how to extract mesh of brandenburg_gate successfully?
- Dominant language
- Jupyter Notebook
- Stars
- 2.8k
- Forks
- 458
- PR merge metrics
- No merged PRs in 30d
Description
Hi~
Thanks for sharing this great code.
I have tried to adapt extract_mesh.ipynb to extract mesh from learned nerf-w model.
after seen the notes , I first get the bounds of point cloud from `dataset.xyz_world`:
```
x y z min:
[-1.58000625 -1.41236581 -0.89322236]
x y z max:
[ 3.32392681 2.49776899 10.96546297]
```
so I set bound params of this scene like:
```
xmin, xmax = -7, 16 # left/right range -1.2 1.2
ymin, ymax = -7, 16 # forward/backward range
zmin, zmax = -7, 16 # up/down range
```
however, the mesh is unreasonable:

have anyone made it ?
Contributor guide
No contributing guide indexed for this repository
Research direction
Start with extract_mesh.ipynb and inspect how bounds are derived from dataset.xyz_world and applied to the learned NeRF-W model. Reproduce the Brandenburg Gate extraction with the reported bounds, then compare the resulting mesh with the expected scene geometry to identify whether the bounds or extraction process is responsible.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, pytorch
- Domain
- computer-vision, machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100