Awesome

VD-Diff

Official implementation of Paper "Rethinking Video Deblurring with Wavelet-Aware Dynamic Transformer and Diffusion Model" (ECCV 2024)

Requirements

You can create a new environment named VD-Diff by running

conda create -n VD-Diff python==3.10
conda activate VD-Diff
pip install -r requirements.txt

Datesets

First, download GoPro dataset and put it in "dataset" folder as the form below: <br>

• dataset<br>
  • GoPro
    • test
      • blur
      • sharp
    • train
      • blur
      • sharp

Train

Training Stage One

To train your own S1 model on the GoPro dataset, simply use the following command:

python basicsr/train.py -opt options/train/train_GoPro_S1.yml

Your S1 model weights will be saved in the directory: "experiments/GOPRO_S1/models/".

Training Stage Two

In this stage, update the "pretrain_network_S1" entry in "options/train/train_GoPro_S2.yml" with the path to your S1 model weights. Then, execute the following command:

python basicsr/train.py -opt options/train/train_GoPro_S2.yml

Training Stage Three

For Stage Three, modify the "pretrain_network_S2" entry in "options/train/train_GoPro_S3.yml" to point to your S2 model weights. Next, run:

python basicsr/train.py -opt options/train/train_GoPro_S3.yml

Test

First, modify the "pretrain_network_g" entry in "options/test/test_GoPro_S3.yml" to your S3 model weights. Then run:

python basicsr/test.py -opt options/test/test_GoPro_S3.yml

You can also test your S1 and S2 model by changing the ".yml" option file path accordingly.

Pretrained Models

Pretrained models will be available in a few days.