How to visualize dense correspondence?

[unlabeledData]

This is a great job. Could you give more details about the visualization of dense correspondence?

[WXinlong]

For two feature points at two views, if they are the most similar one to each other and the similarity is greater than a threshold, e.g., 0.9, this match is kept and visualized.

[CoinCheung]

@WXinlong Hi, I am also not clear with this part of paper. Would you please tell me some details:

1. How to obtain feature points? Which feature is used to for matching, the feature directly from backbone(resnet output) or from the dense-head(used to compute loss)?
2. Since the both the backbone and the dense-head have downsample rate of 32, how could we obtain exact position of points on the original image from the feature point?