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lmb-freiburg / flownet2

FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks

Home Page:https://lmb.informatik.uni-freiburg.de/Publications/2017/IMKDB17/

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DispNetCorr1D always gives negative values

adhara123007 opened this issue · comments

commented

Hi,

This is regarding the DispNet network. I am using the DispNetCorr1D network to register images. I understand the network is only trained to register Right image to the left image. Thus the DispNetCorr1D always gives negative values. In my case, I want to get both positive and negative values of shift. How can I use the weights of the current network to register both Left to Right images and Right to Left images?
For example if I just do
Left to Right registration
python run-flownet-dispnet.py ../models/DispNetCorr1D/model/DispNetCorr1D_CVPR2016.caffemodel ../models/DispNetCorr1D/model/deploy.prototxt ../data/dispnet/imgL.png ../data/dispnet/imgR.png ../data/dispnet/floLR.flo
image

If I do Right to Left registration

python run-flownet-dispnet.py ../models/DispNetCorr1D/model/DispNetCorr1D_CVPR2016.caffemodel ../models/DispNetCorr1D/model/deploy.prototxt ../data/dispnet/imgR.png ../data/dispnet/imgL.png ../data/dispnet/floRL.flo

image

In the second case, the disparity map should have been positive.