{"id":"https://openalex.org/W4389574997","doi":"https://doi.org/10.1145/3610548.3618166","title":"Differentiable Dynamic Visible-Light Tomography","display_name":"Differentiable Dynamic Visible-Light Tomography","publication_year":2023,"publication_date":"2023-12-10","ids":{"openalex":"https://openalex.org/W4389574997","doi":"https://doi.org/10.1145/3610548.3618166"},"language":"en","primary_location":{"id":"doi:10.1145/3610548.3618166","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3610548.3618166","pdf_url":null,"source":null,"license":"cc-by-nd","license_id":"https://openalex.org/licenses/cc-by-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIGGRAPH Asia 2023 Conference Papers","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3610548.3618166","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005722947","display_name":"Kaizhang Kang","orcid":"https://orcid.org/0009-0004-4381-0510"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kaizhang Kang","raw_affiliation_strings":["State Key Lab of CAD&CG, Zhejiang Univerisity, China"],"affiliations":[{"raw_affiliation_string":"State Key Lab of CAD&CG, Zhejiang Univerisity, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033184330","display_name":"Zoubin Bi","orcid":"https://orcid.org/0009-0007-9645-8452"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zoubin Bi","raw_affiliation_strings":["State Key Lab of CAD&CG, Zhejiang Univerisity, China"],"affiliations":[{"raw_affiliation_string":"State Key Lab of CAD&CG, Zhejiang Univerisity, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101536091","display_name":"Xiang Feng","orcid":"https://orcid.org/0009-0003-4439-2253"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiang Feng","raw_affiliation_strings":["State Key Lab of CAD&CG, Zhejiang Univerisity, China"],"affiliations":[{"raw_affiliation_string":"State Key Lab of CAD&CG, Zhejiang Univerisity, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023965095","display_name":"Yaohui Dong","orcid":"https://orcid.org/0009-0005-1433-2553"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yican Dong","raw_affiliation_strings":["State Key Lab of CAD&CG, Zhejiang Univerisity, China"],"affiliations":[{"raw_affiliation_string":"State Key Lab of CAD&CG, Zhejiang Univerisity, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027671723","display_name":"Kun Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Zhou","raw_affiliation_strings":["State Key Lab of CAD&CG, Zhejiang Univerisity, China and ZJU-FaceUnity Joint Lab of Intelligent Graphics, China"],"affiliations":[{"raw_affiliation_string":"State Key Lab of CAD&CG, Zhejiang Univerisity, China and ZJU-FaceUnity Joint Lab of Intelligent Graphics, China","institution_ids":["https://openalex.org/I4210123185"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025339003","display_name":"Hongzhi Wu","orcid":"https://orcid.org/0000-0002-4404-2275"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hongzhi Wu","raw_affiliation_strings":["State Key Lab of CAD&CG, Zhejiang Univerisity, China"],"affiliations":[{"raw_affiliation_string":"State Key Lab of CAD&CG, Zhejiang Univerisity, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5005722947"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9594,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.83741794,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T11569","display_name":"Optical Coherence Tomography Applications","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/computer-science","display_name":"Computer science","score":0.7461864948272705},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6944587230682373},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6111084222793579},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5951603055000305},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.5711581707000732},{"id":"https://openalex.org/keywords/tomography","display_name":"Tomography","score":0.5306609869003296},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5072543025016785},{"id":"https://openalex.org/keywords/differentiable-function","display_name":"Differentiable function","score":0.5037516951560974},{"id":"https://openalex.org/keywords/data-acquisition","display_name":"Data acquisition","score":0.490372896194458},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.4173329472541809},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.33968430757522583},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.18246009945869446},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1123361885547638},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10740628838539124}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7461864948272705},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6944587230682373},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6111084222793579},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5951603055000305},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5711581707000732},{"id":"https://openalex.org/C163716698","wikidata":"https://www.wikidata.org/wiki/Q841267","display_name":"Tomography","level":2,"score":0.5306609869003296},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5072543025016785},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.5037516951560974},{"id":"https://openalex.org/C163985040","wikidata":"https://www.wikidata.org/wiki/Q1172399","display_name":"Data