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View Code? Open in Web Editor NEWPWC Net Tensorflow: Tensorflow implementation of Pyramid, Warping and Cost Volume Networks based on CVRP 2018 paper
PWC Net Tensorflow: Tensorflow implementation of Pyramid, Warping and Cost Volume Networks based on CVRP 2018 paper
Hi @djl11,
Thanks for sharing your code.
The optical flow estimator network is a feed-forward network formed by stacking layers one over the other:
In the flow_estimator_forward_pass
function, where the estimator network is defined, it says:
conv4 = tf.layers.conv2d(conv3,64,[3,3],(1,1),'same','channels_first',(1,1),tf.nn.leaky_relu)
ft = tf.layers.conv2d(conv4,32,[3,3],(1,1),'same','channels_first',(1,1),tf.nn.leaky_relu)
wt = tf.layers.conv2d(conv4,2,[3,3],(1,1),'same','channels_first',(1,1),tf.nn.leaky_relu)
That is, both ft and wt are stacked over conv4
, instead of being stacked one over the other as in the figure from the paper. Was this intentional, or a bug?
hi @djl11
Thanks for your work. I want to know if I want to fine-tune on the Kitti Dataset, the ground truth flow are sparse. so how can I change the Loss Function.
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