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Soccer video semantic analysis has attracted a lot of researchers in the last few years. Many methods of machine learning have been applied to this task and have achieved some positive results, but the neural network method has not yet been used to this task from now. Taking into account the advantages of Convolution Neural Network(CNN) in fully exploiting features and the ability of Recurrent Neural...
Deep learning methods have been successfully used in many areas of computer vision, including super resolution. However, all of the previous deep learning methods have been proposed for generic image super resolution. In this paper, we proposed to use convolutional neural network for face hallucination (FH) by combining the domain specific prior knowledge of face images and properties of deep learning...
Foreground detection plays a fundamental role in video analysis. Frames with only background information are usually beneficial for many foreground detection algorithms, especially for regression-based methods where the background is recovered from a background basis matrix. However, many regression-based methods ignore the basis selection process or select bases by simple sampling, which may limit...
We present a computational model for image super-resolution. Apart from using deep Convolutional Neural Network to map between the low-resolution images and high-resolution images, we adopt stepwise refinement method to improve the reconstruction results and introduce the back projection algorithm to avoid diffusion of error pixels.
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