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Fine-grained visual recognition aims to capture discriminative characteristics amongst visually similar categories. The state-of-the-art research work has significantly improved the fine-grained recognition performance by deep metric learning using triplet network. However, the impact of intra-category variance on the performance of recognition and robust feature representation has not been well studied...
We focus on painting retrieval problem, and our motivation is to find out similar paintings and assist painting plagiarism identification. Similar painting retrieval is much more challenging than natural image retrieval, since different paintings have different styles and the similarity of paintings is difficult to measure. In this paper, we define the similarity of paintings from the perspectives...
User-given tags associated with social images from photo-sharing websites (e.g., Flickr) are valuable auxiliary resources for the image tagging task. However, social images often suffer from noisy and incomplete tags, heavily degrading the effectiveness of previous image tagging approaches. To alleviate the problem, we introduce a Sparse Tag Patterns (STP) model to discover noiseless and complementary...
This paper studies the problem of retrieving images by color, texture and shape in the context of visual assisted product recommendation in E-commerce sites. Different from general CBIR applications, commerce image retrieval puts more emphasis on outlier-free ranking (top N) to gain perfect user experience. We suggest to extend the bag-of-words (BoW) model to global feature characterization rather...
With the proliferation of online media services, video ads are pervasive across various platforms involving Internet services and interactive TV services. Existing research efforts such as Google AdSense and MSRA videosense/imagesense have been devoted to the less intrusive insertion of relevant textual or video ads in streams or Web pages through text/image/video content analysis whereas the inherent...
A commercial system that performs syntactic and semantic analysis during a TV advertising break could facilitate innovative new applications, such as an intelligent set-top box that enhances the ability of viewers to monitor and manage commercials from TV streams.
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