{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T09:34:37Z","timestamp":1761989677299,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":22,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,6,14]],"date-time":"2022-06-14T00:00:00Z","timestamp":1655164800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Research Foundation Flanders","award":["1SA7919N"],"award-info":[{"award-number":["1SA7919N"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,6,14]]},"DOI":"10.1145\/3524273.3532890","type":"proceedings-article","created":{"date-parts":[[2022,8,5]],"date-time":"2022-08-05T22:23:21Z","timestamp":1659738201000},"page":"221-226","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["SILVR"],"prefix":"10.1145","author":[{"given":"Martijn","family":"Courteaux","sequence":"first","affiliation":[{"name":"Ghent University - imec, Zwijnaarde, Oost-Vlaanderen, Belgium"}]},{"given":"Julie","family":"Artois","sequence":"additional","affiliation":[{"name":"Ghent University - imec, Zwijnaarde, Oost-Vlaanderen, Belgium"}]},{"given":"Stijn","family":"De Pauw","sequence":"additional","affiliation":[{"name":"Ghent University - imec, Zwijnaarde, Oost-Vlaanderen, Belgium"}]},{"given":"Peter","family":"Lambert","sequence":"additional","affiliation":[{"name":"Ghent University - imec, Zwijnaarde, Oost-Vlaanderen, Belgium"}]},{"given":"Glenn","family":"Van Wallendael","sequence":"additional","affiliation":[{"name":"Ghent University - imec, Zwijnaarde, Oost-Vlaanderen, Belgium"}]}],"member":"320","published-online":{"date-parts":[[2022,8,5]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"ISO\/IEC JTC 1\/SC 29\/WG 11. 2020. Common Test Conditions for Immersive Video [N19214].  ISO\/IEC JTC 1\/SC 29\/WG 11. 2020. Common Test Conditions for Immersive Video [N19214]."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-016-0902-9"},{"key":"e_1_3_2_1_3_1","volume-title":"Joint 2d-3d-semantic data for indoor scene understanding. CoRR abs\/1702.01105","author":"Armeni Iro","year":"2017","unstructured":"Iro Armeni , Sasha Sax , Amir R Zamir , and Silvio Savarese . 2017. Joint 2d-3d-semantic data for indoor scene understanding. CoRR abs\/1702.01105 ( 2017 ). arXiv:1702.01105 http:\/\/arxiv.org\/abs\/1702.01105 Iro Armeni, Sasha Sax, Amir R Zamir, and Silvio Savarese. 2017. Joint 2d-3d-semantic data for indoor scene understanding. CoRR abs\/1702.01105 (2017). arXiv:1702.01105 http:\/\/arxiv.org\/abs\/1702.01105"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3388536.3407878"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3355056.3364593"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3386569.3392485"},{"key":"e_1_3_2_1_7_1","volume-title":"Matterport3D: Learning from RGB-D Data in Indoor Environments. CoRR abs\/1709.06158","author":"Chang Angel","year":"2017","unstructured":"Angel Chang , Angela Dai , Thomas Funkhouser , Maciej Halber , Matthias Niessner , Manolis Savva , Shuran Song , Andy Zeng , and Yinda Zhang . 2017. Matterport3D: Learning from RGB-D Data in Indoor Environments. CoRR abs\/1709.06158 ( 2017 ). arXiv:1709.06158 http:\/\/arxiv.org\/abs\/1709.06158 Angel Chang, Angela Dai, Thomas Funkhouser, Maciej Halber, Matthias Niessner, Manolis Savva, Shuran Song, Andy Zeng, and Yinda Zhang. 2017. Matterport3D: Learning from RGB-D Data in Indoor Environments. CoRR abs\/1709.06158 (2017). arXiv:1709.06158 http:\/\/arxiv.org\/abs\/1709.06158"},{"key":"e_1_3_2_1_8_1","volume-title":"DeepView: View Synthesis with Learned Gradient Descent. CoRR abs\/1906.07316","author":"Flynn John","year":"2019","unstructured":"John Flynn , Michael Broxton , Paul E. Debevec , Matthew DuVall , Graham Fyffe , Ryan S. Overbeck , Noah Snavely , and Richard Tucker . 2019. DeepView: View Synthesis with Learned Gradient Descent. CoRR abs\/1906.07316 ( 2019 ). arXiv:1906.07316 http:\/\/arxiv.org\/abs\/1906.07316 John Flynn, Michael Broxton, Paul E. Debevec, Matthew DuVall, Graham Fyffe, Ryan S. Overbeck, Noah Snavely, and Richard Tucker. 2019. DeepView: View Synthesis with Learned Gradient Descent. CoRR abs\/1906.07316 (2019). arXiv:1906.07316 http:\/\/arxiv.org\/abs\/1906.07316"},{"key":"e_1_3_2_1_9_1","unstructured":"Blender Foundation. 