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Samsung’s impressive AI turns video into digitally rendered VR worlds

As companies try to find ways to easily render the real world into virtual worlds, this is a space that is accelerating.

Key takeaways

  • In a paper detailing the neural network behind the AI, the researchers explained the inefficient process of creating virtual scenes today: From the real world to the digital one, in a flash.
  • See the tech for yourself As mentioned this type of product could one day help speed up game development, especially video game counterparts of movies that are already being filmed.
  • Before such use cases are realised though the tech still needs some refinement - current scenes can’t be altered or edited, and any large deviations from the original viewpoint results in distortions.
Cite or link to this article

Griffin, M. (2019) 'Samsung’s impressive AI turns video into digitally rendered VR worlds', 311 Institute, 2 September. Available at: https://www.311institute.com/ssmsungs-impressive-ai-turns-video-into-digitally-rendered-vr-worlds/ (Accessed: 1 October 2026).

Hot on the heels of Nvidia who recently released their own very impressive so called Video to Video Artificial Intelligence (AI) system, Samsung researchers have unveiled an AI that generates realistic 3D renders of video scenes that, like Nvidia’s solution, can then be edited and used in everything from the production of movies and video games, through to helping future consumers relive special memories in Virtual Reality (VR). And for my ten cents I think it’s the latter use cases that Samsung will focus on developing so keep an eye out for this feature appearing within the next five years in Samsung’s consumer products.

In a paper detailing the neural network behind the AI, the researchers explained the inefficient process of creating virtual scenes today:

From the real world to the digital one, in a flash. Courtesy: Samsung

“Creating virtual models of real scenes usually involves a lengthy pipeline of operations. Such modelling usually starts with a scanning process, where the photometric properties are captured using camera images and the raw scene geometry is captured using depth scanners or dense stereo matching,” they said, adding, “the latter process usually provides noisy and incomplete point cloud that needs to be further processed by applying certain surface reconstruction and meshing approaches. Given the mesh, the texturing and material estimation processes determine the photometric properties of surface fragments and store them in the form of 2D parameterized maps, such as texture maps, bump maps, view-dependent textures, surface lightfields. Finally, generating photorealistic views of the modelled scene involves computationally-heavy rendering process such as ray tracing and/or radiance transfer estimation.”

The video input is then converted into points which represent the geometry of the scene. These geometry points are then rendered into computer graphics using a neural network, and vastly speeding up the process of rendering a photorealistic 3D scene that can be translated into a VR world, and you can see the result in the video.

See the tech for yourself
 

As mentioned this type of product could one day help speed up game development, especially video game counterparts of movies that are already being filmed. Footage from a film set could provide a replica 3D environment for game developers to create interactive experiences in, but one of the most exciting new use cases, for example, would be letting consumers use it to relive their birthday parties or weddings and events by recording them and then having the solution automatically convert those videos into photorealistic VR worlds that would let them relive those memories all over again using just a VR headset and perhaps, even a haptic clothing like the Teslasuit, that helps them not just relive the moment through their eyes but also through their other senses.

Before such use cases are realised though the tech still needs some refinement - current scenes can’t be altered or edited, and any large deviations from the original viewpoint results in distortions. Still, it’s a fascinating early insight at what could be possible in a not-so-distant future.

Source: Arvix and Github

FAQ

Why does this matter?

As companies try to find ways to easily render the real world into virtual worlds, this is a space that is accelerating.

Matthew Griffin

About the author

Matthew Griffin Founder, 311 Institute

Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath."

Read full bio

Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath." 15-time best selling author of the "Codex of the Future" series, Matthew is the Founder and Futurist in Chief of the 311 Institute, a global Futures and Deep Futures advisory firm working with royal households, world leaders, G7, G20, and G77 governments, NGOs, and multi-national mid and mega cap firms to help them explore, shape, and lead the next 50 years of business and society.

An award-winning YouTube creator with over a million followers, with an unrivalled global reach and impact, Matthew is a highly sought-after international keynote speaker, lecturer, and mentor who collaborates with global leaders through the United Nations Alliance of Civilizations (UNAOC) and United Nations General Assembly (UNGA) to shape pivotal initiatives such as the UN’s AI for Humanity program, the United Nations Conference of the Parties (UN COP), and the World Economic Forum in Davos.

As the former Global Head of Cloud, National Security, and Enterprise Sales for companies including Atos, Dell-EMC, and IBM, Matthew has a proven track record of building multi-billion dollar business units and turning failing divisions into market leaders. His ability to identify, analyse, and communicate the implications of hundreds of emerging technologies and trends is unparalleled, and his insights are trusted by many of the world’s most respected organisations, including ABB, Accenture, Adidas, AON, ARM, BCG, Centrica, Citi, Coca-Cola, Dentons, Deloitte, Dow Jones, EY, Google, KPMG, Lego, Legal & General, LinkedIn, Microsoft, PepsiCo, Qualcomm, RWE, Samsung, Siemens AG and Siemens Energy, T-Mobile, UBS, VISA, Walmart, Workday, Worldpay and many others.

Regularly featured in the global media including the AP, BBC, Bloomberg, CNBC, Discovery, Forbes, Khaleej Times, Telegraph, TIME, ViacomCBS, WIRED, and the WSJ, Matthews mission is to help organisations create a fair and sustainable future whose benefits are shared by everyone irrespective of their ability, background, or circumstances.

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Starburst opens that technology on the interactive 311 Starburst.

Sources and further reading

  1. 1906.08240.pdf arxiv.org
  2. Neural point based graphics dmitryulyanov.github.io

Source: first published by the 311 Institute on 2 September 2019. Cite as: Griffin, M. (2019). Samsung’s impressive AI turns video into digitally rendered VR worlds. 311 Institute. https://www.311institute.com/ssmsungs-impressive-ai-turns-video-into-digitally-rendered-vr-worlds/

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