Product lighting design is a laborious and time-consuming task. With product illustrations being increasingly rendered, the lighting challenge transferred to the virtual realm. Our approach targets lighting design in the context of a scene with fixed objects, materials, and camera parameters, illuminated by environmental lighting. Our solution offers control over the depiction of material characteristics and shape details by optimizing the illuminating environment-map. To that end, we introduce a metric that assesses the shape and material cues in terms of the designed appearance. We formalize the process and support steering the outcome using additional design constraints. We illustrate our solution with several challenging examples.

Video-streaming services usually feature post-processing effects to replace the background. However, these often yield inconsistent lighting. Machine-learning-based relighting methods can address this problem, but, at real-time rates, are restricted to a low resolution and can result in an unrealistic skin appearance. Physically-based rendering techniques require complex skin models that can only be acquired using specialised equipment. Our method is lightweight and uses only a standard smartphone. By correcting imperfections during capture, we extract a convincing physically-based skin model. In combination with suitable acceleration techniques, we achieve real-time rates on commodity hardware.

Shadow volumes are a popular technique to compute pixel-accurate hard shadows in 3D scenes. Many variants exist that trade off accuracy and efficiency. In this work, we present an artifact-free, efficient, and easy-to-implement stencil shadow volume method. We compare our method to established stencil shadow volume techniques and show that it outperforms the alternatives.