Write code to train a NeRF model with adversarial loss to improve photo-realism

Question

Can you write code to train a NeRF model with adversarial loss to improve photo-realism?

Answer 1

You can train a NeRF model with adversarial loss to improve photo-realism by integrating a discriminator network that enhances the realism of the rendered images.

Here is the code snippet you can refer to:

In the above code, we are using the following key points:

• Uses a NeRF model for 3D scene rendering
• Employs an adversarial discriminator to enhance realism
• Minimizes both reconstruction and adversarial loss
• Uses separate optimizers for NeRF (Generator) and Discriminator
• Integrates MSE loss for scene accuracy and BCE loss for adversarial learning

Hence, integrating adversarial loss into NeRF training enhances photo-realism by forcing the generator to produce more realistic rendered images that can fool the discriminator.