ARFlow
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lliuz
The official PyTorch implementation of the paper "Learning by Analogy: Reliable Supervision from Transformations for Unsupervised Optical Flow Estimation".
If i have my own unlabeled dataset (no ground truth) on which i want to train the ARFlow network. How can i do it? Is there a rule of thumb...
during training, Occu_mask whether there is gradient return? when occu_mask is zeros, the loss is small; if need occu_mask -> occu_mask.detach() ?
I have installed the repo using the Dockerfile you have upload. Although i have some problems with the first hands-on experience of the repo. 1. Inference: i run both commands...
Hi, I would like to provide an acceleration strategy that can address the problem of slow optical flow estimation speed in >pytorch1.1 version. Since we want to predict the dense...
Thanks for your wonderful code! I wonder the epe on trainval of sintel-clean/final for the model of sintel_ft.json without AR. Could u also provide the sintel_ft.tar model? By the way,...
Dear @lliuz, thanks for your great work. I am testing your networks on Sintel clean. - for the checkpoint Sintel/pwclite_raw.tar I get a mean epe of 8.5 px, is it...
I'm trying to apply ARFlow on Sintel database, which has images of shape (436, 1024). What is the recommended test shape value? For the example given, images are of shape...
I'm having issues using the correlation package. So, I was thinking of the native implementation you've provided. I would like to understand the differences between them. 1. Is the difference...
Could you please share the method how to train the multi-view model ? It seems that there is no trainer for multi-view version.
