For more information about preparing datasets for use with our NeRF implementation, please see [this document](docs/nerf_dataset_tips.md).
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## Thanks
Many thanks to [Jonathan Tremblay](https://research.nvidia.com/person/jonathan-tremblay) and [Andrew Tao](https://developer.nvidia.com/blog/author/atao/) for testing early versions of this codebase and to Arman Toornias and Saurabh Jain for the factory robot dataset.
Many thanks to [Jonathan Tremblay](https://research.nvidia.com/person/jonathan-tremblay) and [Andrew Tao](https://developer.nvidia.com/blog/author/atao/) for testing early versions of this codebase and to Arman Toorians and Saurabh Jain for the factory robot dataset.
We also thank [Andrew Webb](https://github.com/grey-area) for noticing that one of the prime numbers in the spatial hash was not actually prime; this has been fixed since.
This project makes use of a number of awesome open source libraries, including:
*[tiny-cuda-nn](https://github.com/NVlabs/tiny-cuda-nn) for fast CUDA MLP networks
<em>Lucy</em> model from the <ahref="http://graphics.stanford.edu/data/3Dscanrep/">Stanford 3D scan repository</a>
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<em>Factory robot</em> dataset by Arman Toornias and Saurabh Jain.
<em>Factory robot</em> dataset by Arman Toorians and Saurabh Jain.
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<em>Disney Cloud</em> model by Walt Disney Animation Studios. (<ahref="https://media.disneyanimation.com/uploads/production/data_set_asset/6/asset/License_Cloud.pdf">CC BY-SA 3.0</a>)