"https://openalex.org/keywords/maxima-and-minima","display_name":"Maxima and minima","score":0.5156046748161316},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.46682897210121155},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4634435474872589},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4452284872531891},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4304133951663971},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39398622512817383},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3888886272907257},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.3858378529548645},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3326399624347687},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19772902131080627},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.0795794427394867}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7795965671539307},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7099190354347229},{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.6326025128364563},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.617566704750061},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5740298628807068},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.5156046748161316},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.46682897210121155},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4634435474872589},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4452284872531891},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4304133951663971},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39398622512817383},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3888886272907257},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.3858378529548645},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3326399624347687},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19772902131080627},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0795794427394867},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2019/517","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/517","pdf_url":"https://www.ijcai.org/proceedings/2019/0517.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2019/517","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/517","pdf_url":"https://www.ijcai.org/proceedings/2019/0517.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.7699999809265137}],"awards":[{"id":"https://openalex.org/G3126794548","display_name":"\u57fa\u4e8e\u51e0\u4f55\u548c\u7269\u7406\u6027\u8d28\u7684\u6df1\u5ea6\u6a21\u578b\u4f18\u5316\u7814\u7a76","funder_award_id":"61771201","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6915813291","display_name":null,"funder_award_id":"2017ZT07X183","funder_id":"https://openalex.org/F4320323059","funder_display_name":"South China University of Technology"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323059","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2964621349.pdf","grobid_xml":"https://content.openalex.org/works/W2964621349.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1662382123","https://openalex.org/W2008073424","https://openalex.org/W2016053056","https://openalex.org/W2072747111","https://openalex.org/W2194775991","https://openalex.org/W2342277278","https://openalex.org/W2495603374","https://openalex.org/W2558748708","https://openalex.org/W2560609797","https://openalex.org/W2560722161","https://openalex.org/W2603429625","https://openalex.org/W2748099314","https://openalex.org/W2796426482","https://openalex.org/W2886499109","https://openalex.org/W2897619360","https://openalex.org/W2914821954","https://openalex.org/W2950701417","https://openalex.org/W2962778872","https://openalex.org/W2963121255","https://openalex.org/W2963446712","https://openalex.org/W2963719584","https://openalex.org/W2963735494","https://openalex.org/W2963739349","https://openalex.org/W2963942118","https://openalex.org/W2964015378","https://openalex.org/W2964137676","https://openalex.org/W2964321699","https://openalex.org/W2979750740","https://openalex.org/W4238089689","https://openalex.org/W4394671432"],"related_works":["https://openalex.org/W4238897586","https://openalex.org/W435179959","https://openalex.org/W2619091065","https://openalex.org/W2059640416","https://openalex.org/W1490753184","https://openalex.org/W2284465472","https://openalex.org/W2291782699","https://openalex.org/W1993948687","https://openalex.org/W2000169967","https://openalex.org/W2112883198"],"abstract_inverted_index":{"This":[0],"paper":[1,65],"proposes":[2,66],"a":[3,15,20,26,67,85,100,128,146],"deep":[4],"cascade":[5,69,139],"network":[6],"to":[7,31,46,83,111,164],"generate":[8,84],"3D":[9],"geometry":[10],"of":[11,19,22,41,48,105,138,160],"an":[12],"object":[13,43],"on":[14,71,99,151,168],"point":[16,72,80],"cloud,":[17],"consisting":[18],"set":[21,81],"permutation-insensitive":[23],"points.":[24],"Such":[25],"surface":[27,108],"representation":[28],"is":[29,109],"easy":[30],"learn":[32],"from,":[33],"but":[34],"inhibits":[35],"exploiting":[36],"rich":[37,59],"low-dimensional":[38],"topological":[39],"manifolds":[40],"the":[42,78,113,135,152,161,165],"shape":[44,88,171,174],"due":[45],"lack":[47],"geometric":[49,122],"connectivity.":[50],"For":[51],"benefiting":[52],"from":[53,115],"its":[54],"simple":[55],"structure":[56],"yet":[57],"utilizing":[58],"neighborhood":[60,97],"information":[61],"across":[62],"points,":[63],"this":[64],"two-stage":[68],"model":[70,126,163],"sets.":[73],"Specifically,":[74],"our":[75,125],"method":[76],"adopts":[77],"state-of-the-art":[79,166],"autoencoder":[82],"sparsely":[86],"coarse":[87],"first,":[89],"and":[90,173],"then":[91],"locally":[92],"refines":[93],"it":[94],"by":[95,119],"encoding":[96],"connectivity":[98],"graph":[101],"representation.":[102],"An":[103],"ensemble":[104],"sparse":[106],"refined":[107],"designed":[110],"alleviate":[112],"suffering":[114],"local":[116],"minima":[117],"caused":[118],"modeling":[120],"complex":[121],"manifolds.":[123],"Moreover,":[124],"develops":[127],"dynamically-weighted":[129],"loss":[130],"function":[131],"for":[132],"jointly":[133],"penalizing":[134],"generation":[136],"output":[137],"levels":[140],"at":[141],"different":[142],"training":[143],"stages":[144],"in":[145],"coarse-to-fine":[147],"manner.":[148],"Comparative":[149],"evaluation":[150],"publicly":[153],"benchmarking":[154],"ShapeNet":[155],"dataset":[156],"demonstrates":[157],"superior":[158],"performance":[159],"proposed":[162],"methods":[167],"both":[169],"single-view":[170],"reconstruction":[172],"autoencoding":[175],"applications.":[176]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}