PS-FCN: A Flexible Learning Framework for Photometric Stereo
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[1] Takahiro Okabe,et al. From Intensity Profile to Surface Normal: Photometric Stereo for Unknown Light Sources and Isotropic Reflectances , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[2] Yoichi Sato,et al. SymPS: BRDF Symmetry Guided Photometric Stereo for Shape and Light Source Estimation , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[3] Takeshi Shakunaga,et al. Analysis of photometric factors based on photometric linearization. , 2007, Journal of the Optical Society of America. A, Optics, image science, and vision.
[4] Athinodoros S. Georghiades,et al. Incorporating the Torrance and Sparrow model of reflectance in uncalibrated photometric stereo , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[5] Tai-Pang Wu,et al. Photometric Stereo via Expectation Maximization , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[6] Andrew Zisserman,et al. SilNet : Single- and Multi-View Reconstruction by Learning from Silhouettes , 2017, BMVC.
[7] Zhe Wu,et al. Calibrating Photometric Stereo by Holistic Reflectance Symmetry Analysis , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[8] Jiaya Jia,et al. Efficient photometric stereo on glossy surfaces with wide specular lobes , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[9] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[10] Trevor Darrell,et al. Fully Convolutional Networks for Semantic Segmentation , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[11] Luc Van Gool,et al. Learned Multi-patch Similarity , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[12] Zhe Wu,et al. A Benchmark Dataset and Evaluation for Non-Lambertian and Uncalibrated Photometric Stereo , 2019, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[13] Yasuyuki Matsushita,et al. Deep Photometric Stereo Network , 2017, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW).
[14] Kiyoharu Aizawa,et al. Photometric Stereo Using Constrained Bivariate Regression for General Isotropic Surfaces , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[15] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[16] Robert J. Woodham,et al. Photometric method for determining surface orientation from multiple images , 1980 .
[17] Abhinav Gupta,et al. Designing deep networks for surface normal estimation , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[18] Andrew Jones,et al. Relighting human locomotion with flowed reflectance fields , 2006, EGSR '06.
[19] David J. Kriegman,et al. Resolving the Generalized Bas-Relief Ambiguity by Entropy Minimization , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[20] Kiyoharu Aizawa,et al. Robust photometric stereo using sparse regression , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[21] Yasuyuki Matsushita,et al. Self-calibrating photometric stereo , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[22] Katsushi Ikeuchi,et al. Ieee Transactions on Pattern Analysis and Machine Intelligence Bi-polynomial Modeling of Low-frequency Reflectances , 2022 .
[23] Paolo Favaro,et al. A Closed-Form, Consistent and Robust Solution to Uncalibrated Photometric Stereo Via Local Diffuse Reflectance Maxima , 2013, International Journal of Computer Vision.
[24] Steven M. Seitz,et al. Example-based photometric stereo: shape reconstruction with general, varying BRDFs , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[25] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[26] David J. Kriegman,et al. Photometric stereo with non-parametric and spatially-varying reflectance , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[27] Christian Wöhler,et al. An introduction to image-based 3D surface reconstruction and a survey of photometric stereo methods , 2011 .
[28] Rama Chellappa,et al. A Method for Enforcing Integrability in Shape from Shading Algorithms , 1988, IEEE Trans. Pattern Anal. Mach. Intell..
[29] Edward H. Adelson,et al. Shape estimation in natural illumination , 2011, CVPR 2011.
[30] Andrew Jones,et al. Relighting human locomotion with flowed reflectance fields , 2006, EGSR '06.
[31] Wojciech Matusik,et al. A data-driven reflectance model , 2003, ACM Trans. Graph..
[32] Yann LeCun,et al. Signature Verification Using A "Siamese" Time Delay Neural Network , 1993, Int. J. Pattern Recognit. Artif. Intell..
[33] Katsushi Ikeuchi,et al. Median Photometric Stereo as Applied to the Segonko Tumulus and Museum Objects , 2009, International Journal of Computer Vision.
[34] Aswin C. Sankaranarayanan,et al. A Dictionary-Based Approach for Estimating Shape and Spatially-Varying Reflectance , 2015, 2015 IEEE International Conference on Computational Photography (ICCP).
[35] Jason Lawrence,et al. A photometric approach for estimating normals and tangents , 2008, ACM Trans. Graph..
[36] Yongtian Wang,et al. Robust Photometric Stereo via Low-Rank Matrix Completion and Recovery , 2010, ACCV.
[37] Silvio Savarese,et al. 3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction , 2016, ECCV.
[38] Reinhard Klein,et al. Heightfield and spatially varying BRDF Reconstruction for Materials with Interreflections , 2009, Comput. Graph. Forum.
[39] Berthold K. P. Horn,et al. Determining Shape and Reflectance Using Multiple Images , 1978 .
[40] Rob Fergus,et al. Depth Map Prediction from a Single Image using a Multi-Scale Deep Network , 2014, NIPS.