• Deforming Radiance Fields with Cages (ECCV 2022)
• • Setup
  • Data preparation
  • • Datasets
    • Checkpoints
  • Rendering
  • Custom datasets and cages
  • Citation

Update:

• 11/10/2022 We added a manual for training, mesh/cage generation and deformation, etc.

Deforming Radiance Fields with Cages (ECCV 2022)

Project page | Paper | Video

Setup

Create a conda environment:

conda env create -f environment.yml
conda activate deforming-nerf

Then install all dependencies (this may take a long time):

pip install .

Note that our code implementation is based on Plenoxels, if you have any installation problems, we recommend referring to their original repo.

Data preparation

Datasets

Download the dataset from the following links and put them under ./data/ directory:

NeRF-synthetic dataset: https://drive.google.com/drive/folders/128yBriW1IG_3NJ5Rp7APSTZsJqdJdfc1 (nerf_synthetic.zip)

Synthetic-NSVF dataset: https://github.com/facebookresearch/NSVF#dataset (Synthetic_NSVF.zip)

DTU dataset (IDR preprocessed): https://github.com/lioryariv/idr (DTU.zip)

Checkpoints

Download optimized Plenoxels models and preprocessed cages from Google Drive and put them under .opt/ckpt/ directory.

Rendering

Take Lego in NeRF-synthetic dataset as an example.

Inside opt/, run the following command.

Render a static deformed scene with moving camera:

python render_imgs_deform.py ckpt/nerf_lego/ckpt.npz ../data/nerf_synthetic/lego/ -c configs/syn.json

Render an animation based on the cage interpolation:

python render_imgs_deform.py ckpt/nerf_lego/ckpt.npz ../data/nerf_synthetic/lego/ -c configs/syn.json --interpolate --cam_id 64

Render the original scene for comparison:

python render_imgs_deform.py ckpt/nerf_lego/ckpt.npz ../data/nerf_synthetic/lego/ -c configs/syn.json --render_orig

Note that you need to specify the config file according to the data format (i.e., syn.json, syn_nsvf.json or dtu.json)

Custom datasets and cages

Please see MANUAL.md for some tips about:

• Optimizing Plenoxel model from scratch
• Extracting mesh from optimized Plenoxel model
• Generating cage from mesh
• Cage deformation

Citation

If you find our work useful in your research, please consider citing:

@inproceedings{xu2022deforming,
      title={Deforming Radiance Fields with Cages}, 
      author={Tianhan Xu and Tatsuya Harada},
      year={2022},
      booktitle={ECCV},
}