![]() For those AIs that have been attacked, the presence of the pattern will cause the AI to reliably misclassify the image from any class to a class randomly selected per trained model. Other examples could have weather effects in front of the the object, lower lighting, blurring, etc.Īll Trojan attacks consist of pasting an unknown pixel pattern (between 2% and 25% of the foreground object area) onto the surface of the foreground object in the image. Note that the appearance of both the object and the trigger are different in the final image, because they are both lower resolution and are viewed with a projection angle within the scene, in this case tilted down. ![]() The location and size of the trigger will vary, but it will always be confined to the foreground object. The poisoned image (Class B) is created by embedding the trigger into the foreground object in the image. ![]() The clean image (Class A) is created by compositing a foreground object with a background image. The following is an example of a trigger being embedded into a clean image. See for how to load and inference an example image. For example, an RGB image of size 224 x 224 x 3 on disk needs to be read, transposed into 1 x 3 x 224 x 224, and normalized (via min-max normalization) into the range inclusive. For the image-based tasks, the trained AI models expect NCHW dimension min-max normalized color image input data.
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