Stereo Radiance Fields
Julian Chibane, Aayush Bansal, Verica Lazova, Gerard Pons-Moll
Stereo Radiance Fields (SRF): Learning View Synthesis for Sparse Views of Novel Scenes
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021
Paper - Supplementaty - Video - Project Website - Arxiv - If you find our project useful, please cite us. Citation (Bibtex)
Install
A linux system with python environment manager conda and a full and system wide installation of the CUDA Toolkit 10.1 is required for the project (the latter only for compilation of the torchsearchsorted library).
The following commands clone the repo on your machine and install an environment, "srf", containing all dependencies.
git clone ADD LINK
cd SRF_git
conda env create -f srf_env.yml
Please close the terminal session at this point, and reopen it at the same location. This is done to ensure conda correctly loads all packages.
conda activate srf
pip install torchsearchsorted/
Data Setup
With the next commands the DTU MVS dataset is downloaded and put in place.
wget http://roboimagedata2.compute.dtu.dk/data/MVS/Rectified.zip -P data/
unzip data/Rectified.zip -d data/
mv data/Rectified/* data/DTU_MVS
rmdir data/Rectified
Quick Start with Pretrained Model
To synthesise novel views use the following command
python generator.py --config configs/finetune_scan23.txt --video --render_factor 8 --generate_specific_samples scan23 --fixed_batch 1 --ft_path checkpoint.tar --gen_pose 0
where --config specifies the path to the experiment configuration and --gen_pose is the frame number from 0-55 (including both).
Training
Coming soon.
Contact
For questions and comments please contact Julian Chibane via mail.
License
Copyright (c) 2021 Julian Chibane, Max-Planck-Gesellschaft
By downloading and using this code you agree to the terms in the LICENSE.
You agree to cite the Stereo Radiance Fields (SRF): Learning View Synthesis for Sparse Views of Novel Scenes paper in documents and papers that report on research using this software or the manuscript.
Show LICENSE (click to expand)
Please read carefully the following terms and conditions and any accompanying documentation before you download and/or use this software and associated documentation files (the "Software").The authors hereby grant you a non-exclusive, non-transferable, free of charge right to copy, modify, merge, publish, distribute, and sublicense the Software for the sole purpose of performing non-commercial scientific research, non-commercial education, or non-commercial artistic projects.
Any other use, in particular any use for commercial purposes, is prohibited. This includes, without limitation, incorporation in a commercial product, use in a commercial service, or production of other artefacts for commercial purposes. For commercial inquiries, please see above contact information.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
You understand and agree that the authors are under no obligation to provide either maintenance services, update services, notices of latent defects, or corrections of defects with regard to the Software. The authors nevertheless reserve the right to update, modify, or discontinue the Software at any time.
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
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