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In this paper, we introduce a novel approach to regulate receptive field in deep image parsing network automatically. Unlike previous works which have stressed much importance on obtaining better receptive fields using manually selected dilated convolutional kernels, our approach uses two affine transformation layers in the networks backbone and operates on feature maps. Feature maps will be inflated/shrinked...
Image tag refinement is the task of refining initial tags of an image such that the refined tags can better reflect the content of the image and, therefore, can help users better access that image. The quality of tag refinement depends on the quality of concept representations that build a mapping from concepts to visual images. While good progress was made in the past decade on tag refinement, the...
Millions of video surveillance cameras distribute around the world, and capture tremendous number of video data endlessly. Video browsing by frame is time consuming and inefficient, since needless information is abundant in the raw videos. Video synopsis is an effective way to solve this problem by producing a short video abstraction, while keeping the essential activities of the original video. However,...
In this paper, we propose a novel contextual descriptor which combines the contextual information and local appearance. Based on Gibbs distribution, a local descriptor is designed. By assembling the contextual information and local descriptors, a new partial contextual descriptor (PCD) is finally presented. Combining pyramid match kernel (PMK) and SVM, we test our new descriptor and obtain higher...
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