A team of computer scientists at UC Riverside has developed a new method to detect manipulated facial expressions in deep fake videos. The method could detect these expressions with up to 99% accuracy, making it more accurate than the current state-of-the-art methods.
The new research paper titled “Detection and Localization of Facial Expression Manipulations” was presented at the 2022 Winter Conference on Applications of Computer Vision.
The method also proved as accurate as current methods in cases where the facial identity had been swapped rather than the expressions. This means the new approach can be used to detect any type of facial manipulation, and it is a major step towards the development of automated tools for detecting manipulated videos.
It has never been easier to swap the face of one individual for another or alter original expressions due to recent advancements in video editing software. The detection of such methods is highly important as they are increasingly being deployed in various domestic and international conflicts throughout the globe. With that said, identifying faces with only swapped expressions has been extremely challenging.
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