Image resizing by reconstruction from deep features

Image Reconstruction from Incomplete Data

Image Reconstruction from Incomplete Data

Face Image Reconstruction from Deep Templates

State-of-the-art face recognition systems are based on deep (convolutional) neural networks. Therefore, it is imperative to determine to what extent face templates derived from deep networks can be inverted to obtain the original face image. In this paper, we discuss the vulnerabilities of a face recognition system based on deep templates, extracted by deep networks under image reconstruction a...

High quality image resizing

An increasing amount of display devices with fixed sizes call for an adaptive strategy for optimal display. For this purpose, content aware image resizing techniques are developed. Previous works mainly lay their attention on the shrinkage operation of the examined image. Less efforts are paid on the expansion manipulation. Though some literatures claim an extension of their shrinkage operation...

Automatic Image Resizing

Today’s digital content is displayed on a diverse set of devices, ranging from large monitors of various aspect ratios, to small screens of cell phones or handheld devices. Existing display standards, such as HTML, support the ability to dynamically resize the composition of the page to enable viewing on different display sizes. During this resizing process, images always remain fixed in size. ...