image manipulation thesis

COMMENTS

1. Manipulating natural images by learning relationships between

   In this thesis, we investigate whether flexible attribute manipulation models can be trained without massive labeled datasets of real images by transferring knowledge about the desired manipulation across different image datasets (domains) that share the underlying structure.

2. Making image generation and manipulation simple and effective

   In this thesis, we explore techniques that allow casual users to perform complex semantic image manipulation with ease in an intuitive way. Enabling such interactions requires a deep knowledge of images and their underlying structures.

3. Framing digital image credibility: image manipulation

   I describe the various types of image manipulation, giving examples, and then canvas the literature to describe the landscape of image manipulation problems and extant solutions, namely: the nature of image manipulation, investigations of human perceptions of image manipulation, eye gaze tracking and manipulated images,