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Inferring user search goals for a query can be very useful in improving search engine relevance and user experience. Although the research on analyzing user goals or intents for text search has received much attention, little has been proposed for image search. In this paper, we propose a novel approach to infer user search goals in image search by mining search engine query logs with semi-supervised...
Aliasing is a common artifact in low-resolution (LR) images generated by a downsampling process. Recovering the original high-resolution image from its LR counterpart while at the same time removing the aliasing artifacts is a challenging image interpolation problem. Since a natural image normally contains redundant similar patches, the values of missing pixels can be available at texture-relevant...
Traditional image interpolation methods assume that the local spatial structure of the low-resolution (LR) and high-resolution (HR) images are approximately the same, and use edge information of the LR image to estimate the missing pixels. This assumption, however, no longer holds for natural images with fine and dense textures. Consequently, those methods cannot restore dense textures well and tend...
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