We provide an implementation of the photometric stereo method presented in the following paper. The code can be used for research purpose only. If you find our code useful for your research, please cite our paper.
@inproceedings{Taniai18,
author = {Tatsunori Taniai and
Takanori Maehara},
title = {{Neural Inverse Rendering for General Reflectance Photometric Stereo}},
booktitle = {{Proceedings of the 35th International Conference on Machine Learning (ICML)}},
pages = {4864--4873},
year = {2018},
}
- Python 3.5+
- Chainer 3.4 (or maybe higher version is acceptable)
- numpy
- CUDA and cuDNN (if use the GPU mode "-g 0")
Move to chainer_code directory and enter the following command.
For CPU mode
python train.py -t 0
For GPU dode
python train.py -t 0 -g 0
| Options | Type | Settings |
|---|---|---|
| --gpu (-g) | int | GPU ID to use |
| --target (-t) | int (0-9) | Scene number from 0 to 9 (ball to reading) |