Codes for CVPR 2024 paper "SpikeNeRF: Learning Neural Radiance Fields from Continuous Spike Stream"
Demo.mp4
YouTube demo video link.
The code is based on nerf-pytorch.
git clone https://github.com/BIT-Vision/SpikeNeRF.git
cd SpikeNeRF
pip install -r requirements.txt
You can download the training data we processed from Google Drive. Place the downloaded dataset according to the following directory structure:
├── configs
│ ├── ...
│
├── data
│ ├── nerf_llff_data
│ │ └── toys # downloaded llff dataset
| | └── ...
| ├── nerf_synthetic
| | └── lego
| | └── chair # downloaded synthetic dataset
| | └── ...
To train SpikeNeRF on different datasets:
python run_spikenerf.py --config configs/{DataType}/{DataSet}.txt
replace {DataType} with nerf_synthetic or nerf_llff_data , and replace {DataSet} with toys | dolls | lego | chair | etc.
To test SpikeNeRF trained on different datasets: render the test data：
python run_spikenerf.py --config configs/{DataType}/{DataSet}.txt --render_only --render_test
render the novel view:
python run_spikenerf.py --config configs/{DataType}/{DataSet}.txt --render_only
replace {DataType} with nerf_synthetic or nerf_llff_data , and replace {DataSet} with toys | dolls | lego | chair | etc.
This codebase is built upon nerf-pytorch, and thanks to the above open source projects for their help and inspiration.