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Retrieval-Robust-to-Object-Motion-Blur

Description

Pytorch code for paper: Retrieval Robust to Object Motion Blur

Accepted by <strong><em>ECCV 2024</em></strong>

Rong Zou, Marc Pollefeys and Denys Rozumnyi

Installation

The code is tested with Python 3.8.16.

Install this repository using the following commands:

# Clone the repository
git clone https://github.com/Rong-Zou/Retrieval-Robust-to-Object-Motion-Blur.git

# Change to the project directory
cd Retrieval-Robust-to-Object-Motion-Blur

# Install dependencies
pip install -r requirements.txt

Data Preparation

Download dataset zips from this link, and extract the data.

You may use the following commands:

# Download the dataset
wget https://cvg-data.inf.ethz.ch/romb/real_data.zip
wget https://cvg-data.inf.ethz.ch/romb/synthetic_data.zip
wget https://cvg-data.inf.ethz.ch/romb/synthetic_data_distractors.zip

# Unzip the dataset to ./data/, change the target path to your desired directory
unzip real_data.zip -d data/
unzip synthetic_data.zip -d data/
unzip synthetic_data_distractors.zip -d data/

See the dataset page for more details.

Pretrained Model

Download our pre-trained model from this link.

For testing, put the model in the directory same as the link file.

Testing

First modify the parameter values in the set_data_dirs.py script to configure the correct directories.

Test the model by running the testing script test.py:

python3 test.py

License

This project is licensed under the MIT License.

Citation

@inproceedings{blur_retrieval,
  author = {Rong Zou and Marc Pollefeys and Denys Rozumnyi},
  title = {Retrieval Robust to Object Motion Blur},
  booktitle = {European Conference on Computer Vision (ECCV)},
  year = {2024}
}