
NVIDIA Neuralangelo Research Reconstructs 3D Scenes
Brie Clayton June 2, 2023
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Neuralangelo, a new AI model by NVIDIA Research for 3D reconstruction using neural networks, turns 2D video clips into detailed 3D structures - generating lifelike virtual replicas of buildings, sculptures and other real-world objects.
Like Michelangelo sculpting stunning, life-like visions from blocks of marble, Neuralangelo generates 3D structures with intricate details and textures. Creative professionals can then import these 3D objects into design applications, editing them further for use in art, video game development, robotics and industrial digital twins.
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In a demo, NVIDIA researchers showcased how the model could recreate objects as iconic as Michelangelo's David and as commonplace as a flatbed truck. Neuralangelo can also reconstruct building interiors and exteriors - demonstrated with a detailed 3D model of the park at NVIDIA's Bay Area campus.
Neural surface reconstruction has been shown to be powerful for recovering dense 3D surfaces via image-based neural rendering. However, current methods struggle to recover detailed structures of real-world scenes. To address the issue, NVIDIA presents Neuralangelo, which combines the representation power of multi-resolution 3D hash grids with neural surface rendering.
May 3, 2023Latest NVIDIA Graphics Research Advances Generative AI's Next FrontierNVIDIA will present around 20 research papers at SIGGRAPH, the year's most
April 5, 2023DFT POLAR HQ Film Scanner Evolves at NAB 2023DFT, the leading provider of high-end film scanning solutions that preserves, manages
Two key ingredients enable the approach: (1) numerical gradients for computing higher-order derivatives as a smoothing operation and (2) coarse-to-fine optimization on the hash grids controlling different levels of details. Even without auxiliary inputs such as depth, Neuralangelo can effectively recover dense 3D surface structures from multi-view images with fidelity significantly surpassing previous methods, enabling detailed large-scale scene reconstruction from RGB video captures.
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