How 21st Century Technology Is Preserving Ukrainian Heritage Sites

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In February of 2022, Russian troops swept into Ukraine, leading to the destruction of hundreds of religious and historical buildings and dozens of public monuments, libraries, and museums. Backup Ukraine, a collaborative project between the Danish UNESCO National Commission and Polycam, uses 3D capturing technology to preserve Ukrainian heritage sites, allowing anyone with a phone to create high quality 3D models. Lidar scanners and neural radiance fields (NRF) are two technology trends driving this progress, as they are cheaper and require fewer scans than before.


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As a weapon of war, destroying cultural heritage sites is a common method by armed invaders to deprive a community of their distinct identity. It was no surprise then, in February of 2022, as Russian troops swept into Ukraine, that historians and cultural heritage specialists braced for the coming destruction. So far in the Russia-Ukraine War, UNESCO has confirmed damage to hundreds of religious and historical buildings and dozens of public monuments, libraries, and museums.

The Russia-Ukraine War began in February of 2022

While new technologies like low-cost drones, 3D printing, and private satellite internet may be creating a distinctly 21st century battlefield unfamiliar to conventional armies, another set of technologies is creating new possibilities for citizen archivists off the frontlines to preserve Ukrainian heritage sites.

Backup Ukraine, a collaborative project between the Danish UNESCO National Commission and Polycam, a 3D creation tool, enables anyone equipped with only a phone to scan and capture high-quality, detailed, and photorealistic 3D models of heritage sites, something only possible with expensive and burdensome equipment just a few years ago.

Backup Ukraine is a collaborative project between the Danish UNESCO National Commission and Polycam

Backup Ukraine is a notable expression of the stunning speed with which 3D capture and graphics technologies are progressing, according to Bilawal Sidhu, a technologist, angel investor, and former Google product manager who worked on 3D maps and AR/VR.

"Reality capture technologies are on a staggering exponential curve of democratization," he explained to me in an interview for Singularity Hub.

According to Sidhu, generating 3D assets had been possible, but only with expensive tools like DSLR cameras, lidar scanners, and pricey software licenses. As an example, he cited the work of CyArk, a non-profit founded two decades ago with the aim of using professional grade 3D capture technology to preserve cultural heritage around the world.

Apple introduced lidar scanning to its iPhone 12 Pro and Pro Max in 2020

"What is insane, and what has changed, is today I can do all of that with the iPhone in your pocket," he says.

In our discussion, Sidhu laid out three distinct yet interrelated technology trends that are driving this progress. First is a drop in cost of the kinds of cameras and sensors which can capture an object or space. Second is a cascade of new techniques which make use of artificial intelligence to construct finished 3D assets. And third is the proliferation of computing power, largely driven by GPUs, capable of rendering graphics-intensive objects on devices widely available to consumers.

Google introduced neural radiance fields, commonly referred to as NRF, in 2020

Lidar scanners are an example of the price-performance improvement in sensors. First popularized as the bulky spinning sensors on top of autonomous vehicles, and priced in the tens of thousands of dollars, lidar made its consumer-tech debut on the iPhone 12 Pro and Pro Max in 2020. The ability to scan a space in the same way driverless cars see the world meant that suddenly anyone could quickly and cheaply generate detailed 3D assets. This, however, was still only available to the wealthiest Apple customers.One of the industry’s most consequential turning points occurred that same year when researchers at Google introduced neural radiance fields, commonly referred to as NRF. The technique, which utilizes AI, requires far fewer scans and simpler hardware than previous 3D capturing techniques.

3D capturing used to require expensive tools, such as DSLR cameras, lidar scanners, and pricey software

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