Yang Fu
·
Sifei Liu
·
Amey Kulkarni
·
Jan Kautz
Alexei A. Efros
·
Xiaolong Wang
Paper | Video | Project Page
The codes have been tested on python 3.10, CUDA>=11.6. The simplest way to install all dependences is to use anaconda and pip in the following steps:
conda create -n cf3dgs python=3.10
conda activate cf3dgs
conda install conda-forge::cudatoolkit-dev=11.7.0
conda install pytorch==2.0.0 torchvision==0.15.0 pytorch-cuda=11.7 -c pytorch -c nvidia
pip install -r requirements.txtDATAROOT is ./data by default. Please first make data folder by mkdir data.
Download the data preprocessed by Nope-NeRF as below, and the data is saved into the ./data/Tanks folder.
wget https://www.robots.ox.ac.uk/~wenjing/Tanks.zipDownload our preprocessed data, and put it saved into the ./data/co3d folder.
python run_cf3dgs.py -s data/Tanks/Francis \ # change the scene path
--mode train \
--data_type tanks# pose estimation
python run_cf3dgs.py --source data/Tanks/Francis \
--mode eval_pose \
--data_type tanks \
--model_path ${CKPT_PATH}
# by default the checkpoint should be store in "./output/progressive/Tanks_Francis/chkpnt/ep00_init.pth"
# novel view synthesis
python run_cf3dgs.py --source data/Tanks/Francis \
--mode eval_nvs \
--data_type tanks \
--model_path ${CKPT_PATH} -
To run CF-3DGS on your own video, you need to first convert your video to frames and save them to
./data/$CUSTOM_DATA/images/ -
Camera intrincics can be obtained by running COLMAP (check details in
convert.py). Otherwise, we provide a heuristic camera setting which should work for most landscope videos. -
Run the following commands:
python run_cf3dgs.py -s ./data/$CUSTOM_DATA/ \ # change to your data path
--mode train \
--data_type customYou can change the depth estimator:
python run_cf3dgs.py -s ./data/$CUSTOM_DATA/
--mode train \
--data_type custom \
--depth_model_type depth_anything # can be one of [zoe, depth_anything, <anything>]. Anything but the first two will use MiDaS.
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