Deep models have achieved impressive performance for face hallucination tasks. However, we observe that directly feeding the hallucinated facial images into recognition models can even degrade the recognition performance despite the much better visualization quality. In this paper, we address this problem by jointly learning a deep model for two tasks, i.e. face hallucination and recognition. I...

Owing to the success of deep learning techniques for tasks such as Q/A and text-based dialog, there is an increasing demand for AI agents in several domains such as retail, travel, entertainment, etc. that can carry on multimodal conversations with humans employing both text and images within a dialog seamlessly. However, deep learning research is this area has been limited primarily due to the...

It is generally known that active pixel sensors (APS) have a number of advantages over CCD detectors if it comes to cost for mass production, power consumption and ease of integration. Nevertheless, most space applications still use CCD detectors because they tend to give better performance and have a successful heritage. To this respect a change may be at hand with the advent of deep sub-micro...

Scale-space representation has been popular in computer vision community due to its theoretical foundation. The motivation for generating a scale-space representation of a given data set originates from the basic observation that real-world objects are composed of different structures at different scales. Hence, it’s reasonable to consider learning features with image pyramids generated by smoo...