We present an integrated approach for creating and assigning color palettes to different visualizations such as multi-class scatterplots, line, bar charts. While other methods separate the creation of colors from their assignment, our takes data characteristics into account produce palettes, which are then assigned in a way that fosters better visual discrimination classes. To do so, we use cus...

Colorization, the process of adding color to monochrome images, is a tedious and difficult task and often requires intensive manual effort by color experts. To alleviate this problem, a number of computational studies have been proposed in the literature which aim to perform this task in a relatively easy way, either by employing minimal user input in terms of color scribbles or using a colored...

In this study a new artificial neural network based approach to automatic or semi-automatic colorization of black and white film footages is introduced. Different features of black and white images are tried as the input of a MLP neural network which has been trained to colorize the movie using its first frame as the ground truth. Amongst the features tried, e.g. position, relaxed position, lum...

Colorization of grayscale images is a hot topic in computer vision. Previous research mainly focuses on producing a color image to recover the original one in a supervised learning fashion. However, since many colors share the same gray value, an input grayscale image could be diversely colorized while maintaining its reality. In this paper, we design a novel solution for unsupervised diverse c...

Levin et al.’s Colorization method [1] requires neither precise image segmentation, nor accurate region tracking, which is in fact based on a simple premise: neighboring pixels in space-time that have similar intensities should have similar colors. The authors accomplish this by formalizing this idea using a quadratic cost function, which leads to an optimization problem that can be solved effi...

We develop a probabilistic technique for colorizing grayscale natural images. In light of the intrinsic uncertainty of this task, the proposed probabilistic framework has numerous desirable properties. In particular, our model is able to produce multiple plausible and vivid colorizations for a given grayscale image and is one of the first colorization models to provide a proper stochastic sampl...