Fourier Feature Networks and Neural Volume Rendering

Fourier Feature Networks are an exciting new development in Computer Vision, and their use for modeling radiance fields has produced a range of impressive results at the meeting point of Computer Vision and Computer Graphics. In this lecture I cover the motivation behind using Fourier features in neural network training, introduce the fundamentals of volumetric ray casting, and then show how we can use Fourier Feature Networks to render high-quality novel views of complex 3D scenes. This video was created for my guest lecture as part of University of Cambridge Engineering Tripos Part IIB, 4F12: Computer Vision. In addition to the lecture, you can access code and a Jupyter notebook for use in further learning at the companion Github repository: https://github.com/matajoh/fourier_fe...