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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Instant neural graphics primitives: lightning fast NeRF and more
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# Instant Neural Graphics Primitives  <img src="docs/assets_readme/fox.gif" height="342"/> <img src="docs/assets_readme/robot5.gif" height="342"/> 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__](https://github.com/NVlabs/tiny-cuda-nn) framework. > __Instant Neural Graphics Primitives with a Multiresolution Hash Encoding__ > [Thomas Müller](https://tom94.net), [Alex Evans](https://research.nvidia.com/person/alex-evans), [Christoph Schied](https://research.nvidia.com/person/christoph-schied), [Alexander Keller](https://research.nvidia.com/person/alex-keller) > _ACM Transactions on Graphics (__SIGGRAPH__), July 2022_ > __[Project page](https://nvlabs.github.io/instant-ngp) / [Paper](https://nvlabs.github.io/instant-ngp/assets/mueller2022instant.pdf) / [Video](https://nvlabs.github.io/instant-ngp/assets/mueller2022instant.mp4) / [Presentation](https://tom94.net/data/publications/mueller22instant/mueller22instant-gtc.mp4) / [Real-Time Live](https://tom94.net/data/publications/mueller22instant/mueller22instant-rtl.mp4) / [BibTeX](https://nvlabs.github.io/instant-ngp/assets/mueller2022instant.bib)__ For business inquiries, please submit the [NVIDIA research licensing form](https://www.nvidia.com/en-us/research/inquiries/). ## Installation 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](https://github.com/NVlabs/instant-ngp/releases/download/continuous/Instant-NGP-for-RTX-5000.zip) - [**RTX 3000 & 4000 series, RTX A4000–A6000**, and other Ampere & Ada cards](https://github.com/NVlabs/instant-ngp/releases/download/continuous/Instant-NGP-for-RTX-3000-and-4000.zip) - [**RTX 2000 series, Titan RTX, Quadro RTX 4000–8000**, and other Turing cards](https://github.com/NVlabs/instant-ngp/releases/download/continuous/Instant-NGP-for-RTX-2000.zip) - [**GTX 1000 series, Titan Xp, Quadro P1000–P6000**, and other Pascal cards](https://github.com/NVlabs/instant-ngp/releases/download/continuous/Instant-NGP-for-GTX-1000.zip) Keep reading for a guided tour of the application or, if you are interested in creating your own NeRF, watch [the video tutorial](https://www.youtube.com/watch?v=3TWxO1PftMc) or read the [written instructions](docs/nerf_dataset_tips.md). If you use Linux, or want the [developer Python bindings](https://github.com/NVlabs/instant-ngp#python-bindings), or if your GPU is not listed above (e.g. Hopper, Volta, or Maxwell generations), you need to [build __instant-ngp__ yourself](https://github.com/NVlabs/instant-ngp#building-instant-ngp-windows--linux). ## Usage <img src="docs/assets_readme/testbed.png" width="100%"/> __instant-ngp__ comes with an interactive GUI that includes many features: - [comprehensive controls](https://github.com/NVlabs/instant-ngp#keyboard-shortcuts-and-recommended-controls) for interactively exploring neural graphics primitives, - [VR mode](https://github.com/NVlabs/instant-ngp#vr-controls) 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, - and many more. ### NeRF fox Simply start `instant-ngp` and drag the `data/nerf/fox` folder into the window. Or, alternatively, use the command line: ```sh instant-ngp$ ./instant-ngp da
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Thomas Müller
665
AIST · Japan
17
Jad Abou-Chakra · QUT Centre for Robotics · Australia
12
Ziyi
6
Yen-Chen Lin
5
Ily83
4
James Perlman · United States
4
Tavius Koktavy · United States
4
United States
3
Jiabao Lei · China
3
Tomáš Karabela · ENGINN EFFECT, s.r.o. · Czech Republic
3
3
Rebecca J
3
Switzerland
3
Julius Jacobsohn · Germany
2
franz96521
2
Francisco Javier Gañán · Movumtech · Spain
2
Sang Min Kim · Seoul National University · South Korea
2
Paul Wais
2
Michael Paniagua · Azerbaijan
2
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:2b3e118160d0656e, topic:computer-vision, topic:nerf, topic:3d-reconstruction