acquisition","level":2,"score":0.490372896194458},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.4173329472541809},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.33968430757522583},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.18246009945869446},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1123361885547638},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10740628838539124},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3610548.3618166","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3610548.3618166","pdf_url":null,"source":null,"license":"cc-by-nd","license_id":"https://openalex.org/licenses/cc-by-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIGGRAPH Asia 2023 Conference Papers","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3610548.3618166","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3610548.3618166","pdf_url":null,"source":null,"license":"cc-by-nd","license_id":"https://openalex.org/licenses/cc-by-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIGGRAPH Asia 2023 Conference Papers","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.5,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1925354503","https://openalex.org/W1967139652","https://openalex.org/W1974218973","https://openalex.org/W1990919278","https://openalex.org/W1991923341","https://openalex.org/W2018515743","https://openalex.org/W2027621340","https://openalex.org/W2034233362","https://openalex.org/W2076246983","https://openalex.org/W2080461625","https://openalex.org/W2098244689","https://openalex.org/W2101523447","https://openalex.org/W2157812230","https://openalex.org/W2163213698","https://openalex.org/W2331128040","https://openalex.org/W2574952845","https://openalex.org/W2612085147","https://openalex.org/W2810337759","https://openalex.org/W2957120029","https://openalex.org/W2963329659","https://openalex.org/W2964335577","https://openalex.org/W2971995780","https://openalex.org/W3024380564","https://openalex.org/W3034739481","https://openalex.org/W3092370246","https://openalex.org/W3121214277","https://openalex.org/W3131054221","https://openalex.org/W3198632145","https://openalex.org/W3207040188","https://openalex.org/W3216616977","https://openalex.org/W4285981733","https://openalex.org/W6600007113"],"related_works":["https://openalex.org/W2058965144","https://openalex.org/W2164382479","https://openalex.org/W2146343568","https://openalex.org/W98480971","https://openalex.org/W2150291671","https://openalex.org/W2013643406","https://openalex.org/W2027972911","https://openalex.org/W2157978810","https://openalex.org/W2597809628","https://openalex.org/W3013693939"],"abstract_inverted_index":{"We":[0,120],"propose":[1],"the":[2,82,102,155,170,174],"first":[3],"visible-light":[4],"tomography":[5,71],"system":[6,156],"for":[7],"real-time":[8],"acquisition":[9,40,72,123],"and":[10,26,53,73,84,99,112,117,183],"reconstruction":[11,74,118],"of":[12,33,87,125,136,154],"general":[13],"temporally-varying":[14],"3D":[15],"phenomena.":[16],"Using":[17],"a":[18,22,30,38,56,64,76,133,181],"single":[19],"high-speed":[20],"camera,":[21],"high-performance":[23],"LED":[24],"array":[25],"optical":[27],"fibers":[28],"with":[29,42,55,146,169,176,186],"total":[31],"length":[32],"5":[34],"km,":[35],"we":[36,62],"build":[37],"novel":[39,65],"setup":[41],"no":[43],"mechanical":[44],"movements":[45],"to":[46,68,75,96,109,127],"simultaneously":[47],"sample":[48],"using":[49],"1,920":[50],"interleaved":[51],"sources":[52],"detectors":[54],"complete":[57],"360":[58],"\u00b0":[59],"coverage.":[60],"Next,":[61],"introduce":[63],"differentiable":[66],"framework":[67,106],"map":[69],"both":[70,88],"carefully":[77],"designed":[78],"autoencoder.":[79],"This":[80],"allows":[81],"joint":[83],"automatic":[85],"optimization":[86],"processes":[89],"in":[90],"an":[91,122],"end-to-end":[92],"fashion,":[93],"essentially":[94],"learning":[95],"physically":[97],"compress":[98],"computationally":[100],"decompress":[101],"target":[103],"information.":[104],"Our":[105,164],"can":[107],"adapt":[108],"various":[110,161],"factors,":[111],"trade":[113],"between":[114],"capture":[115],"speed":[116,124],"quality.":[119],"achieve":[121],"up":[126],"36.8":[128],"volumes":[129],"per":[130],"second":[131],"at":[132,180],"spatial":[134],"resolution":[135],"32":[137],"\u00d7":[138,140],"128":[139],"128;":[141],"each":[142],"volume":[143],"is":[144,157],"captured":[145],"as":[147,149],"few":[148],"8":[150],"images.":[151],"The":[152],"effectiveness":[153],"demonstrated":[158],"on":[159,179],"acquiring":[160],"dynamic":[162],"scenes.":[163],"results":[165],"are":[166],"also":[167],"validated":[168],"reconstructions":[171],"computed":[172],"from":[173],"measurements":[175],"one":[177],"source":[178],"time,":[182],"compare":[184],"favorably":[185],"state-of-the-art":[187],"techniques.":[188]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}