{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T19:28:51Z","timestamp":1672601331886},"reference-count":55,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2021,10,25]],"date-time":"2021-10-25T00:00:00Z","timestamp":1635120000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2021,10,25]],"date-time":"2021-10-25T00:00:00Z","timestamp":1635120000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci. China Inf. Sci."],"published-print":{"date-parts":[[2021,11]]},"DOI":"10.1007\/s11432-020-3236-2","type":"journal-article","created":{"date-parts":[[2021,10,27]],"date-time":"2021-10-27T11:02:28Z","timestamp":1635332548000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Single-view facial reflectance inference with a differentiable renderer"],"prefix":"10.1007","volume":"64","author":[{"given":"Jiahao","family":"Geng","sequence":"first","affiliation":[]},{"given":"Yanlin","family":"Weng","sequence":"additional","affiliation":[]},{"given":"Lvdi","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Kun","family":"Zhou","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,10,25]]},"reference":[{"key":"3236_CR1","doi-asserted-by":"crossref","unstructured":"Debevec P, Hawkins T, Tchou C, et al. Acquiring the reflectance field of a human face. In: Proceedings of the 27th Annual Conference on Computer Graphics and Interactive Techniques, 2000. 145\u2013156","DOI":"10.1145\/344779.344855"},{"key":"3236_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2070781.2024163","volume":"30","author":"A Ghosh","year":"2011","unstructured":"Ghosh A, Fyffe G, Tunwattanapong B, et al. Multiview face capture using polarized spherical gradient illumination. ACM Trans Graph, 2011, 30: 1\u201310","journal-title":"ACM Trans Graph"},{"key":"3236_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2766974","volume":"34","author":"A E Ichim","year":"2015","unstructured":"Ichim A E, Bouaziz S, Pauly M. Dynamic 3D avatar creation from hand-held video input. ACM Trans Graph, 2015, 34: 1\u201314","journal-title":"ACM Trans Graph"},{"key":"3236_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3092817","volume":"36","author":"L Hu","year":"2017","unstructured":"Hu L, Saito S, Wei L, et al. Avatar digitization from a single image for real-time rendering. ACM Trans Graph, 2017, 36: 1\u201314","journal-title":"ACM Trans Graph"},{"key":"3236_CR5","doi-asserted-by":"crossref","unstructured":"Sengupta S, Kanazawa A, Castillo C D, et al. SfSNet: learning shape, reflectance and illuminance of faces in the wild. 2018. arXiv:1712.01261","DOI":"10.1109\/CVPR.2018.00659"},{"key":"3236_CR6","doi-asserted-by":"crossref","unstructured":"Tewari A, Zollhfer M, Kim H, et al. MoFA: model-based deep convolutional face autoencoder for unsupervised monocular reconstruction. 2017. ArXiv:1703.10580","DOI":"10.1109\/ICCV.2017.401"},{"key":"3236_CR7","doi-asserted-by":"crossref","unstructured":"Genova K, Cole F, Maschinot A, et al. Unsupervised training for 3D morphable model regression. 2018. ArXiv:1806.06098","DOI":"10.1109\/CVPR.2018.00874"},{"key":"3236_CR8","doi-asserted-by":"crossref","unstructured":"Deng Y, Yang J, Xu S, et al. Accurate 3D face reconstruction with weakly-supervised learning: from single image to image set. 2019. ArXiv:1903.08527","DOI":"10.1109\/CVPRW.2019.00038"},{"key":"3236_CR9","doi-asserted-by":"crossref","unstructured":"Tran L, Liu X. Nonlinear 3D face morphable model. In: Proceedings of IEEE Computer Vision and Pattern Recognition, Salt Lake City, 2018","DOI":"10.1109\/CVPR.2018.00767"},{"key":"3236_CR10","doi-asserted-by":"crossref","unstructured":"Tran L, Liu F, Liu X. Towards high-fidelity nonlinear 3D face morphable model. In: Proceedings of IEEE Computer Vision and Pattern Recognition, Long Beach, 2019","DOI":"10.1109\/CVPR.2019.00122"},{"key":"3236_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3197517.3201364","volume":"37","author":"S Yamaguchi","year":"2018","unstructured":"Yamaguchi S, Saito S, Nagano K, et al. High-fidelity facial reflectance and geometry inference from an unconstrained image. ACM Trans Graph, 2018, 37: 1\u201314","journal-title":"ACM