Many real-life materials have sparkling appearances. Some small flakes on the surface of an object can make a considerable contribution by reflecting or refracting light at a particular angle, eventually causing a sparkling appearance. Most existing approaches have focused on the glinty effects on reflective surfaces. However, transparent glint rendering has not been well studied, even though there are many natural phenomena (e.g., frost) in the real world. Recent studies have proposed the simulation of transparent glints under specific constraints (e.g., limited to the Beckmann distribution and V-groove shadowing-masking function). In this study, we propose a more general transparent glint model by performing a four-dimensional hierarchical search to count the particles located in the pixel footprint and cone around the refracted ray. Our method can produce transparent glint appearances for arbitrary normal distribution functions (e.g., GGX or Beckmann) and converge to a smooth microfacet model with a large particle count.

Monte Carlo based methods such as path tracing are widely used in movie production. To achieve low noise, they require many samples per pixel, resulting in long rendering time. To reduce the cost, one solution is Monte Carlo denoising, which renders the image with fewer samples per pixel (as little as 128) and then denoises the resulting image. Many Monte Carlo denoising methods rely on deep learning: they use convolutional neural networks to learn the relationship between noisy images and reference images, using auxiliary features such as position and normal together with image color as inputs. The network predicts kernels which are then applied to the noisy input. These methods show powerful denoising ability, but tend to lose geometric or lighting details and to blur sharp features during denoising.

Rendering translucent materials is costly: light transport algorithms need to simulate a large number of scattering events inside the material before reaching convergence. The cost is especially high for materials with a large albedo or a small mean-free-path, where higher-order scattering effects dominate. In simple terms, the paths get lost in the medium. Path guiding has been proposed for surface rendering to make convergence faster by guiding the sampling process. In this paper, we introduce a path guiding solution for translucent materials. We learn an adaptive approximate representation of the radiance distribution in the volume and use it to sample the scattering direction, combining it with phase function sampling by resampled importance sampling. The proposed method significantly improves the performance of light transport simulation in participating media, especially for small lights and media with refractive boundaries. Our method can handle any homogeneous participating medium, with high or low scattering, with high or low absorption, and from isotropic to highly anisotropic.