DirectVoxGO optimizes a dense voxel grid directly to represent scene geometry and appearance, replacing the MLP backbone in NeRF for faster training and rendering. It uses dense 3D voxel grids for volume densities and 4D feature grids with shallow MLPs for view-dependent colors. The project includes custom CUDA extensions for additional speedup and implements an efficient O(N) distortion loss, with support for bounded and unbounded scene datasets.