Deep Shading: Convolutional Neural Networks for Screen-Space Shading

In computer vision, Convolutional Neural Networks (CNNs) have recently achieved new levels of performance for several inverse problems where RGB pixel appearance is mapped to attributes such as positions, normals or reflectance. In computer graphics, screen-space shading has recently increased the visual quality in interactive image synthesis, where per-pixel attributes such as positions, normals or reflectance of a virtual 3D scene are converted into RGB pixel appearance, enabling effects like ambient occlusion, indirect light, scattering, depth-of-field, motion blur, or anti-aliasing. In this paper we consider the diagonal problem: synthesizing appearance from given per-pixel attributes using a CNN. The resulting Deep Shading simulates all screen-space effects as well as arbitrary combinations thereof at competitive quality and speed while not being programmed by human experts but learned from example images

Perceptually-motivated, interactive rendering and editing of global illumination

This thesis proposes several new perceptually-motivated techniques to synthesize, edit and enhance depiction of three-dimensional virtual scenes. Finding algorithms that fit the perceptually economic middle ground between artistic depiction and full physical simulation is the challenge taken in this work. First, we will present three interactive global illumination rendering approaches that are inspired by perception to efficiently depict important light transport. Those methods have in common to compute global illumination in large and fully dynamic scenes allowing for light, geometry, and material changes at interactive or real-time rates. Further, this thesis proposes a tool to edit reflections, that allows to bend physical laws to match artistic goals by exploiting perception. Finally, this work contributes a post-processing operator that depicts high contrast scenes in the same way as artists do, by simulating it "seen'; through a dynamic virtual human eye in real-time.Diese Arbeit stellt eine Anzahl von Algorithmen zur Synthese, Bearbeitung und verbesserten Darstellung von virtuellen drei-dimensionalen Szenen vor. Die Herausforderung liegt dabei in der Suche nach Ausgewogenheit zwischen korrekter physikalischer Berechnung und der künstlerischen, durch die Gesetze der menschlichen Wahrnehmung motivierten Praxis. Zunächst werden drei Verfahren zur Bild-Synthese mit globaler Beleuchtung vorgestellt, deren Gemeinsamkeit in der effizienten Handhabung großer und dynamischer virtueller Szenen liegt, in denen sich Geometrie, Materialen und Licht frei verändern lassen. Darauffolgend wird ein Werkzeug zum Editieren von Reflektionen in virtuellen Szenen das die menschliche Wahrnehmung ausnutzt um künstlerische Vorgaben umzusetzen, vorgestellt. Die Arbeit schließt mit einem Filter am Ende der Verarbeitungskette, der den wahrgenommen Kontrast in einem Bild erhöht, indem er die Entstehung von Glanzeffekten im menschlichen Auge nachbildet