Y. Tsuji, Y. Yatagawa, H. Kubo, and S. Morishima, "Event-based Camera Simulation using Monte Carlo Path Tracing with Adaptive Denoising," In Proceedings of the IEEE International Conference on Image Processing, 2023. (to appear) [Preprint]
Prepare virtualenv using Poetry.
# Install required modules
poetry install --no-dev
# Enable Poetry's virtualenv
poetry shell- SanMiguel: https://drive.google.com/file/d/1B8Juxd1llp__96dWlXDegZ-YuBRj27rc/view?usp=share_link
- TwoBoxes: https://drive.google.com/file/d/1XWpIgi9oR5SpYOAm_1CbnvixrfL42HdK/view?usp=drive_link
- LivingRoom: https://drive.google.com/file/d/1prC6BAMmmqR0TJklhVbuiB3BnrlXJS4y/view?usp=drive_link
Then, unzip the archive and store in the data folder. If the data is sanmiguel, four subdirectories (i.e., 32spp, 64spp, 128spp, and 4096spp) will be stored in data/sanmiguel.
# To reproduce our results in the paper, run the following.
python main.py --data_root /path/to/data --spp 32 --ksize 13 --wlr simple --thres 1.00The default parameters used to generate the following results are shown in run.sh. After running the above code, you can visually compare our method with other baselines with analysis.ipynb in the notebooks folder.
LivingRoom-comp.mp4
SanMiguel-comp.mp4
TwoBoxes-comp.mp4
Note that the above videos are compressed to fit the 10MB file size limit of GitHub. You can find uncompressed ones in the following URL:
https://drive.google.com/file/d/1hPtCmBYmo7h-aczLSPVK8ZIK8_sUJ4nW/view?usp=share_link
Also, you can find the quantitative comparisons in the supplementary document in the following URL:
https://drive.google.com/file/d/1gJsuApMHOO-PPWweZ849QaGdr0OQsjyl/view?usp=share_link
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
(c) Yuta Tsuji, Tatsuya Yatagawa, Hiroyuki Kubo, and Shigeo Morishima.