Rendering

We propose a practical way to precompute and compactly store ASOs and demonstrate their ability to accelerate path tracing.

We present a novel method for synchronizing action videos where a similar action is performed by different people at different times and different locations with different local speed changes, e.g., as in sports like weightlifting, baseball pitch, or dance.

We consider three foveated rendering methods and propose practical rules of thumb for each method to achieve significant performance gains in real-time rendering frameworks.

We propose a solution for presenting movie quality graphics to the user while still allowing the sense of presence afforded by free viewpoint head motion.

We propose a new adaptive rendering method to improve the performance of Monte Carlo ray tracing, by reducing noise contained in rendered images while preserving high-frequency edges.

We present subdivision next-event estimation (SNEE) for unbiased Monte Carlo simulation of subsurface scattering.

In this paper, we propose a method to interactively render these complex 3D paintings with a focus on character animation in video games.

We propose a new adaptive rendering algorithm that enhances the performance of Monte Carlo ray tracing by reducing the noise, i.e., variance while preserving a variety of high-frequency edges in rendered images through a novel prediction based reconstruction.

We address the problem of modeling and rendering granular materials—such as large structures made of sand, snow, or sugar— where an aggregate object is composed of many randomly oriented, but discernible grains.

We present a technique to efficiently importance sample distant, all-frequency illumination in indoor scenes.