The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Convolutional Neural Network (CNN) based image representations have achieved high performance in image retrieval tasks. However, traditional CNN based global representations either provide high-dimensional features, which incurs large memory consumption and computing cost, or inadequately capture discriminative information in images, which degenerates the functionality of CNN features. To address...
Mobile visual search has undergone a wide development and gained much progress in recent years thanks to the ever-growing computational power of mobile devices. Most visual search methods take a single image as query and generate an image-level representation to implement image retrieval. To form a compact and discriminative representation for the query image, Fisher vectors (FV) have shown great...
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...
Constructing discriminative feature descriptors is crucial towards effective image retrieval. The state-of-the-art powerful global descriptor for this purpose is Vector of Locally Aggregated Descriptors (VLAD). Given a set of local features (say, SIFT) extracted from an image, the VLAD is generated by quantizing local features with a small visual vocabulary (64 to 512 centroids), aggregating the residual...
Smart phones is bringing about emerging potentials in mobile visual search. Extensive research efforts have been made in compact visual descriptors. However, directly extracting visual descriptors on a mobile device is computationally intensive and time consuming. Towards low bit rate visual search, we propose to deeply compress query images by learning a customized JPEG quantization table in the...
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...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.