{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,26]],"date-time":"2026-01-26T19:42:17Z","timestamp":1769456537080,"version":"3.49.0"},"publisher-location":"Cham","reference-count":32,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030012519","type":"print"},{"value":"9783030012526","type":"electronic"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-030-01252-6_35","type":"book-chapter","created":{"date-parts":[[2018,10,5]],"date-time":"2018-10-05T13:48:05Z","timestamp":1538747285000},"page":"591-607","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["Volumetric Performance Capture from Minimal Camera Viewpoints"],"prefix":"10.1007","author":[{"given":"Andrew","family":"Gilbert","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marco","family":"Volino","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John","family":"Collomosse","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adrian","family":"Hilton","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,10,6]]},"reference":[{"issue":"3","key":"35_CR1","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1080\/2151237X.2009.10129284","volume":"14","author":"J Starck","year":"2009","unstructured":"Starck, J., Kilner, J., Hilton, A.: A free-viewpoint video renderer. J. Graph. GPU Game Tools 14(3), 57\u201372 (2009)","journal-title":"J. Graph. GPU Game Tools"},{"key":"35_CR2","doi-asserted-by":"crossref","unstructured":"Tsiminaki, V., Franco, J., Boyer, E.: High resolution 3D shape texture from multiple videos. In: Proceedings of the Computer Vision and Pattern Recognition (CVPR) (2014)","DOI":"10.1109\/CVPR.2014.195"},{"key":"35_CR3","unstructured":"Volino, M., Casas, D., Collomosse, J., Hilton, A.: 4D for interactive character appearance. In: Computer Graphics Forum (Proceedings of Eurographics 2014) (2014)"},{"issue":"4","key":"35_CR4","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1145\/2766945","volume":"34","author":"A Collet","year":"2015","unstructured":"Collet, A., et al.: High-quality streamable free-viewpoint video. ACM Trans. Graph. (TOG) 34(4), 69 (2015)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"35_CR5","unstructured":"Grauman, K., Shakhnarovich, G., Darrell, T.: A Bayesian approach to image-based visual hull reconstruction. In: Proceedings of the CVPR (2003)"},{"issue":"1","key":"35_CR6","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1007\/s11263-010-0413-z","volume":"93","author":"JY Guillemaut","year":"2011","unstructured":"Guillemaut, J.Y., Hilton, A.: Joint multi-layer segmentation and reconstruction for free-viewpoint video applications. Int. J. Comput. Vis. 93(1), 73\u2013100 (2011)","journal-title":"Int. J. Comput. Vis."},{"key":"35_CR7","unstructured":"Casas, D., Huang, P., Hilton, A.: Surface-based character animation. In: Magnor, M., Grau, O., Sorkine-Hornung, O., Theobalt, C. (eds.) Digital Representations of the Real World: How to Capture, Model, and Render Visual Reality, pp. 239\u2013252. CRC Press (2015)"},{"issue":"2","key":"35_CR8","doi-asserted-by":"publisher","first-page":"150","DOI":"10.1109\/34.273735","volume":"16","author":"A Laurentini","year":"1994","unstructured":"Laurentini, A.: The visual hull concept for silhouette-based image understanding. IEEE Trans. Pattern Anal. Mach. Intell. 16(2), 150\u2013162 (1994)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"35_CR9","doi-asserted-by":"crossref","unstructured":"Franco, J., Boyer, E.: Exact polyhedral visual hulls. In: Proceedings of the British Machine Vision Conference (BMVC) (2003)","DOI":"10.5244\/C.17.32"},{"key":"35_CR10","doi-asserted-by":"crossref","unstructured":"Volino, M., Casas, D., Collomosse, J., Hilton, A.: Optimal representation of multiple view video. In: Proceedings of the British Machine Vision Conference. BMVA Press (2014)","DOI":"10.5244\/C.28.8"},{"issue":"1\u20133","key":"35_CR11","doi-asserted-by":"publisher","first-page":"256","DOI":"10.1007\/s11263-012-0553-4","volume":"102","author":"C Budd","year":"2013","unstructured":"Budd, C., Huang, P., Klaudinay, M., Hilton, A.: Global non-rigid alignment of surface sequences. Int. J. Comput. Vis. (IJCV) 102(1\u20133), 256\u2013270 (2013)","journal-title":"Int. J. Comput. Vis. (IJCV)"},{"key":"35_CR12","doi-asserted-by":"crossref","unstructured":"Han, X., Li, Z., Huang, H., Kalogerakis, E., Yu, Y.: High-resolution shape completion using deep neural networks for global structure and local geometry inference. In: Proceedings of the International Conference on Computer Vision (ICCV 2017) (2017)","DOI":"10.1109\/ICCV.2017.19"},{"key":"35_CR13","unstructured":"Wu, Z., et al.: 3D shapenets: a deep representation for volumetric shapes. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2015) (2015)"},{"key":"35_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"236","DOI":"10.1007\/978-3-319-49409-8_20","volume-title":"Computer Vision \u2013 ECCV 2016 Workshops","author":"A Sharma","year":"2016","unstructured":"Sharma, A., Grau, O., Fritz, M.: VConv-DAE: deep volumetric shape learning without object labels. In: Hua, G., J\u00e9gou, H. (eds.) ECCV 2016. LNCS, vol. 9915, pp. 236\u2013250. