Fighting fake videos with improved computer vision
Contributing to a project that aims to detect “deepfake” videos, U-M engineers developed software that improves a computer’s ability to track an object through a video clip by 11% on average. The software, called BubbleNets, chooses the best frame for a human to annotate. In addition to helping train algorithms for spotting doctored clips, it could improve computer… Read More »