Light Field Network

Light field networks represent 3D scenes by learning a mapping from rays to colors, offering a compact and efficient alternative to traditional methods for novel view synthesis and 3D reconstruction. Current research focuses on improving robustness to noisy data and occlusions through techniques like outlier detection and developing architectures that handle dynamic scenes and varying levels of detail, often employing deep learning models with multi-view training strategies. These advancements are significant for applications requiring efficient and high-fidelity 3D scene representation, such as virtual and augmented reality, computer vision, and robotics.