Closed stalin18 closed 6 years ago
The stddev is about 255, so it's simply re-scaling the range to be approximately contained in [-1, 1]. I believe for the mean values, just using 255/2 should work equally well, but i only tried training with this normalization. I used the mean from the code at "http://scs.ryerson.ca/~jjyu/projects/unsupervised/optical/flow/machine/learning/2016/08/30/Unsup-flow.html" and i think it's the KITTI mean.
what about the mean of sintel and synthia. It looks you didn't use mean in synthia, but use the same mean in sintel with kitti.
The same mean is used everywhere.
Hi, I see that you perform mean normalization with:
mean = [104.920005, 110.1753, 114.785955] stddev = 1 / 0.0039216
Are these values from ImageNet dataset? I'm curious to know if performing normalization considerably affected (improved) your results? I believe none of the papers (your's included) explicitly mention about input image normalization for optical flow. Thanks!