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A study of local smoothness-informed convolutional neural network models for image inpainting

 y    | 14 abr 2022

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Bertalmio M, Sapiro G, Caselles V, Ballester C. Image Inpainting, In: Proceedings of the 27th annual conference on Computer graphics and interactive techniques (SIGGRAPH’00), ACM Press, USA, 2000 pp. 417–424. https://doi.org/10.1145/344779.344972. Search in Google Scholar

Chan T F, Shen J. Mathematical Models for Local Nontexture Inpaintings, SIAM Journal on Applied Mathematics, 2002, 62(3), pp. 1019–1043. https://doi.org/10.2307/3061798. Search in Google Scholar

Chan T F, Shen J. Nontexture Inpainting by Curvature-Driven Diffusions. Journal of Visual Communication and Image Representation, 2001, 12, 436–449. https://doi.org/10.1006/jvci.2001.0487. Search in Google Scholar

Rudin L I, Osher S, Fatemi E. Nonlinear Total Variation Based Noise Removal Algorithms, Physica D: Nonlinear Phenomena, 1992, 60(1–4), pp. 259–268. Search in Google Scholar

Oliveira M M, Bowen B, Mckenna R, Chang Y S. Fast Digital Image Inpainting, Proceedings of the International Conference on Visualization, Imaging and Image Processing (VIIP 2001), Marbella, Spain, 2001. Search in Google Scholar

Efros A A, Leung T K. Texture Synthesis by Non-Parametric Sampling, Proceedings of the Seventh IEEE International Conference on Computer Vision 2, 1999, pp. 1033–1038. https://doi.org/10.1109/ICCV.1999.790383. Search in Google Scholar

Xu Z, Sun J. Image Inpainting by Patch Propagation Using Patch Sparsity, In: IEEE Trans Image Processing, 2010, 19(5), pp. 1153–1165. https://doi.org/10.1109/TIP.2010.2042098. Search in Google Scholar

Pathak D, Krähenbühl P, Donahue J, Darrell T, Efros A A. Context Encoders: Feature Learning by Inpainting, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA, 2016, pp. 2536–2544. https://doi.org/10.1109/CVPR.2016.278. Search in Google Scholar

Goodfellow I J, Pouget-Abadie J, Mirza M, Xu B, Warde-Farley D, Ozair S, Courville A, Bengio Y. Generative Adversarial Nets, In: Proceedings of the 27th International Conference on Neural Information Processing Systems (NIPS’14), MIT Press, Cambridge, MA, USA, 2014, 2, pp. 2672–2680. Search in Google Scholar

Yeh R A, Chen C, Lim T Y, Schwing A G, Hasegawa-Johnson M, Do, M N. Semantic Image Inpainting with Deep Generative Models, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, USA, 2017, pp. 6882–6890. https://doi.org/10.1109/CVPR.2017.728. Search in Google Scholar

Pérez P, Gangnet M, Blake A. Poisson Image Editing. In ACM SIGGRAPH 2003 Papers (SIGGRAPH’03), Association for Computing Machinery, New York, NY, USA, 2003, pp. 313–318. https://doi.org/10.1145/1201775.882269. Search in Google Scholar

Iizuka S, Simo-Serra E, Ishikawa H. Globally and Locally Consistent Image Completion, ACM Trans Graphics, 2017, 36(4), pp. 1–14. https://doi.org/10.1145/3072959.3073659. Search in Google Scholar

Fukushima K. Neocognitron: A Hierarchical Neural Network Capable of Visual Pattern Recognition, Neural Networks, 1988, 1, pp. 119–130. https://doi.org/10.1016/0893-6080(88)90014-7. Search in Google Scholar

Zhang W, Itoh K, Tanida J, Ichioka Y. Parallel Distributed Processing Model with Local Space-Invariant Interconnections and Its Optical Architecture, Applied Optics, 1990, 29(32), pp. 4790–4797. https://doi.org/:10.1364/AO.29.004790. Search in Google Scholar

Nair V, Hinton G E. Rectified Linear Units Improve Restricted Boltzmann Machines, In: Proceedings of the 27th International Conference on International Conference on Machine Learning (ICML’10). Omnipress, Madison, WI, USA, 2010, 807–814. Search in Google Scholar

Pascal G. Total Variation Inpainting Using Split Bregman, Image Processing On Line, 2012, 2, pp. 147–157. https://doi.org/10.5201/ipol.2012.g-tvi. Search in Google Scholar

Perona P, Malik J. Scale-Space and Edge Detection Using Anisotropic Diffusion, In: IEEE Trans Pattern Analy Machine Intell., 1990, 12(7), pp. 629–639. https://doi.org/10.1109/34.56205. Search in Google Scholar

Sobel I. An Isotropic 3x3 Image Gradient Operator, Presentation at Stanford A.I. Project 1968. Search in Google Scholar

Kingma D P, Ba J. Adam: A Method for Stochastic Optimization, CoRR, 2015, abs/1412.6980. Search in Google Scholar

Abadi M, Barham, P, Chen J M, et al., TensorFlow: A System for Large-Scale Machine Learning, In: Proceedings of the 12th USENIX conference on Operating Systems Design and Implementation (OSDI’16). USENIX Association, USA, 2016, pp. 265–283. Search in Google Scholar

VQEG, Final Report from the Video Quality Experts Group on the Validation of Objective Models of Video Quality Assessment, Mar., 2000, http://www.vqeg.org/. Search in Google Scholar

Wang Z, Bovik A C, Sheikh H R, Simoncelli E P. Image Quality Assessment: From Error Visibility to Structural Similarity, 2004, IEEE TIP. Search in Google Scholar

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