old photo restoration

We have hosted the application old photo restoration in order to run this application in our online workstations with Wine or directly.

Quick description about old photo restoration:

We propose to restore old photos that suffer from severe degradation through a deep learning approach. Unlike conventional restoration tasks that can be solved through supervised learning, the degradation in real photos is complex and the domain gap between synthetic images and real old photos makes the network fail to generalize. Therefore, we propose a novel triplet domain translation network by leveraging real photos along with massive synthetic image pairs. Specifically, we train two variational autoencoders (VAEs) to respectively transform old photos and clean photos into two latent spaces. And the translation between these two latent spaces is learned with synthetic paired data. This translation generalizes well to real photos because the domain gap is closed in the compact latent space. Besides, to address multiple degradations mixed in one old photo, we design a global branch with a partial nonlocal block targeting to the structured defects, such as scratches and dust spots.

Features:

• Old Photo Restoration via Deep Latent Space Translation, TPAMI 2022
• The framework now supports the restoration of high-resolution input
• Training code is available and welcome to have a try and learn the training details
• You can now play with our Colab and try it on your photos
• The code is tested on Ubuntu with Nvidia GPUs and CUDA installed
• Python>=3.6 is required to run the code

Programming Language: Python.
Categories: