Summary

In this chapter, we came to understand how a neural network can be used to model and represent a 3D scene. This neural network is called the NeRF model. We then trained a simple NeRF model on a synthetic 3D scene. We then dug deeper into the NeRF model architecture and its implementation in code. We also understood the main components of the model. We then understood the principles behind rendering volumes with the NeRF model. The NeRF model is used to capture a single scene. Once we build this model, we can use it to render that 3D scene from different angles. It is logical to wonder whether there is a way to capture multiple scenes with a single model and whether we can predictably manipulate certain objects and attributes in the scene. This is our topic of exploration in the next chapter where we will explore the GIRAFFE model.