If you have a limited number of images of the same scene, with NeRF you can generate new images from different positions and angles (novel view synthesis). But

If you have a limited number of images of the same scene, with NeRF you can generate new images from different positions and angles (novel view synthesis). But this only works with rigid scenes: e.g. if you apply NeRF to images of a person, they cannot move between the pictures. This is what HyperNeRF is trying to solve. If there are pictures of a person, and in one of them they are smiling but on another not, 1. this method will not fail, and 2. looks like it will give reasonable new views/images.