High resolution neural rendering

Methods and systems are provided for training a machine learning model to generate density values and radiance components based on positional data, along with a weighting scheme associated with a particular view direction based on directional data to compute a final RGB value for each point along a plurality of camera rays. The positional data and directional data are extracted from set of training images of a particular static scene. The radiance components, density values, and weighting schemes are cached for efficient image data processing to perform volume rendering for each point sampled. A novel viewpoint of a static scene is generated based on the volume rendering for each point sampled.