Comments (2)
Here is a model trained on Matterport3D.
validation houses: yqstnuAEVhm
, Z6MFQCViBuw
, ZMojNkEp431
, zsNo4HB9uLZ
, XcA2TqTSSAj
test houses: VzqfbhrpDEA
, Vvot9Ly1tCj
, YFuZgdQ5vWj
, YVUC4YcDtcY
, YmJkqBEsHnH
training houses: all remaining houses
The network input, RGB and sparse depth, are normalized in the same way as for ScanNet:
https://github.com/barbararoessle/dense_depth_priors_nerf/blob/master/run_nerf.py#L683
https://github.com/barbararoessle/dense_depth_priors_nerf/blob/master/run_nerf.py#L670
And the network output, depth and uncertainty, is converted back to meters like:
https://github.com/barbararoessle/dense_depth_priors_nerf/blob/master/run_nerf.py#L686
For best performance, the depth prior training should consider the scenario that you plan to use the depth priors in (e.g. sparse depth density and accuracy). Details can be found here
from dense_depth_priors_nerf.
@barbararoessle You should provide pretrain models and the train / test split on matterport3d for future works to compare.
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Related Issues (20)
- How to compute stantard deviation? HOT 1
- On the standard deviation of depth map HOT 1
- Confused about the coordinate system and COLMAP sparse reconstruction
- What scenes are used for the training of pre-trained depth_prior_network HOT 1
- Models to reproduce the results on ScanNet and Matterport3D HOT 5
- can't run extract_scannet_scene
- Could you provide more complete preprocessing scripts?
- Depth loss is negative HOT 1
- About the depth-guided ray sampling HOT 2
- Error in compute_depth_loss
- Video generation with less than 3 images
- The torch version of the completion depth network HOT 1
- Can I obtain dense depth maps corresponding to each rgb images through your depth completion work๏ผ
- Error while making the preprocessing/build . HOT 1
- How do I run this project on my own dataset? HOT 1
- UnpicklingError: A load persistent id instruction was encountered HOT 2
- Question for the resolution of the imags
- Question with regards to the target depth map
- Question about depth_prior_network_path and db_path HOT 1
- Dataset preprocessing
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