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-49409-8_20"},{"key":"35_CR15","doi-asserted-by":"crossref","unstructured":"Fattal, R.: Image upsampling via imposed edge statistics. In: Proceedings of the ACM SIGGRAPH (2007)","DOI":"10.1145\/1275808.1276496"},{"issue":"1\u20134","key":"35_CR16","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1016\/0167-2789(92)90242-F","volume":"60","author":"LI Rudin","year":"1992","unstructured":"Rudin, L.I., Osher, S., Fatemi, E.: Non-linear total variation based noise removal algorithms. Phys. D 60(1\u20134), 259\u2013268 (1992)","journal-title":"Phys. D"},{"issue":"9","key":"35_CR17","doi-asserted-by":"publisher","first-page":"4135","DOI":"10.1364\/BOE.8.004135","volume":"8","author":"S Abrahamsson","year":"2017","unstructured":"Abrahamsson, S., Blom, H., Jans, D.: Multifocus structured illumination microscopy for fast volumetric super-resolution imaging. Biomed. Opt. Express 8(9), 4135\u20134140 (2017)","journal-title":"Biomed. Opt. Express"},{"key":"35_CR18","unstructured":"Aydin, V., Foroosh, H.: Volumetric super-resolution of multispectral data. In: CORR arXiv:1705.05745v1 (2017)"},{"key":"35_CR19","unstructured":"Xie, J., Xu, L., Chen, E.: Image denoising and inpainting with deep neural networks. In: Proceedings of the Neural Information Processing Systems (NIPS), pp. 350\u2013358 (2012)"},{"key":"35_CR20","doi-asserted-by":"crossref","unstructured":"Wang, Z., Liu, D., Yang, J., Han, W., Huang, T.S.: Deep networks for image super-resolution with sparse prior. In: Proceedings of the International Conference on Computer Vision (ICCV), pp. 370\u2013378 (2015)","DOI":"10.1109\/ICCV.2015.50"},{"key":"35_CR21","doi-asserted-by":"crossref","unstructured":"Shi, W., et al.: Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network. In: Proceedings of the Computer Vision and Pattern Recognition (CVPR) (2016)","DOI":"10.1109\/CVPR.2016.207"},{"key":"35_CR22","unstructured":"Jain, V., Seung, H.: Natural image denoising with convolutional networks. In: Proceedings of the Neural Information Processing Systems (NIPS), pp. 769\u2013776 (2008)"},{"issue":"2","key":"35_CR23","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1109\/TPAMI.2015.2439281","volume":"38","author":"C Dong","year":"2016","unstructured":"Dong, C., Loy, C.C., He, K., Tang, X.: Image super-resolution using deep convolutional networks. IEEE Trans. Pattern Anal. Mach. Intell. 38(2), 295\u2013307 (2016)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"35_CR24","unstructured":"Zeiler, M.D.: Adadelta: an adaptive learning rate method. arXiv preprint arXiv:1212.5701 (2012)"},{"key":"35_CR25","unstructured":"Srivastava, R.K., Greff, K., Schmidhuber, J.: Training very deep networks. In: Advances in Neural Information Processing Systems, pp. 2377\u20132385 (2015)"},{"key":"35_CR26","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"issue":"4","key":"35_CR27","first-page":"163","volume":"21","author":"W Lorensen","year":"1987","unstructured":"Lorensen, W., Cline, H.: Marching cubes: a high resolution 3D surface construction algorithm. ACM Trans. Graph. (TOG) 21(4), 163\u2013169 (1987)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"35_CR28","doi-asserted-by":"crossref","unstructured":"Trumble, M., Gilbert, A., Malleson, C., Hilton, A., Collomosse, J.: Total capture: 3D human pose estimation fusing video and inertial sensors. In: Proceedings of 28th British Machine Vision Conference, pp. 1\u201313 (2017)","DOI":"10.5244\/C.31.14"},{"issue":"7","key":"35_CR29","doi-asserted-by":"publisher","first-page":"1325","DOI":"10.1109\/TPAMI.2013.248","volume":"36","author":"C Ionescu","year":"2014","unstructured":"Ionescu, C., Papava, D., Olaru, V., Sminchisescu, C.: Human3.6m: large scale datasets and predictive methods for 3D human sensing in natural environments. IEEE Trans. Pattern Anal. Mach. Intell. 36(7), 1325\u20131339 (2014)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"3","key":"35_CR30","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1109\/MCG.2007.68","volume":"27","author":"Jonathan Starck","year":"2007","unstructured":"Starck, J., Hilton, A.: Surface capture for performance-based animation. IEEE Comput. Graph. Appl. 27(3) (2007)","journal-title":"IEEE Computer Graphics and Applications"},{"key":"35_CR31","doi-asserted-by":"crossref","unstructured":"Mustafa, A., Volino, M., Guillemaut, J.Y., Hilton, A.: 4D temporally coherent light-field video. In: 3DV 2017 Proceedings (2017)","DOI":"10.1109\/3DV.2017.00014"},{"issue":"4","key":"35_CR32","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Tran. Image Process. (TIP) 13(4), 600\u2013612 (2004)","journal-title":"IEEE Tran. Image Process. (TIP)"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2018"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-01252-6_35","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,5]],"date-time":"2022-10-05T00:06:09Z","timestamp":1664928369000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-01252-6_35"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030012519","9783030012526"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-01252-6_35","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"6 October 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Munich","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2018.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}