xiaohangzhan / conditional-motion-propagation Goto Github PK
View Code? Open in Web Editor NEWCode for our CVPR 2019 work.
License: MIT License
Code for our CVPR 2019 work.
License: MIT License
Thanks for your interesting work.
I have a small question. The paper title implies your method is self-supervised, but I notice your network is supervised by ground truth which is generated by another optical flow network.
So is it proper to be called as a self-supervised method?
Can you please release the tutorial of eval?
including the data structure.
it will help a lot !
The article says that the guidance is sampled from the target flow, but what is the basis of the "sparse motion+mask" we input at the beginning? At this time, the static image does not have a corresponding optical flow diagram.
Thanks for the great contribution. I was wondering if you are able to provide the demo code for the video generation as it was shown in the youtube video. Preferably, the code generates a .gif output, given the arrows/anchors.
Thanks,
I want to train on my video dataset
I do not have any questions, just want to say this work is aaaaaaaawesome.
It deserves more attention from the self-supervised learning community.
I believe the conditional motion propagation pretext task will play an important role in the future, serving as one crucial component of a multi-task self-supervised learning framework.
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