fast-d3dgs branch still treats the scene as static

[lemonci]

The scene.init checks for data format markers in order:

1. sparse/ → COLMAP (static)
2. transforms_train.json → Blender
3. poses_bounds.npy → plenopticVideo (dynamic)
4. ...etc.

Since the neur3d zip contains sparse/0/ (COLMAP reconstruction), and the COLMAP check comes first, the fast-d3dgs branch loads neur3d as static COLMAP data.

The train.sh confirms this — the training command is just:
python train.py -s ./data/neur3d/cook_spinach -m output/cook_spinach --eval --iterations 30000

No --is_blender, no --is_6dof, no temporal flags. Same format as regular FastGS static training.

So the fast-d3dgs branch treats neur3d scenes as static multi-view scenes (via COLMAP loader), even though the training pipeline still includes a deformation network. The deformation model is present but learns minimal/zero deformations since the data has no temporal axis.

[Shiwei-Ren]

Hello! Thank you for the suggestion. I will check the code and upload an updated version soon.