2022. Agent 327: Barbershop. Blender Studio. https:\/\/studio.blender.org\/  Blender Foundation. 2022. Agent 327: Barbershop. Blender Studio. https:\/\/studio.blender.org\/"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3458305.3478450"},{"key":"e_1_3_2_1_11_1","volume-title":"Learning-Based View Synthesis for Light Field Cameras. ACM Transactions on Graphics (Proceedings of SIGGRAPH Asia 2016) 35, 6","author":"Kalantari Nima Khademi","year":"2016","unstructured":"Nima Khademi Kalantari , Ting-Chun Wang , and Ravi Ramamoorthi . 2016. Learning-Based View Synthesis for Light Field Cameras. ACM Transactions on Graphics (Proceedings of SIGGRAPH Asia 2016) 35, 6 ( 2016 ). Nima Khademi Kalantari, Ting-Chun Wang, and Ravi Ramamoorthi. 2016. Learning-Based View Synthesis for Light Field Cameras. ACM Transactions on Graphics (Proceedings of SIGGRAPH Asia 2016) 35, 6 (2016)."},{"volume-title":"The (New) Stanford Light Field Archive","author":"Laboratory Computer Graphics","key":"e_1_3_2_1_12_1","unstructured":"Computer Graphics Laboratory . 2008. The (New) Stanford Light Field Archive . Stanford University . http:\/\/lightfield.stanford.edu\/lfs.html Computer Graphics Laboratory. 2008. The (New) Stanford Light Field Archive. Stanford University. http:\/\/lightfield.stanford.edu\/lfs.html"},{"key":"e_1_3_2_1_13_1","volume-title":"Stanford Lytro Light Field Archive","author":"Laboratory Computer Graphics","year":"2016","unstructured":"Computer Graphics Laboratory . 2008. Stanford Lytro Light Field Archive . Stanford University . http:\/\/lightfields.stanford.edu\/LF 2016 .html Computer Graphics Laboratory. 2008. Stanford Lytro Light Field Archive. Stanford University. http:\/\/lightfields.stanford.edu\/LF2016.html"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3304109.3325815"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3503250"},{"key":"e_1_3_2_1_16_1","volume-title":"Instant Neural Graphics Primitives with a Multiresolution Hash Encoding. arXiv:2201.05989 (Jan","author":"M\u00fcller Thomas","year":"2022","unstructured":"Thomas M\u00fcller , Alex Evans , Christoph Schied , and Alexander Keller . 2022. Instant Neural Graphics Primitives with a Multiresolution Hash Encoding. arXiv:2201.05989 (Jan . 2022 ). Thomas M\u00fcller, Alex Evans, Christoph Schied, and Alexander Keller. 2022. Instant Neural Graphics Primitives with a Multiresolution Hash Encoding. arXiv:2201.05989 (Jan. 2022)."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3272127.3275031"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3355089.3356555"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/566654.566575"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01072"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.221"},{"key":"e_1_3_2_1_22_1","unstructured":"Richard Tucker and Noah Snavely. 2018. RealEstate10K. Google. https:\/\/google.github.io\/realestate10k\/  Richard Tucker and Noah Snavely. 2018. RealEstate10K. Google. https:\/\/google.github.io\/realestate10k\/"}],"event":{"name":"MMSys '22: 13th ACM Multimedia Systems Conference","sponsor":["SIGMM ACM Special Interest Group on Multimedia","SIGCOMM ACM Special Interest Group on Data Communication","SIGMOBILE ACM Special Interest Group on Mobility of Systems, Users, Data and Computing"],"location":"Athlone Ireland","acronym":"MMSys '22"},"container-title":["Proceedings of the 13th ACM Multimedia Systems Conference"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3524273.3532890","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3524273.3532890","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:31:06Z","timestamp":1750188666000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3524273.3532890"}},"subtitle":["a synthetic immersive large-volume plenoptic dataset"],"short-title":[],"issued":{"date-parts":[[2022,6,14]]},"references-count":22,"alternative-id":["10.1145\/3524273.3532890","10.1145\/3524273"],"URL":"https:\/\/doi.org\/10.1145\/3524273.3532890","relation":{},"subject":[],"published":{"date-parts":[[2022,6,14]]},"assertion":[{"value":"2022-08-05","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}