LATEST UPDATE
Python API is working! Check examples/ folder.
Workin on the Blender integration now.
Estimated ETA on the Blender plugin is ~March 14, 2022
Still a lot to do...
After the Blender integration is complete, I will release a binary along with the addon codebase
INTRODUCTION
Hello NeRF enthusiasts! Here you will find my NeRF rendering and training library. The core principles of this NeRF method are based on the incredible work of Thomas Müller, Alex Evans, Christoph Schied, and Alex Keller, in their paper Instant neural graphics primitives with a multiresolution hash encoding.
Yes, I realize there is already a CUDA implementation, but I wanted to take a crack at reimplementing this myself for the challenge, and for artistic uses such as:
- Spatial distortions
- Multiple NeRFs in one scene
- Multi-GPU capabilities
- Shadertoy-style effects
- Fractals
Since everything here has been written from scratch*, this codebase is permissively licensed and commercial-use-friendly.
(*with generous help from NeRF, nerfstudio, NerfAcc, and completely built on the tiny-cuda-nn backend.)
DISCLAIMER: Although I am extremely passionate about NeRFs and their artistic applications, I do not have a deep background in ML research or CUDA development, and the code I've written here may certainly reflect that. But perhaps that's where you come in! Feel free to browse and suggest changes, this is all a learning process!
Enjoy!
-James
https://twitter.com/jperldev
INSTALLATION
Required toolkits:
Tested Configuration:
Build steps:
git clone git@github.com:JamesPerlman/NeRFRenderCore --recursive
cd NeRFRenderCore
cmake . -B build
cmake --build build -j
Until we have an extensible data loader, the test data I'm working with is here:
https://www.dropbox.com/sh/qkt4t1tk1o7pdc6/AAD218LLtAavRZykYl33mO8ia?dl=1
This project has only been tested on that one Lego scene. Real scenes appear to be broken for now.
THANK YOU
Extreme gratitude to open source projects that will allow this project to reach its full potential (in order of integration date):
- CUDA CMake Starter
- tiny-cuda-nn
- JSON for modern C++
- stb
- NeRF
- nerfstudio
- NerfAcc
- torch-ngp
- Nerfies
- glfw
- pybind11
- RenderMan
- glad
LICENSES TO BE ADDED TO CODEBASE SOON. CHECK LICENSES/ DIRECTORY
CITATIONS
Next-level respect to the researchers much of this codebase is based off. Thank you for making your research public. This would not have been possible without you.
Mildenhall, Ben, et al. "NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis." arXiv, 2020. doi:10.48550/arxiv.2003.08934 - (https://arxiv.org/abs/2003.08934)
Müller, Thomas, et al. "Instant neural graphics primitives with a multiresolution hash encoding." ACM Trans. Graph., 41(4), 102:1-102:15 - https://doi.org/10.1145/3528223.3530127
Max, Nelson. "Optical Models for Direct Volume Rendering." IEEE Transactions on Visualization and Computer Graphics (1995) - https://courses.cs.duke.edu/spring03/cps296.8/papers/max95opticalModelsForDirectVolumeRendering.pdf
Müller, T. (2021). tiny-cuda-nn (Version 1.7) [Computer software]. https://github.com/NVlabs/tiny-cuda-nn
Fawzi, A., Balog, M., Huang, A. et al. Discovering faster matrix multiplication algorithms with reinforcement learning. Nature 610, 47–53 (2022). https://doi.org/10.1038/s41586-022-05172-4
Alman, Josh, and Virginia Vassilevska Williams. "A Refined Laser Method and Faster Matrix Multiplication." arXiv, 2020, doi:10.48550/arxiv.2010.05846. https://arxiv.org/abs/2010.05846
Sabour, Sara, et al. "RobustNeRF: Ignoring Distractors with Robust Losses." arXiv, 2023, arXiv:2302.00833. https://arxiv.org/abs/2302.00833
SUPPORTERS
Extreme thank yous to these subscribers on Twitch (https://twitch.tv/jperldev) who support this project's development!
madclawgonzo - Requested a haiku written by ChatGPT: "Madclawgonzo / Subscribing to your stream / Software project."
anonymous - Requested to remain anonymous
gusround - https://github.com/candidogustavo
slowcon - "uncle slowcon is here with the 4090"
likid_3 - <3
cognitrol - Supporting cool work that helps the community explore technology
dankmatrix - (pending message)
seferidis - (pending message)
memepp - (pending message)
Dakren12 - (pending message)
Relakin - (Confused)
flouwr - (pending message)