  Current image transformation and recoloring algorithms try to introduce
artistic effects in the photographed images, based on user input of target
image(s) or selection of pre-designed filters. These manipulations, although
intended to enhance the impact of an image on the viewer, do not include the
option of image transformation by specifying the affect information. In this
paper we present an automatic image-transformation method that transforms the
source image such that it can induce an emotional affect on the viewer, as
desired by the user. Our proposed novel image emotion transfer algorithm does
not require a user-specified target image. The proposed algorithm uses features
extracted from top layers of deep convolutional neural network and the
user-specified emotion distribution to select multiple target images from an
image database for color transformation, such that the resultant image has
desired emotional impact. Our method can handle more diverse set of photographs
than the previous methods. We conducted a detailed user study showing the
effectiveness of our proposed method. A discussion and reasoning of failure
cases has also been provided, indicating inherent limitation of color-transfer
based methods in the use of emotion assignment.
  Project Page: http://im.itu.edu.pk/affective-image-transfer/
