Comments (2)
In our original work,featurenet was trained separately. But we found it can also be trained jointly with depthnet and posenet, and got close performance with the one trained separately. We provide a config file for joint training, it will consume much more GPU memory.
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Thanks for your reply. :-)
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Related Issues (20)
- running infer_singleimage.py in win10 ModuleNotFoundError: No module named 'resource' HOT 1
- it seems that the decoder of the auto-encoder network is not trained in the code HOT 1
- About the training and testing setting. HOT 4
- Is there a way to visually check the output of the FeatureNet HOT 1
- Question about MS evaluation HOT 5
- dataset.flag HOT 1
- An error occurred while training my own dataset HOT 2
- How to start non-distributed training HOT 2
- Why use DistOptimizerHook? HOT 1
- Problems using DDP HOT 2
- Train only Image Reconstruction Model HOT 2
- cfg_kitti_fm.py stops while training, expected 4 input channels, but got 3 channels instead
- train on own dataset with fm_joint.cfg HOT 1
- pose question HOT 1
- pose question HOT 2
- feature-metric loss only use the first output of the Autoencoder HOT 2
- Evaluation Issue HOT 1
- how to use multi-gpus training?
- Weights for Monocular-only training
- 关于online refinement的疑问
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