Open source code for the paper of Neural Sparse Voxel Fields

Open source code for the paper of Neural Sparse Voxel Fields

Open source code for the paper of Neural Sparse Voxel Fields. Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers. Methods used in the Paper.

Neural Sparse Voxel Fields (NSVF)

Photo-realistic free-viewpoint rendering of real-world scenes using classical computer graphics techniques is a challenging problem because it requires the difficult step of capturing detailed appearance and geometry models. Neural rendering is an emerging field that employs deep neural networks to implicitly learn scene representations encapsulating both geometry and appearance from 2D observations with or without a coarse geometry. However, existing approaches in this field often show blurry renderings or suffer from slow rendering process. We propose Neural Sparse Voxel Fields (NSVF), a new neural scene representation for fast and high-quality free-viewpoint rendering.

Requirements and Installation

This code is implemented in PyTorch using fairseq framework.

The code has been tested on the following system:

  • Python 3.7
  • PyTorch 1.4.0
  • Nvidia apex library (optional)
  • Nvidia GPU (Tesla V100 32GB) CUDA 10.1

Only learning and rendering on GPUs are supported.

To install, first clone this repo and install all dependencies:

pip install -r requirements.txt


Then, run

pip install --editable ./


Or if you want to install the code locally, run:

python build_ext --inplace

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