Tensorial Radiance Field

Tensorial Radiance Fields (TRFs) represent a scene as a multi-dimensional tensor, offering a more efficient and compact alternative to traditional neural radiance fields (NeRFs) for 3D scene reconstruction and novel view synthesis. Current research focuses on improving TRF architectures, such as employing tensor decompositions (e.g., CP and VM decompositions) to reduce computational cost and memory footprint while enhancing rendering quality, particularly for handling complex effects like specular highlights and dynamic scenes. This approach shows promise for accelerating training and inference speeds, making high-fidelity 3D scene modeling more accessible for applications ranging from satellite imagery processing to facial reconstruction and large-scale scene generation.