- Re-implementing Denoising Diffusion Probabilistic Models and Denoising Diffusion Implicit Models using Pytorch
- DDPM
- DDIM
- Denoising Diffusion Probabilistic Models (Paper link)
- Denoising Diffusion Implicit Models (Paper link)
- DDPM
python main.py --model_type=ddpm
- DDIM
python main.py --model_type=ddim
- DDPM
- DDIM
- Quantitative result
| Model | FID | IS | #Params |
|---|---|---|---|
| DDPM | - | - | - |
| DDIM | - | - | - |
-
Qualitative result (WIP, attach more images later !, Below images are trained model result !)
- DDPM
model_460000_t_1000_num_0 model_460000_t_900_num_0 model_460000_t_800_num_0 model_460000_t_700_num_0 model_460000_t_600_num_0 model_460000_t_500_num_0 model_460000_t_400_num_0 model_460000_t_300_num_0 model_460000_t_200_num_0 model_460000_t_100_num_0 model_460000_t_2_num_0
- DDIM
model_700000_t_1000_num_0 model_700000_t_900_num_0 model_700000_t_800_num_0 model_700000_t_700_num_0 model_700000_t_600_num_0 model_700000_t_500_num_0 model_700000_t_400_num_0 model_700000_t_300_num_0 model_700000_t_200_num_0 model_700000_t_100_num_0 model_700000_t_2_num_0
- Example (Below image is paper result)
- Usage
python metric/fid_test.py --cuda=True
- Usage
WIP
@article{ho2020denoising, title={Denoising diffusion probabilistic models}, author={Ho, Jonathan and Jain, Ajay and Abbeel, Pieter}, journal={Advances in Neural Information Processing Systems}, volume={33}, pages={6840--6851}, year={2020} }
@article{song2020denoising, title={Denoising diffusion implicit models}, author={Song, Jiaming and Meng, Chenlin and Ermon, Stefano}, journal={arXiv preprint arXiv:2010.02502}, year={2020} }