You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hi, thank you for this brilliant work.
I am currently trying to use your method for point cloud registration, similar to the way mentioned in your work (adapted to networks like RPMNet). However there is one thing that confuses me a little bit, that is:
In point cloud registration, the source and target point cloud contains sometimes points that are not able to be matched, which in the case of RPMNet are taken care of by adding a dummy column and a dummy row. And the Sinkhorn normalization skips the dummy column and row, so that potentially multiple unmatched points can map themself to the dummy space. (If I understand it correctly) https://github.com/yewzijian/RPMNet/blob/b1c9ee0290a4f1f6515b22d496f8e1768c661c91/src/models/rpmnet.py#L63-L91
I am wondering how should I modify your implicit-sinkhorn to adapt to dummy padding, especially for the gradient computation in the "backward" function.
The text was updated successfully, but these errors were encountered:
Hi, thank you for this brilliant work.
I am currently trying to use your method for point cloud registration, similar to the way mentioned in your work (adapted to networks like RPMNet). However there is one thing that confuses me a little bit, that is:
In point cloud registration, the source and target point cloud contains sometimes points that are not able to be matched, which in the case of RPMNet are taken care of by adding a dummy column and a dummy row. And the Sinkhorn normalization skips the dummy column and row, so that potentially multiple unmatched points can map themself to the dummy space. (If I understand it correctly)
https://github.com/yewzijian/RPMNet/blob/b1c9ee0290a4f1f6515b22d496f8e1768c661c91/src/models/rpmnet.py#L63-L91
I am wondering how should I modify your implicit-sinkhorn to adapt to dummy padding, especially for the gradient computation in the "backward" function.
The text was updated successfully, but these errors were encountered: