Ever wanted to train a NeRF model of a fox in under 5 seconds? Or fly around a scene captured from photos of a factory robot? Of course you have!

Here you will find an implementation of four neural graphics primitives, being neural radiance fields (NeRF), signed distance functions (SDFs), neural images, and neural volumes. In each case, we train and render a MLP with multiresolution hash input encoding using the tiny-cuda-nn framework.

Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
Thomas Müller, Alex Evans, Christoph Schied, Alexander Keller
ACM Transactions on Graphics (SIGGRAPH), July 2022
Project page / Paper / Video / Presentation / Real-Time Live / BibTeX

For business inquiries, please submit the NVIDIA research licensing form.

If you have Windows, download one of the following releases corresponding to your graphics card and extract it. Then, start instant-ngp.exe.

• RTX 5000 series and other Blackwell cards
• RTX 3000 & 4000 series, RTX A4000–A6000, and other Ampere & Ada cards
• RTX 2000 series, Titan RTX, Quadro RTX 4000–8000, and other Turing cards
• GTX 1000 series, Titan Xp, Quadro P1000–P6000, and other Pascal cards

Keep reading for a guided tour of the application or, if you are interested in creating your own NeRF, watch the video tutorial or read the written instructions.

If you use Linux, or want the developer Python bindings, or if your GPU is not listed above (e.g. Hopper, Volta, or Maxwell generations), you need to build instant-ngp yourself.

instant-ngp comes with an interactive GUI that includes many features:

• comprehensive controls for interactively exploring neural graphics primitives,
• VR mode for viewing neural graphics primitives through a virtual-reality headset,
• saving and loading "snapshots" so you can share your graphics primitives on the internet,
• a camera path editor to create videos,
• NeRF->Mesh and SDF->Mesh conversion,
• camera pose and lens optimization,