Comments (2)
Could you plz answer my question...?
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Yes, it is correct, but it doesn't matter. You will find that the geometry consistency loss is small from the beginning or quickly drops to a small value so that the weight for most regions is always high. After several epochs, the system can learn correct consistency, so that the training will not be degraded.
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Related Issues (20)
- 0.01 in pose decoder HOT 1
- General question (loss to constant 0) HOT 1
- How to use this on a Windows Machine? HOT 3
- Custom Dataset
- NYU V2 HOT 1
- Stereo datasets needed for training? HOT 1
- pebble missing as a dependency
- unexpected loss curves on my own driving datasets
- About posenet HOT 1
- train only posenet HOT 2
- How to train monodepth2 with the rectified_nyu dataset? HOT 4
- Customized data sets HOT 1
- Pseudo-RGBD SLAM
- monodepth2 added ARN HOT 2
- Mask Visualization HOT 4
- How to Apply the Code to EUROC Dataset?
- About smoothing
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