A research team, led by computer scientists from the University of Bern-Switzerland and University of Maryland-College Park, have devised a sketch-based editing framework that enables a user to edit their photos by “sketching” a few strokes on top of them. Their system, called FaceShop, also offers a copy-paste function, which allows users to edit any part of a photo by copying-and-pasting the portion to be edited from another (better) photo, eliminating the need to hand-draw or sketch anything at all.
The team’s approach is built on machine-learning techniques, which, in the end, give users more control over their desired edits in real-time and produce more realistic results. Most other approaches rely on more traditional, handcrafted techniques, which impose some limitations.
For instance, these systems are either [by design] restricted to limited sets of predefined editing operations, or they are very flexible but hard to use and require experienced users to spend a considerable amount of time to perform rather basic edits.
The team’s method is based on generative adversarial neural networks (GANs), a form of artificial intelligence (AI) that, in recent years, has attracted a lot of research interest for its ability to generate realistic looking images. These GANs consist of two AIs that fight against each other.
The first component tries to distinguish the generated images from genuine images, whereas the second component tries to produce images that fool the other AI. During training, the two components learn from each other, eventually resulting in a system that autonomously learned to produce realistic looking images, without any human judgement in the loop.
In future work, the researchers intend to explore additional user interaction tools to add to their framework, and consider how to leverage AI for sketch-based editing of videos.
News Source : https://www.eurekalert.org/pub_releases/2018-07/afcm-cgr070218.php
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