Trans Graph"},{"key":"3236_CR12","unstructured":"Ma W C, Hawkins T, Peers P, et al. Rapid acquisition of specular and diffuse normal maps from polarized spherical gradient illumination. In: Proceedings of the Eurographics Symposium on Rendering Techniques, Grenoble, 2007"},{"key":"3236_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3272127.3275073","volume":"37","author":"P Gotardo","year":"2019","unstructured":"Gotardo P, Riviere J, Bradley D, et al. Practical dynamic facial appearance modeling and acquisition. ACM Trans Graph, 2019, 37: 1\u201313","journal-title":"ACM Trans Graph"},{"key":"3236_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1778765.1778777","volume":"29","author":"T Beeler","year":"2010","unstructured":"Beeler T, Bickel B, Beardsley P, et al. High-quality single-shot capture of facial geometry. ACM Trans Graph, 2010, 29: 1\u20139","journal-title":"ACM Trans Graph"},{"key":"3236_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2010324.1964970","volume":"30","author":"T Beeler","year":"2011","unstructured":"Beeler T, Hahn F, Bradley D, et al. High-quality passive facial performance capture using anchor frames. ACM Trans Graph, 2011, 30: 1\u201310","journal-title":"ACM Trans Graph"},{"key":"3236_CR16","doi-asserted-by":"crossref","unstructured":"Graham P, Tunwattanapong B, Busch J, et al. Measurement-based synthesis of facial microgeometry. In: Proceedings of ACM SIGGRAPH, 2013","DOI":"10.1145\/2343045.2343057"},{"key":"3236_CR17","doi-asserted-by":"crossref","unstructured":"von der Pahlen J, Jimenez J, Danvoye E, et al. Digital Ira and Beyond: Creating a Real-Time Photoreal Digital Actor. Technical Report, 2014","DOI":"10.1145\/2614028.2615407"},{"key":"3236_CR18","doi-asserted-by":"crossref","unstructured":"Blanz V, Vetter T. A morphable model for the synthesis of 3D faces. In: Proceedings of ACM SIGGRAPH, 1999","DOI":"10.1145\/311535.311556"},{"key":"3236_CR19","doi-asserted-by":"crossref","unstructured":"Kemelmacher-Shlizerman I. Internet based morphable model. In: Proceedings of IEEE International Conference on Computer Vision, 2013. 3256\u20133263","DOI":"10.1109\/ICCV.2013.404"},{"key":"3236_CR20","doi-asserted-by":"crossref","unstructured":"Booth J, Roussos A, Zafeiriou S, et al. A 3D morphable model learnt from 10000 faces. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. 5543\u20135552","DOI":"10.1109\/CVPR.2016.598"},{"key":"3236_CR21","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3395208","volume":"39","author":"B Egger","year":"2020","unstructured":"Egger B, Smith W A P, Tewari A, et al. 3D morphable face models-past, present, and future. ACM Trans Graph, 2020, 39: 1\u201338","journal-title":"ACM Trans Graph"},{"key":"3236_CR22","doi-asserted-by":"crossref","unstructured":"Thies J, Zollhofer M, Stamminger M, et al. Face2face: real-time face capture and reenactment of RGB videos. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016. 2387\u20132395","DOI":"10.1109\/CVPR.2016.262"},{"key":"3236_CR23","first-page":"1","volume":"35","author":"P Garrido","year":"2016","unstructured":"Garrido P, Zollhofer M, Casas D, et al. Reconstruction of personalized 3D face rigs from monocular video. ACM Trans Graph, 2016, 35: 1\u201315","journal-title":"ACM Trans Graph"},{"key":"3236_CR24","first-page":"1","volume":"33","author":"C Cao","year":"2014","unstructured":"Cao C, Hou Q, Zhou K. Displaced dynamic expression regression for real-time facial tracking and animation. ACM Trans Graph, 2014, 33: 1\u201310","journal-title":"ACM Trans Graph"},{"key":"3236_CR25","doi-asserted-by":"crossref","unstructured":"Tewari A, Zollh\u00f6fer M, Garrido P, et al. Self-supervised multi-level face model learning for monocular reconstruction at over 250 Hz. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018. 2549\u20132559","DOI":"10.1109\/CVPR.2018.00270"},{"key":"3236_CR26","doi-asserted-by":"crossref","unstructured":"Saito S, Wei L, Hu L, et al. Photorealistic facial texture inference using deep neural networks. 