You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
hi~ I'm digging in your work for weeks and it's really awesome! Now I wanna ask if I set the conv size as the input size, does it mean that the convCRF is equivalent to FullyCRF in this case?
The text was updated successfully, but these errors were encountered:
My understanding is you need to change the kernel size in the message passing function. Change it from 7 (the value used in the current code) to your input size.
Yes, if you use a large filter size you will get a model very similar to FullCRF. Note that there are some subtle differences. FullCRF uses the Permutohedral Lattice approximation, while a ConvCRF with large filter size is exact.
I have visualized the differences by plotting the impulse response for the filters on a simple 10x10 pixel image, where the center pixels are white with a black frame. The 10x10 filter has the same response as a simple (inefficient) exact filter I have implemented in numpy. The lattice filter however loses some detail. Below the results.
hi~ I'm digging in your work for weeks and it's really awesome! Now I wanna ask if I set the conv size as the input size, does it mean that the convCRF is equivalent to FullyCRF in this case?
The text was updated successfully, but these errors were encountered: