This AI Restores Old Photos with Damages Automatically!

Introduction

Recently, a fascinating advancement in face enhancement methods has emerged, particularly focused on image restoration. The approach, known as DFD Net, diverges from conventional upscaling techniques by disassembling essential facial features such as the eyes and mouth. By using a library of facial features as references, this method generates highly detailed and accurate enhancements to replace the original features. This innovation is a significant leap towards creating a comprehensive image restoration program.

Not long after DFD Net's unveiling, Microsoft debuted an open-source AI named "Bring Photos Back to Life." Upon reviewing the official, carefully curated results from this new AI, it's clear that it boasts numerous impressive functions. These include noise tone readjustment, phase enhancement, and, most notably, physical damage restoration. This new capability extends beyond merely erasing scratches; it can also eliminate food marks, brown spots, and other imperfections, showcasing a holistic approach to photo restoration.

One question persists: How effectively can this AI restore our personal images? Before diving into the testing process, it's important to clarify that there is a specific function requiring users to indicate whether their input images have scratches. Although this function isn't limited to scratches alone, its activation is essential since it allows the AI to focus on restoring physical damage. After all, the allure of this new AI largely lies in its ability to remove scratches, a task that previous AIs found challenging.

To test the AI's capabilities, I curated a selection of images from the r/e_restoration and r/oldschoolcool subreddits, categorizing them based on the restoration difficulty they present.

Easy Restoration Category

The first set of images consisted of those with minor damage. An interesting example is a completely black image with white markings over it, serving as a masking layer generated by the AI to highlight areas deemed as scratches. The results reveal how the AI interprets various damages and determines which areas to patch using pixel generation techniques, often labeled as "inpainting." Given that this group mostly featured thin or small damages, the overall restoration quality was commendable, and the color adjustments contributed positively to the final images. While some may argue that detecting smaller scratches poses a challenge for the AI, it is evident why these images were designated as easy to restore.

Hard Restoration Category

In contrast, another set of photos displayed severe damage, requiring the AI to repair substantial color loss and reconstruct vital facial features, such as eyes. The outcome of this test is particularly revealing regarding the AI's proficiency in inpainting. When the damage is too extensive, the risk increases that the AI will create results that look unnatural or discordant with human features. Although the AI performs admirably in certain instances, the overall conclusion for these severely damaged images indicates that while it shows promise, there are significant improvements needed for consistent restoration results.

Integrating techniques from DFD Net into future iterations of this AI could enhance its ability to replace damaged features more effectively. With promising yet imperfect restoration capabilities, there's potential for further development that may lead to superior outcomes in future AI-generated restorations.

To explore these features and test the AI on your images, I will provide a link to the collaborative tool in the description, along with a brief tutorial.

Keyword

AI, image restoration, DFD Net, Microsoft, Bring Photos Back to Life, physical damage restoration, noise tone readjustment, inpainting, old photos, digital enhancement.

FAQ

1. What is DFD Net and how does it work?
DFD Net is an advanced face enhancement method that disassembles important facial features for reference, allowing accurate and detailed restorations.

2. What features does Microsoft's AI, "Bring Photos Back to Life," offer?
The AI includes functions for noise tone readjustment, phase enhancement, and physical damage restoration, such as removing scratches and food marks.

3. How do I know if my image has scratches?
The AI offers a specific function where users can indicate the presence of scratches. Activating this will prompt the AI to focus on restoring these damages effectively.

4. Is the AI effective in restoring damaged images?
The AI shows impressive results with minor damages but struggles with severely damaged images, often producing unnatural outcomes. Further improvements are anticipated for better future performance.

5. Where can I try this AI for restoring my own images?
A link to the collaborative tool for using the AI, along with a tutorial, will be provided in the video description for user convenience.