Comments (4)
I find the corresponding RGB images corresponding to your provide trajectory document, and find that they are continuous in a small room. But their index number on raw datasets are unordered. Did you sort them with your observation on the raw RGB images manually or is their any documents provided by raw datasets to show that?
from deepmapping.
Hi, thanks for your interest in our work. For the first question, our key idea behind DeepMapping is that we solve the registration/mapping problem as if we are "training" the DNN and thus we do not necessarily expect the trained DNN to generalize to other scenes. In another word, we train a unique DNN for each point cloud sequence.
For your second question, the AVD dataset provides code to allow you to virtually navigate the room (go from one location or another/rotate viewpoint). We use their code to sample the trajectories.
Let us know if you have other questions!
from deepmapping.
@Tina1994 It seems your questions are all answered above by Li, I'm closing this issue now. If you have other questions, feel free to follow up in this thread.
from deepmapping.
Thanks a lot
from deepmapping.
Related Issues (12)
- run_train_2D.sh error HOT 3
- Question about the warm start HOT 2
- who can tell me how to deal this problem? HOT 6
- run_train_2D.sh error HOT 3
- About used Active Vision Dataset (AVD) trajectory HOT 9
- Training for ordered / un-ordered data points HOT 2
- how to understand “we do not necessarily expect the trained DNNs to generalize to other scenes.” HOT 4
- About generating 3D ground truth for custom trajectory on the AVD dataset HOT 1
- why the output of M-Net is not using sigmoid? HOT 1
- How to generate Occupancy Map after registration HOT 2
- A Potential Bug in Sample Unoccupied Point HOT 3
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from deepmapping.