2017. arXiv:1612.00523","DOI":"10.1109\/CVPR.2017.250"},{"key":"3236_CR27","doi-asserted-by":"crossref","unstructured":"Gecer B, Ploumpis S, Kotsia I, et al. GANFIT: generative adversarial network fitting for high fidelity 3D face reconstruction. 2019. ArXiv:1902.05978","DOI":"10.1109\/CVPR.2019.00125"},{"key":"3236_CR28","doi-asserted-by":"crossref","unstructured":"Huynh L, Chen W, Saito S, et al. Mesoscopic facial geometry inference using deep neural networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018. 8407\u20138416","DOI":"10.1109\/CVPR.2018.00877"},{"key":"3236_CR29","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3355089.3356529","volume":"38","author":"T Sun","year":"2019","unstructured":"Sun T, Barron J T, Tsai Y T, et al. Single image portrait relighting. ACM Trans Graph, 2019, 38: 1\u201312","journal-title":"ACM Trans Graph"},{"key":"3236_CR30","doi-asserted-by":"crossref","unstructured":"Zhou H, Hadap S, Sunkavalli K, et al. Deep single-image portrait relighting. In: Proceedings of the IEEE International Conference on Computer Vision, 2019. 7194\u20137202","DOI":"10.1109\/ICCV.2019.00729"},{"key":"3236_CR31","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3306346.3323027","volume":"38","author":"A Meka","year":"2019","unstructured":"Meka A, H\u00e4ne C, Pandey R, et al. Deep reflectance fields. ACM Trans Graph, 2019, 38: 1\u201312","journal-title":"ACM Trans Graph"},{"key":"3236_CR32","doi-asserted-by":"crossref","unstructured":"Liu S, Li T, Chen W, et al. Soft rasterizer: a differentiable renderer for image-based 3D reasoning. 2019. ArXiv:1904.01786","DOI":"10.1109\/ICCV.2019.00780"},{"key":"3236_CR33","unstructured":"Chen W, Ling H, Gao J, et al. Learning to predict 3D objects with an interpolation-based differentiable renderer. In: Proceedings of Advances in Neural Information Processing Systems, 2019. 9605\u20139616"},{"key":"3236_CR34","doi-asserted-by":"crossref","unstructured":"Shu Z, Yumer E, Hadap S, et al. Neural face editing with intrinsic image disentangling. 2017. ArXiv:1704.04131","DOI":"10.1109\/CVPR.2017.578"},{"key":"3236_CR35","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2897824.2925917","volume":"35","author":"M Aittala","year":"2016","unstructured":"Aittala M, Aila T, Lehtinen J. Reflectance modeling by neural texture synthesis. ACM Trans Graph, 2016, 35: 1\u201313","journal-title":"ACM Trans Graph"},{"key":"3236_CR36","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3355089.3356488","volume":"38","author":"D Gao","year":"2019","unstructured":"Gao D, Li X, Dong Y, et al. Deep inverse rendering for high-resolution SVBRDF estimation from an arbitrary number of images. ACM Trans Graph, 2019, 38: 1\u201315","journal-title":"ACM Trans Graph"},{"key":"3236_CR37","doi-asserted-by":"publisher","first-page":"767","DOI":"10.1364\/AO.4.000767","volume":"4","author":"F E Nicodemus","year":"1965","unstructured":"Nicodemus F E. Directional reflectance and emissivity of an opaque surface. Appl Opt, 1965, 4: 767\u2013775","journal-title":"Appl Opt"},{"key":"3236_CR38","doi-asserted-by":"crossref","unstructured":"Calian D A, Lalonde J F, Gotardo P, et al. From faces to outdoor light probes. In: Proceedings of Computer Graphics Forum, 2018. 51\u201361","DOI":"10.1111\/cgf.13341"},{"key":"3236_CR39","unstructured":"Dib A, Bharaj G, Ahn J, et al. Face reflectance and geometry modeling via differentiable ray tracing. 2019. ArXiv:1910.05200"},{"key":"3236_CR40","first-page":"1","volume":"37","author":"T M Li","year":"2019","unstructured":"Li T M, Aittala M, Durand F, et al. Differentiable Monte Carlo ray tracing through edge sampling. ACM Trans Graph, 2019, 37: 1\u201311","journal-title":"ACM Trans Graph"},{"key":"3236_CR41","doi-asserted-by":"crossref","unstructured":"Isola P, Zhu J Y, Zhou T, et al. Image-to-image translation with conditional adversarial networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017. 