The companys latest work, showcased this month at the CVPR computer vision conference, demonstrates how digital forensics done by humans can be automated by machines in much less time. The research paper does not represent a breakthrough in the field, and its not yet available as a commercial product, but its interesting to see Adobe a name synonymous with image editing take an interest in this line of work.
But, the company points to its work with law enforcement as evidence of its responsible attitude toward its technology.
The new research paper shows how machine learning can be used to identify three common types of image manipulation: splicing, where two parts of different images are combined; cloning, where objects within an image are copy and pasted; and removal, when an object is edited out altogether.
When these sorts of edits are made, they leave behind digital artifacts, like inconsistencies in the random variations in color and brightness created by image sensors . When you splice together two different images, for example, or copy and paste an object from one part of an image to another, this background noise doesnt match, like a stain on a wall covered with a slightly different paint color.
However, the research has no direct application in spotting deepfakes, a new breed of edited videos created using artificial intelligence.
Original article