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3D Realism
  • Brands.
  • Studios.
  • Creators.

We are developing the next generation 3D capture system for accurate and automatic 3D conversion of the real-world.


The initial research and development of our first precision scanning system. This system is capable of capturing objects to a high level of fidelity; able to capture thread level detail, accurate depth, accurate diffuse and specular maps. Whilst roughness and transparency maps are estimated. This system was used to capture the industry renowned Nike AR shoe that went viral across social channels. We are currently using this system to service our partners.

Our current R&D focus is how we achieve full texture acquisition universally across a captured object. Our semi-automated patent pending system uses custom optics and machine learning to extract a full range of material properties, such as diffuse, specular, roughness, IOR and transparency. This is key to achieving accurate 3D conversion of real-world objects. Giving the end user a sense that 3D models are real due to the fact 3D models react to lighting correctly.

During this phase we will look to conclude our 3D capture methodology. The proposed system aims to capture an object automatically whilst extracting the full array of texture maps. The generated 3D asset will then progress through an automated pipeline for optimisation. Once complete, the aim is to convert the 3D model into an array of LODs (level of detail) to be used for any desired application: AR/VR, Film and AAA Games.

At this stage, we aim to provide the industry with a system which is able to accurately convert real-world objects into 3D assets at scale. Enabling brands, studios and creators to leverage the infinite world of 3D with highly realistic 3D assets.

*click each stage to find out more

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We undertake interesting research and development focused projects that push the bounds of the future of 3D experiences. Establishing new techniques backed by compelling creatives.





Studio 7,

5 Hancock Rd,


United Kingdom

E3 3DA