Efficient Specular Glints Rendering With Differentiable Regularization.

Rendering glinty details from specular microstructure enhances the level of realism in computer graphics. However, naive sampling fails to render such effects, due to insufficient sampling of the contributing normals on the surface patch visible through a pixel. Other approaches resort to searching for the relevant normals in more explicit ways, but they rely on special acceleration structures, leading to increased storage costs and complexity.

Foveated Photon Mapping.

Virtual reality (VR) applications require high-performance rendering algorithms to efficiently render 3D scenes on the VR head-mounted display, to provide users with an immersive and interactive virtual environment. Foveated rendering provides a solution to improve the performance of rendering algorithms by allocating computing resources to different regions based on the human visual acuity, and renders images of different qualities in different regions. Rasterization-based methods and ray tracing methods can be directly applied to foveated rendering, but rasterization-based methods are difficult to estimate global illumination (GI), and ray tracing methods are inefficient for rendering scenes that contain paths with low probability.

Realistic Rendering in "Details".

Rendering is far from solved. Even today, the rendered results still look artificial and overly perfect. To make rendering more realistic, we need details.

Lightweight Bilateral Convolutional Neural Networks for Interactive Single-Bounce Diffuse Indirect Illumination.

Physically correct, noise-free global illumination is crucial in physically-based rendering, but often takes a long time to compute. Recent approaches have exploited sparse sampling and filtering to accelerate this process but still cannot achieve interactive performance. It is partly due to the time-consuming ray sampling even at 1 sample per pixel, and partly because of the complexity of deep neural networks.