Deep Lidar-Guided Image Deblurring

This repository contains the official implementation for "Deep Lidar-Guided Image Deblurring"

Requirements

The code has been tested with the following dependencies:

• python 3.10
• pytorch 2.0.1
• natten (for DeblurDiNATL)

Dataset

The code uses the ARKitScenes datasets, available for download from https://github.com/apple/ARKitScenes

How to train

1. config your train hyperparameter in config/*.yaml
2. run

python main.py -task train -model_type original -model_task Deblur/DepthDeblur/KernelDeblur/KernelDepthDeblur -device cuda/cpu

How to test

1. config your train hyperparameter in config/*.yaml
2. run

python main.py -task test -model_type original -model_task Deblur/DepthDeblur/KernelDeblur/KernelDepthDeblur -device cuda/cpu

Pre-trained Models

You can download pretrained models here: https://www.dropbox.com/scl/fo/1vdmlh64yhs3dr1ilkowf/AJXGJdKxE7VHG9D5ss_XUiM?rlkey=27874gc4gkj6qgoxisqzggpae&st=j6l55k7z&dl=0

Acknowledgement

This study was carried out within the “AI-powered LIDAR fusion for next-generation smartphone cameras (LICAM)” project – funded by European Union – Next Generation EU within the PRIN 2022 program (D.D. 104 - 02/02/2022 Ministero dell’Università e della Ricerca). This manuscript reflects only the authors' views and opinions and the Ministry cannot be considered responsible for them.

License

Our code is released under MIT License (see LICENSE file for details).