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It's the subtlety, because vision algorithms don't necessarily look at the world like we do. Here, some folks perturbed an image of a cat to scan as guacamole,
by lsb 7y ago
It's the subtlety, because vision algorithms don't necessarily look at the world like we do.
Here, some folks perturbed an image of a cat to scan as guacamole, and have 3d printed a model of a turtle that scans as a rifle: https://www.labsix.org/physical-objects-that-fool-neural-nets/ https://www.labsix.org/physical-objects-that-fool-neural-net...
- yarg 7y agoMore on this point: computer vision tasks are (currently) far more reliant on the presence of a number of identifying features in the high frequency details of images. The are looking for a significant subset of some identifying group of highly localised features: think a large number of small things, rather than a small number of large things; think colour gradients rather than colours. These sorts of high frequency pieces of information can be placed into images in a way that is imperceivable to humans, but screams at computer vision neural networks. A sign could say no right turn to people and no left turn to machines.