TAF: An Implicit Neural Representation for the Image Stack: Depth, All in Focus, and High Dynamic Range [Siggrapha Aisa 2023]
Use the following commands with Anaconda to create and activate your environment:
conda env create -f environment.yml
conda activate TAF
python train.py --save_path "./results" --base_path "./dataset/scene_1/"
please change the base_path to your own dataset path
python test.py
please modify the wieghts path to your own for testing, here we include pre-trained weights in folder “weight” as an example.
@article{wang2023implicit,
title={An Implicit Neural Representation for the Image Stack: Depth, All in Focus, and High Dynamic Range},
author={Wang, Chao and Serrano, Ana and Pan, Xingang and Wolski, Krzysztof and Chen, Bin and Myszkowski, Karol and Seidel, Hans-Peter and Theobalt, Christian and Leimk{\"u}hler, Thomas},
journal={ACM Transactions on Graphics (TOG)},
volume={42},
number={6},
pages={1--11},
year={2023},
publisher={ACM New York, NY, USA}
}
}
This source code is derived from the (https://shnnam.github.io/research/nir/). We really appreciate the contributions of the authors to that repository.