1125\u20131134","DOI":"10.1109\/CVPR.2017.632"},{"key":"3236_CR42","doi-asserted-by":"publisher","first-page":"527","DOI":"10.1145\/566654.566612","volume":"21","author":"P P Sloan","year":"2002","unstructured":"Sloan P P, Kautz J, Snyder J. Precomputed radiance transfer for real-time rendering in dynamic, low-frequency lighting environments. ACM Trans Graph, 2002, 21: 527\u2013536","journal-title":"ACM Trans Graph"},{"key":"3236_CR43","doi-asserted-by":"crossref","unstructured":"Ronneberger O, Fischer P, Brox T. U-Net: convolutional networks for biomedical image segmentation. 2015. ArXiv: 1505.04597","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"3236_CR44","doi-asserted-by":"crossref","unstructured":"Ledig C, Theis L, Husz\u00e1r F, et al. Photo-realistic single image super-resolution using a generative adversarial network. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017. 4681\u20134690","DOI":"10.1109\/CVPR.2017.19"},{"key":"3236_CR45","unstructured":"Simonyan K, Zisserman A. Very deep convolutional networks for large-scale image recognition. 2014. ArXiv:1409.1556"},{"key":"3236_CR46","unstructured":"Sloan P P. Stupid spherical harmonics (SH) tricks. In: Proceedings of Game Developers Conference, 2008. 42"},{"key":"3236_CR47","unstructured":"Snyder J. Code Generation and Factoring for Fast Evaluation of Low-order Spherical Harmonic Products and Squares. Microsoft TechReport MSR-TR-2006-53, 2006"},{"key":"3236_CR48","unstructured":"Walter B, Marschner S R, Li H, et al. Microfacet models for refraction through rough surfaces. In: Proceedings of the Eurographics Symposium on Rendering Techniques, Grenoble, 2007"},{"key":"3236_CR49","unstructured":"Lagarde S, de Rousiers C. Moving frostbite to physically based rendering. In: Proceedings of SIGGRAPH 2014 Conference, Vancouver, 2014"},{"key":"3236_CR50","unstructured":"Gardner M A, Sunkavalli K, Yumer E, et al. Learning to predict indoor illumination from a single image. 2017. ArXiv:1704.00090"},{"key":"3236_CR51","doi-asserted-by":"publisher","first-page":"399","DOI":"10.1145\/1015706.1015736","volume":"23","author":"R W Sumner","year":"2004","unstructured":"Sumner R W, Popovic J. Deformation transfer for triangle meshes. ACM Trans Graph, 2004, 23: 399\u2013405","journal-title":"ACM Trans Graph"},{"key":"3236_CR52","doi-asserted-by":"publisher","first-page":"1122","DOI":"10.3758\/s13428-014-0532-5","volume":"47","author":"D S Ma","year":"2015","unstructured":"Ma D S, Correll J, Wittenbrink B. The Chicago face database: a free stimulus set of faces and norming data. Behav Res, 2015, 47: 1122\u20131135","journal-title":"Behav Res"},{"key":"3236_CR53","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1145\/882262.882269","volume":"22","author":"P P\u00e9rez","year":"2003","unstructured":"P\u00e9rez P, Gangnet M, Blake A. Poisson image editing. ACM Trans Graph, 2003, 22: 313\u2013318","journal-title":"ACM Trans Graph"},{"key":"3236_CR54","unstructured":"Abadi M, Barham P, Chen J, et al. Tensorflow: a system for large-scale machine learning. In: Proceedings of the 12th USENIX Symposium on Operating Systems Design and Implementation, 2016. 265\u2013283"},{"key":"3236_CR55","unstructured":"Kingma D P, Ba J. Adam: a method for stochastic optimization. 2014. ArXiv:1412.6980"}],"container-title":["Science China Information Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11432-020-3236-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11432-020-3236-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11432-020-3236-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,20]],"date-time":"2022-12-20T21:05:11Z","timestamp":1671570311000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11432-020-3236-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,25]]},"references-count":55,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2021,11]]}},"alternative-id":["3236"],"URL":"https:\/\/doi.org\/10.1007\/s11432-020-3236-2","relation":{},"ISSN":["1674-733X","1869-1919"],"issn-type":[{"value":"1674-733X","type":"print"},{"value":"1869-1919","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,10,25]]},"assertion":[{"value":"28 May 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 December 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 March 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 October 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"210101"}}