Gaussian Splatting

NeRFs

  • MobileNeRF: This approach adapts NeRFs for mobile devices by exploiting the polygon rasterization pipeline for efficient neural field rendering. It achieves very fast rendering times (0.016-0.017s) but requires long training times.
  • MobileR2L: This method uses a full CNN-based neural light field model with a super-resolution model in its second stage. It achieves real-time inference on mobile devices while maintaining high image quality, rendering a 1008x756 image of real 3D scenes in 18.04ms on an iPhone 13.
  • Instant NGP (Neural Graphics Primitives): Developed by NVIDIA, this technique significantly speeds up the training and rendering of NeRFs, allowing for near-instantaneous scene reconstruction.
  • Plenoxels (Plenoptic Voxels): This method replaces neural networks with a sparse 3D grid of spherical harmonics, enabling faster training and competitive quality compared to NeRFs.
  • NGLOD (Neural Geometric Level of Detail): This approach combines neural implicit representations with explicit geometric representations, allowing for multi-resolution rendering and faster training.
  • NeRF-MAE (Masked AutoEncoders for NeRFs): This technique applies the concept of masked autoencoders to NeRFs for self-supervised 3D representation learning, potentially improving generalization and efficiency.

NeRFs vs Hardware Acceleration

PaperNeural Network TypeResidual LayerConcatenation LayerSuitability for Low-end Mobile Hardware
GIRAFFEMLP, CNNRequiredRequired7
Render NetMLP, CNNNot RequiredRequired6
Neural Voxel RendererMLP, CNNNot RequiredRequired5
Neural VolumesMLP, CNNNot RequiredRequired5
NeRFMLPNot RequiredRequired8
NeRF in the WildMLPNot RequiredRequired7
KiloNeRFMLPNot RequiredRequired8
FastNeRFMLPNot RequiredRequired9
PlenoctreesMLPNot RequiredRequired8
Instant Neural Graphics PrimitivesMLPNot RequiredRequired9
Scene Representation NetworksMLPNot RequiredRequired7
Extracting Motion and AppearanceMLP, CNN, TransformerRequiredRequired6
Instant 3DMLPNot RequiredRequired8
Neural Point Cloud RenderingCNN, U-NetNot RequiredRequired6
Deep ShadingCNNNot RequiredRequired6
Neural Reflectance FieldsCNNRequiredNot Required7
Deep IlluminationGAN, U-NetNot RequiredRequired5
Common Objects in 3DMLP, TransformerRequiredRequired7
GeoNeRFTransformerRequiredRequired7
Gen-NeRFTransformerRequiredRequired7