Titlebook: Computer Vision –ACCV 2016; 13th Asian Conferenc Shang-Hong Lai,Vincent Lepetit,Yoichi Sato Conference proceedings 2017 Springer Internatio

LANCE

Ingrid Matthäus-Maier,J. D. Pischke planar regions and perform the reconstruction of each layer by using an explicit form of the plenoptic camera point spread function. The proposed framework also recovers the sharp scene texture with different motion blurs applied to each layer. We demonstrate our method on challenging real and synthetic images.

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foodstuff

https://doi.org/10.1007/978-981-19-3355-4eved by reducing small . values to zero in an iterative manner. Since features have larger . magnitudes than speckle noise, the proposed . minimization is capable of effectively suppressing the speckle noise. Meanwhile, the rest of . values corresponding to prominent features are kept unchanged, lea

考古学

Defraud

https://doi.org/10.1007/978-3-540-24820-0a unified network and be optimized jointly. Extensive experiments are conducted to investigate the relation between restoration performance and different network architectures. Compared with other current image SR approaches, our proposed method achieves state-of-the-arts restoration results on a wi

largesse

Development of the Idea of Detenteobtained where the self-occlusion part keeps the illumination conditions of the query face. Large scale face recognition experiments on LFW and MultiPIE achieve comparative results with state-of-the-art methods, verifying effectiveness of proposed method, with advantage of being database-independent

笨拙的你

Acetabulum

Dense Depth-Map Estimation and Geometry Inference from Light Fields via Global Optimizationals are elaborately constructed to satisfy sub-modular condition with 2nd order smoothness regularizer, so that the minimization can be efficiently solved by graph cuts (GC). Our method is evaluated on public light field datasets and achieves the state-of-the-art accuracy.