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Mip-Grid: Anti-aliased Grid Representations for Neural Radiance Fields

Seungtae Nam, Daniel Rho, Jong Hwan Ko, Eunbyung Park*
*Corresponding author
in Neural Information Processing Systems (NeurIPS), 2023

Architecture overview

architecture

  • Mip-Grid generates multi-scale grids by applying convolution to a single-scale grid with learnable kernels.
  • Two multi-scale grids closest to given scales are interpolated.

Environment setup

1. Install Docker and NVIDIA Container Toolkit

  • please follow the official document for installation.
  • if you already installed both of them, please skip this part.

2. Build the docker image

  • run the command below at "/your/path/to/MipGrid".
  • don't forget to include the dot . at the end.
docker build -t mipgrid_environment .

3. Run the docker image

  • run the command below at "/your/path/to/MipGrid".
  • please also change the dataset path ("/your/path/to/dataset").
docker run -it \
    -v ./:/workspace \
    -v /hdd/stnamjef/dataset:/workspace/dataset \
    --ipc host \
    --gpus all \
    --name mipgrid \
    mipgrid_environment:latest

Training

  • run the commands below at "/your/path/to/mipTensoRF" inside the docker container.

  • original TensoRF on the multi-scale Blender dataset.

bash ./scripts/blender/tensor_vm.sh
  • single-scale TensoRF on the multi-scale Blender dataset.
bash ./scripts/blender/singlescale_tensor_vm.sh
  • multi-scale TensoRF on the multi-scale Blender dataset.
bash ./scripts/blender/multiscale_tensor_vm.sh
  • mipTensoRF (disc.) on the multi-scale Blender dataset.
bash ./scripts/blender/mip_tensor_vm_discrete.sh
  • mipTensoRF (cont.) on the multi-scale Blender dataset.
bash ./scripts/blender/mip_tensor_vm_continuous.sh
  • mipTensoRF (2D) on the multi-scale Blender dataset.
bash ./scripts/blender/mip_tensor_vm_2d.sh

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