Image steganography is the technique of hiding secret information within images. It is an important research direction in the security field. Benefitting from the rapid development of deep neural networks, many steganographic ...

Image composition extracts the content of interest (COI) from a source image and blends it into a target image to generate a new image. In the majority of existing works, the COI is manually extracted and then overlaid on ...

Palette-based image decomposition has attracted increasing attention in recent years. A specific class of approaches have been proposed basing on the RGB-space geometry, which manage to construct convex hulls whose vertices ...

We present a novel interactive learning-based method for curating datasets using user-defined criteria for training and refining Generative Adversarial Networks. We employ a novel batch-mode active learning strategy to ...

Smoothing noises while preserving strong edges in images is an important problem in image processing. Image smoothing filters can be either explicit (based on local weighted average) or implicit (based on global optimization). ...

Image metrics predict the perceived per-pixel difference between a reference image and its degraded (e. g., re-rendered) version. In several important applications, the reference image is not available and image metrics ...

Light field imaging is rapidly becoming an established method for generating flexible image based description of scene appearances. Compared to classical 2D imaging techniques, the angular information included in light ...

Mathematical models of ordinary differential equations are used to describe and understand biological phenomena. These models are dynamical systems that often describe the time evolution of more than three variables, i.e., ...

This paper proposes a deep learning-based image tone enhancement approach that can maximally enhance the tone of an image while preserving the naturalness. Our approach does not require carefully generated ground-truth ...