Generating feature fields
The first step of the scene generation process is generating a feature field. This is analogous to generating an RGB image in the NeRF model. In the NeRF model, the output of the model is a feature field that happens to be an image made up of RGB values. However, a feature field can be any abstract notion of the image. It is a generalization of an image matrix. The difference here is that instead of generating a three-channel RGB image, the GIRAFFE model generates a more abstract image that we refer to as the feature field with dimensions HV, WV, and Mf, where HV is the height of the feature field, WV is its width, and Mf is the number of channels in the feature field.
For this section, let us assume that we have a trained GIRAFFE model. It has been trained on some predefined dataset that we are not going to think about now. To generate a new image, we need to do the following three things:
- Specify the camera pose: This defines the viewing angle...
