TensorFlow Graphics offers a collection of differentiable graphics layers that can be embedded into neural network architectures. It bridges computer graphics and deep learning by providing tools like spatial transformers, camera models, lighting models, and differentiable renderers. These layers enable networks to leverage geometric priors and constraints for more robust, efficient, and self-supervised training.