unsupervised-depth-completion-visual-inertial-odometry

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Hi, how did you generate the predicted depth map of the kitti dataset as colored and back-projected to 3-D? I think the net_utils file seems to be doing this, but how is it called in kitti? Thank you very much for any reply.

You can follow the general instructions in this thread of our recent work KBNet: https://github.com/alexklwong/calibrated-backprojection-network/issues/17#issuecomment-1176431551

This repo is in Tensorflow so it is a bit harder to use for the general purpose of creating point clouds. A PyTorch version is coming soon.

In the meantime, here is the PyTorch version of the function: https://github.com/alexklwong/calibrated-backprojection-network/blob/master/src/net_utils.py#L1638-L1667