We create a metrically accurate hair representation using neural rendering primitives and optical flow.
We create virtual objects that visually and physically resemble their real counterparts.
We propose a novel approach for 3D video synthesis that is able to represent multi-view video recordings of a dynamic real-world scene in a compact, yet expressive representation that enables high-quality view synthesis and motion interpolation.
We propose a novel approach for learning a representation of the geometry, appearance, and motion of a class of articulated objects given only a set of color images as input.