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Our paper is motivated from the advancement in deep learning algorithms for various computer vision problems. We are proposing a novel end-to-end deep learning based framework for image super-resolution. This framework simultaneously calculates the convolutional features of low-resolution (LR) and high-resolution (HR) image patches and learns the non-linear function that maps these convolutional features...
Multi-view stereo, novel view synthesis and high dynamic range (HDR) imaging are three pertinent areas of concern for high quality 3D view generation. This paper presents a novel parameterized variety based model that integrates these different domains into one common framework with an envisioned goal, to accommodate multi-view stereo for multiple exposure input views and to render photo-realistic...
We present a video coding technique based on texture synthesis via stitching small patches of previous images as done in texture transfer. Each macroblock is identified as a texture or non texture block by means of an edge based criterion. The texture blocks are reconstructed using the luminance values as the control block information to guide the texture transfer algorithm. By modifying the texture...
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