3 ms·

>I don't see how this follows. What we're not focused on is blurred, yes, but what we're focused on is at least partially related to our ability to recognize pa

>I don't see how this follows. What we're not focused on is blurred, yes, but what we're focused on is at least partially related to our ability to recognize patterns (e.g. reading from peripheral vision is very difficult). Object detection from peripheral vision is not difficult though. I think you're overestimating how much of our vision is actually clear. >The fact that CNNs are tricked by imperceptible perturbations while the semantic content is held constant is highly informative information, don't reject it for superficial reasons. Yes, but that is not this paper. These perturbations are not imperceptible, and unlike other adversarial examples the model adapted well when allowed to train on them. Also, it looks like the model did reasonable well on the random filtered versions, only failing on the blurred versions. The random filtered images looked much more corrupted to me than the blurred ones, which is consistent with blurred images being part of the training for the human visual system, but not randomly filtered ones.

yorwba 9y ago
The radial masking in the Fourier domain is pretty much imperceptible for me, but it seems to cause the most problems for the CNNs.
- moultano 9y ago
  I'm pretty sure that's because you are constantly trained on that type of image in your day to day life. "Radial masking in the Fourier domain" is pretty much identical to an image that it is out of focus or seen with a low resolution part of your eye. (Most of your vision.)
hackinthebochs 9y ago
>Object detection from peripheral vision is not difficult though. Because we understand high level semantic information, which is largely robust against blurring. >The random filtered images looked much more corrupted to me than the blurred ones, which is consistent with blurred images being part of the training for the human visual system, It's also consistent with the neural network training on surface level regularities, which a random filter would corrupt at a much lower rate than a blur filter would.

yorwba 9y ago

The radial masking in the Fourier domain is pretty much imperceptible for me, but it seems to cause the most problems for the CNNs.

moultano 9y ago
I'm pretty sure that's because you are constantly trained on that type of image in your day to day life. "Radial masking in the Fourier domain" is pretty much identical to an image that it is out of focus or seen with a low resolution part of your eye. (Most of your vision.)

hackinthebochs 9y ago

>Object detection from peripheral vision is not difficult though. Because we understand high level semantic information, which is largely robust against blurring. >The random filtered images looked much more corrupted to me than the blurred ones, which is consistent with blurred images being part of the training for the human visual system, It's also consistent with the neural network training on surface level regularities, which a random filter would corrupt at a much lower rate than a blur filter would.