Seeing was believing until technology reared its mighty head and gave us powerful and inexpensive photo-editing tools.
Seeing was believing until technology reared its mighty head and gave us powerful and inexpensive photo-editing tools. Now, realistic videos that map the facial expressions of one person onto those of another, known as deepfakes, present a formidable political weapon.
But whether it’s the benign smoothing of a wrinkle in a portrait, or a video manipulated to make it look like a politician saying something offensive, all photo editing leaves traces for the right tools to discover.
Research led by Amit Roy-Chowdhury’s Video Computing Group at the University of California, Riverside has developed a deep neural network architecture that can identify manipulated images at the pixel level with high precision. Roy-Chowdhury is a professor of electrical and computer engineering and the Bourns Family Faculty Fellow in the Marlan and Rosemary Bourns College of Engineering.
A deep neural network is what artificial intelligence researchers call computer systems that have been trained to do specific tasks, in this case, recognize altered images. These networks are organized in connected layers; “architecture” refers to the number of layers and structure of the connections between them.
Read more at University of California - Riverside
