what is neural rendering

Neural rendering is a method that uses deep neural networks and physics engines to create novel images and video footage based on existing scenes. It combines machine learning techniques with physical knowledge from computer graphics to obtain controllable and photo-realistic models of scenes. The key concept behind neural rendering approaches is that they are differentiable, meaning that their derivatives exist at each point in the domain. This is important because machine learning is basically the chain rule with extra steps. One of the coolest flavors of neural rendering is novel view synthesis, where a neural network learns to render a scene from an arbitrary viewpoint. Neural rendering has huge potential in improving many aspects of the rendering pipeline by leveraging generative machine learning techniques. Some of the applications of neural rendering include rendering scenes for games and films, creating photorealistic 3D avatars, and transferring objects to digital maps. Neural rendering is still a very young field, but it has grown to encompass a large number of techniques, and it has the potential to revolutionize the way we render virtual worlds.