Comments (4)
I already finished the codes but won't have much time to do testing before mid-March. Hopefully this can be released by end of March.
from sparse-to-dense.pytorch.
Any possibility to help with testing? Can't wait to see the pytorch implementation! :-)
from sparse-to-dense.pytorch.
Any possibility to help with testing? Can't wait to see the pytorch implementation! :-)
Thanks for offering to help. I'll do my best to release it asap. :P
from sparse-to-dense.pytorch.
Just uploaded the codes.
from sparse-to-dense.pytorch.
Related Issues (20)
- An issue with "resume" mode HOT 2
- [NYU] Different Scaling in Training and Validation HOT 4
- Implementing SLAM
- How is the loss calculated for KITTI dataset ?
- Is there an easy way to run inference on a different dataset HOT 2
- Apply the pretrained model to other datasets HOT 2
- No rgb image normalization during pre-process HOT 1
- Different sparse input when each sample input is loaded HOT 3
- The low download speed in NYU and KITTI
- License for repo
- pose information for processed data
- Benchmark on KITTI vs NYU Depth v2
- Request for pretrained model with depth-only modality
- Failed to reproduce the RGB based problem, whereas the RGBd problem works fine for me.
- How can I use this Git from Windows OS HOT 1
- Using another model
- Scaling factor cancels out for depth values
- The principle of implementing a simple Visual Odometry (VO) algorithm
- Output for custom image
- replace the method of "misc.imresize(img, self.size, self.interpolation, 'F')" HOT 2
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from sparse-to-dense.pytorch.