News for hackers. Stuff that matters.
Re:ImageNet-trained CNNs are biased towards texture (2019) by kzrdude on Monday April 20, 2020 @03:43AM (#22921950)
Texture is area-filling, while silhouette is "just a line", so it sounds natural that texture areas would weigh more in an image? If there is both texture and contour "signal" in the labeled inputs, how to pick what get's weighted more? This is supposed to be learned by training.
Re:ImageNet-trained CNNs are biased towards texture (2019) by mbeex on Monday April 20, 2020 @04:16AM (#22922111)
I think, this is one of the reasons to use much more video-based training sets and these in time-correct frame order. A moving boundary is something quite significant, but these should possibly not exclusively inspected through a hole ('convolutinal')
Re:ImageNet-trained CNNs are biased towards texture (2019) by rayuela on Monday April 20, 2020 @10:58AM (#22924363)
Oh wow you're absolutely right. This is actually a really clever solution to the problem presented in this paper.
Re:ImageNet-trained CNNs are biased towards texture (2019) by mbeex on Monday April 20, 2020 @04:21AM (#22922118)
Oh, forgot an 'o'.
Re:ImageNet-trained CNNs are biased towards texture (2019) by mkl on Monday April 20, 2020 @05:48AM (#22922477)
Did you know you can edit your comments for two hours? Click "edit" above the comment.

https://github.com/minimaxir/hacker-news-undocumented

Re:ImageNet-trained CNNs are biased towards texture (2019) by mbeex on Monday April 20, 2020 @11:30AM (#22924741)
This is actually new to me. Thank you!