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This paper presents a Semantic Attribute assisted video SUMmarization framework (SASUM). Compared with traditional methods, SASUM has several innovative features. Firstly, we use a natural language processing tool to discover a set of keywords from an image and text corpora to form the semantic attributes of visual contents. Secondly, we train a deep convolution neural network to extract visual features...
We present a novel method for constructing Variational Autoencoder (VAE). Instead of using pixel-by-pixel loss, we enforce deep feature consistency between the input and the output of a VAE, which ensures the VAE's output to preserve the spatial correlation characteristics of the input, thus leading the output to have a more natural visual appearance and better perceptual quality. Based on recent...
Road is the skeleton of the city, which is usually elongated. Extracting road information is of great significance in urban planning. Tensor voting can detect the geometric characteristics of the typical objects in the image. In this paper in order to improve the accuracy of road extraction in high-resolution remote sensing image, road is extracted preliminary using morphological edge segmentation...
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