{"id":"https://openalex.org/W4411631937","doi":"https://doi.org/10.1145/3731715.3733371","title":"Learning 3D Volume Cloud from Single Image","display_name":"Learning 3D Volume Cloud from Single Image","publication_year":2025,"publication_date":"2025-06-25","ids":{"openalex":"https://openalex.org/W4411631937","doi":"https://doi.org/10.1145/3731715.3733371"},"language":"en","primary_location":{"id":"doi:10.1145/3731715.3733371","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3731715.3733371","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 International Conference on Multimedia Retrieval","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/A5102655017","display_name":"Yuhang Cheng","orcid":"https://orcid.org/0009-0006-5801-2911"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhang Cheng","raw_affiliation_strings":["Southwest University, Chongqing, China"],"raw_orcid":"https://orcid.org/0009-0006-5801-2911","affiliations":[{"raw_affiliation_string":"Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yu Zhang","orcid":"https://orcid.org/0009-0000-5199-3426"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Zhang","raw_affiliation_strings":["Southwest University, Chongqing, China"],"raw_orcid":"https://orcid.org/0009-0000-5199-3426","affiliations":[{"raw_affiliation_string":"Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040565849","display_name":"Xiaogang Wang","orcid":"https://orcid.org/0000-0002-8402-7504"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaogang Wang","raw_affiliation_strings":["Southwest University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-8402-7504","affiliations":[{"raw_affiliation_string":"Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I142108993"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23920686,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"117","last_page":"125"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9995999932289124,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9959999918937683,"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":0.994700014591217,"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/cloud-computing","display_name":"Cloud computing","score":0.6862185001373291},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6485867500305176},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.6433910131454468},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4718344807624817},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43205732107162476},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41048580408096313},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.354879230260849},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.06107929348945618},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.05960690975189209}],"concepts":[{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.6862185001373291},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6485867500305176},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.6433910131454468},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4718344807624817},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43205732107162476},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41048580408096313},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.354879230260849},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.06107929348945618},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.05960690975189209},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3731715.3733371","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3731715.3733371","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G81769915","display_name":null,"funder_award_id":"SWU120076","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"}],"funders":[{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1850744708","https://openalex.org/W1901129140","https://openalex.org/W1921523184","https://openalex.org/W1973218627","https://openalex.org/W2029315739","https://openalex.org/W2033664843","https://openalex.org/W2036812736","https://openalex.org/W2044068224","https://openalex.org/W2058945810","https://openalex.org/W2104231178","https://openalex.org/W2133665775","https://openalex.org/W2169328021","https://openalex.org/W2336763592","https://openalex.org/W2354934882","https://openalex.org/W2783879794","https://openalex.org/W2962785568","https://openalex.org/W2986023562","https://openalex.org/W3135367836","https://openalex.org/W3158278368","https://openalex.org/W3185113610","https://openalex.org/W4226317937","https://openalex.org/W4237648096","https://openalex.org/W4289785095","https://openalex.org/W4312933868","https://openalex.org/W4321594000","https://openalex.org/W4353007647","https://openalex.org/W4386076018","https://openalex.org/W4386840067","https://openalex.org/W4389347744","https://openalex.org/W6629747460","https://openalex.org/W6640963894","https://openalex.org/W6641966045","https://openalex.org/W6677698182","https://openalex.org/W6678815747","https://openalex.org/W6679319196","https://openalex.org/W6745512297","https://openalex.org/W6780226713","https://openalex.org/W6843813467","https://openalex.org/W6850245686"],"related_works":["https://openalex.org/W4244478748","https://openalex.org/W3150465815","https://openalex.org/W4223488648","https://openalex.org/W2134969820","https://openalex.org/W2251605416","https://openalex.org/W1997222214","https://openalex.org/W2560439919","https://openalex.org/W4389340727","https://openalex.org/W2802581102","https://openalex.org/W4205786897"],"abstract_inverted_index":{"Three-dimensional":[0],"(3D)":[1],"cloud":[2,59,82,112,135,173,186,198,220],"modeling":[3,39],"plays":[4],"a":[5,25,42,51,81,85,95,103,110,122,141,171,194],"pivotal":[6],"role":[7],"in":[8,216],"advancing":[9],"atmospheric":[10],"models":[11],"and":[12,84,139,203,209],"enhancing":[13],"natural":[14],"phenomena":[15],"visualization":[16],"systems.":[17],"Nevertheless,":[18],"the":[19,116,129,159,178,207],"high-quality":[20],"reconstruction":[21,60,113,130,221],"of":[22,162,197,211],"clouds":[23],"remains":[24],"significant":[26],"challenge,":[27],"primarily":[28],"due":[29],"to":[30,45,108,120,157],"their":[31],"inherent":[32,160],"heterogeneous":[33],"nature":[34],"as":[35],"volumetric":[36,123],"media.":[37],"Image-based":[38],"approaches":[40],"offer":[41],"promising":[43],"solution":[44],"this":[46],"challenge.":[47],"This":[48,182],"paper":[49],"presents":[50],"novel":[52,91],"two-stage":[53,214],"neural":[54],"network":[55,72,215],"architecture":[56],"for":[57,153,176],"3D":[58,111,219],"from":[61,94,166,222],"single":[62,96],"image.":[63,98],"The":[64,99],"first":[65],"stage":[66,101],"introduces":[67],"an":[68],"innovative":[69],"view":[70],"synthesis":[71],"built":[73],"upon":[74],"Stable":[75],"Diffusion,":[76],"incorporating":[77],"two":[78],"specialized":[79],"modules:":[80],"mapper":[83,180],"viewpoint":[86,179],"mapper,":[87],"which":[88],"collaboratively":[89],"generate":[90],"perspective":[92],"views":[93],"input":[97],"second":[100],"implements":[102],"physics-based":[104],"differentiable":[105],"rendering":[106],"framework":[107],"construct":[109],"network,":[114],"leveraging":[115],"synthesized":[117],"multi-view":[118,185],"images":[119,187],"optimize":[121],"density":[124,136],"grid":[125],"representation.":[126],"To":[127],"enhance":[128],"fidelity,":[131],"we":[132,169],"integrate":[133],"real-world":[134],"distribution":[137],"statistics":[138],"implement":[140],"post-processing":[142],"refinement":[143],"using":[144],"Perlin-Worley":[145],"noise":[146],"combined":[147],"with":[148,188],"Fractal":[149],"Brownian":[150],"Motion":[151],"(FBM)":[152],"erosion":[154],"effects.":[155],"Additionally,":[156],"mitigate":[158],"limitations":[161],"geometric":[163],"information":[164],"extraction":[165],"single-view":[167,223],"images,":[168],"developed":[170],"comprehensive":[172],"simulation":[174],"dataset":[175,183],"pre-training":[177],"module.":[181],"encompasses":[184],"corresponding":[189],"camera":[190],"extrinsic":[191],"parameters,":[192],"capturing":[193],"diverse":[195],"range":[196],"formations.":[199],"Extensive":[200],"quantitative":[201],"evaluations":[202],"qualitative":[204],"assessments":[205],"demonstrate":[206],"efficacy":[208],"potential":[210],"our":[212],"proposed":[213],"achieving":[217],"accurate":[218],"images.":[224]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}