Neural Visibility Cache for Real-Time Light Sampling

Direct illumination with many lights is an inherent component of physically-based rendering, remaining challenging, especially in real-time scenarios. We propose an online-trained neural cache that stores visibility between lights and 3D positions. We feed light visibility to weighted reservoir sampling (WRS) to sample a light source. The cache is implemented as a fully-fused multilayer perceptron (MLP) with multi-resolution hash-grid encoding, enabling online training and efficient inference on modern GPUs in real-time frame rates. The cache can be seamlessly integrated into existing rendering frameworks and can be used in combination with other real-time techniques such as spatiotemporal reservoir sampling (ReSTIR).

@article{bokšanský2025_2506.05930,
  title={ Neural Visibility Cache for Real-Time Light Sampling },
  author={ Jakub Bokšanský and Daniel Meister },
  journal={arXiv preprint arXiv:2506.05930},
  year={ 2025 }
}