We present a complete system for real-time rendering of scenes with complex appearance previously reserved for offline use. This is achieved with a combination of algorithmic and system level innovations. Our appearance model utilizes learned hierarchical textures that are interpreted using neural decoders, which produce reflectance values and importance-sampled directions. To best utilize the modeling capacity of the decoders, we equip the decoders with two graphics priors. The first prior—transformation of directions into learned shading frames—facilitates accurate reconstruction of mesoscale effects. The second prior—a microfacet sampling distribution—allows the neural decoder to perform importance sampling efficiently. The resulting appearance model supports anisotropic sampling and level-of-detail rendering, and allows baking deeply layered material graphs into a compact unified neural representation. By exposing hardware accelerated tensor operations to ray tracing shaders, we show that it is possible to inline and execute the neural decoders efficiently inside a real-time path tracer. We analyze scalability with increasing number of neural materials and propose to improve performance using code optimized for coherent and divergent execution. Our neural material shaders can be over an order of magnitude faster than non-neural layered materials. This opens up the door for using film-quality visuals in real-time applications such as games and live previews.

The Manuka rendering architecture has been designed in the spirit of the classic reyes rendering architecture: to enable the creation of visually rich computer generated imagery for visual effects in movie production. Following in the footsteps of reyes over the past 30 years, this means supporting extremely complex geometry, texturing, and shading. In the current generation of renderers, it is essential to support very accurate global illumination as a means to naturally tie together different assets in a picture. This is commonly achieved with Monte Carlo path tracing, using a paradigm often called shade on hit , in which the renderer alternates tracing rays with running shaders on the various ray hits. The shaders take the role of generating the inputs of the local material structure, which is then used by path-sampling logic to evaluate contributions and to inform what further rays to cast through the scene. We propose a shade before hit paradigm instead and minimise I/O strain on the system, leveraging locality of reference by running pattern generation shaders before we execute light transport simulation by path sampling. We describe a full architecture built around this approach, featuring spectral light transport and a flexible implementation of multiple importance sampling ( mis ), resulting in a system able to support a comparable amount of extensibility to what made the reyes rendering architecture successful over many decades.

Graphics Processing Units (GPUs) recently became general enough to enable implementation of a variety of light transport algorithms. However, the efficiency of these GPU implementations has received relatively little attention in the research literature and no systematic study on the topic exists to date. The goal of our work is to fill this gap. Our main contribution is a comprehensive and in-depth investigation of the efficiency of the GPU implementation of a number of classic as well as more recent progressive light transport simulation algorithms. We present several improvements over the state-of-the-art. In particular, our light vertex cache, a new approach to mapping connections of subpath vertices in bidirectional path tracing on the GPU, outperforms the existing implementations by 30--60%. We also describe a first GPU implementation of the recently introduced vertex connection and merging algorithm [Georgiev et al. 2012], showing that even relatively complex light transport algorithms can be efficiently mapped on the GPU. With the implementation of many of the state-of-the-art algorithms within a single system at our disposal, we present a unique direct comparison and analysis of their relative performance.

Developing robust light transport simulation algorithms that are capable of dealing with arbitrary input scenes remains an elusive challenge. Although efficient global illumination algorithms exist, an acceptable approximation error in a reasonable amount of time is usually only achieved for specific types of input scenes. To address this problem, we present a reformulation of photon mapping as a bidirectional path sampling technique for Monte Carlo light transport simulation. The benefit of our new formulation is twofold. First, it makes it possible, for the first time, to explain in a formal manner the relative efficiency of photon mapping and bidirectional path tracing, which have so far been considered conceptually incompatible solutions to the light transport problem. Second, it allows for a seamless integration of the two methods into a more robust combined rendering algorithm via multiple importance sampling. A progressive version of this algorithm is consistent and efficiently handles a wide variety of lighting conditions, ranging from direct illumination, diffuse and glossy inter-reflections, to specular-diffuse-specular light transport. Our analysis shows that this algorithm inherits the high asymptotic performance from bidirectional path tracing for most light path types, while benefiting from the efficiency of photon mapping for specular-diffuse-specular lighting effects.

Accurately rendering glossy materials in design applications, where previewing and interactivity are important, remains a major challenge. While many fast global illumination solutions have been proposed, all of them work under limiting assumptions on the materials and lighting in the scene. In the presence of many glossy (directionally scattering) materials, fast solutions either fail or degenerate to inefficient, brute-force simulations of the underlying light transport. In particular, many-light algorithms are able to provide fast approximations by clamping elements of the light transport matrix, but they eliminate the part of the transport that contributes to accurate glossy appearance. In this paper we introduce a solution that separately solves for the global (low-rank, dense) and local (highrank, sparse) illumination components. For the low-rank component we introduce visibility clustering and approximation, while for the high-rank component we introduce a local light technique to correct for the missing illumination. Compared to competing techniques we achieve superior gloss rendering in minutes, making our technique suitable for applications such as industrial design and architecture, where material appearance is critical.