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In this paper, we propose an accurate edge detector using richer convolutional features (RCF). Since objects in natural images possess various scales and aspect ratios, learning the rich hierarchical representations is very critical for edge detection. CNNs have been proved to be effective for this task. In addition, the convolutional features in CNNs gradually become coarser with the increase of...
In this paper, we propose a shape-guided segmentation algorithm for fine-grained visual classification(FGVC). First, edge information is extracted from the query image and compared with each sample of training set, which can help us retrieve a subset of candidate proposals. These proposals are used to learn prior shape knowledge by separately estimating the foreground probabilities of corresponding...
Text contained in images and video frames provide an important clue for content based images and video indexing. However, in natural scene, text elements are corrupted by many types of noise, such as streaks, highlights, or cracks. These effects make the clean and automatic segmentation very difficult and can reduce the accuracy of further analysis such as optical character recognition. This paper...
The text appears in the images is important for fully understanding the images. The number of digital images and digital videos has increased tremendously. Although there are many methods have been proposed over the past years for the text extraction from natural scene images, the text detection and extraction from born-digital images are still a challenge. In this paper, we describe existing methods...
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