Fast Global Illumination Approximations on Deep G-Buffers

Deep Geometry Buffers (G-buffers) combine the fine-scale and efficiency of screen-space data with much of the robustness of voxels. We introduce a new hardware-aware method for computing two-layer deep G-buffers and show how to produce dynamic indirect radiosity, ambient occlusion (AO), and mirror reflection from them in real-time. Our illumination computation approaches the performance of today’s screen-space AO-only rendering passes on current GPUs and far exceeds their quality. Our G-buffer generation method is order-independent, guarantees a minimum separation between layers, operates in a (small) bounded memory footprint, and avoids any sorting. Moreover, to address the increasingly expensive cost of pre-rasterization computations, our approach requires only a single pass over the scene geometry. We show how to apply Monte Carlo sampling and reconstruction to these to efficiently compute global illumination terms from the deep G-buffers.

The resulting illumination captures small-scale detail and dynamic illumination effects and is more substantially more robust than screen space estimates. It necessarily still view-dependent and lower-quality than offline rendering. However, it is real-time, temporally coherent, and plausible based on visible geometry. Furthermore, the lighting algorithms automatically identify undersampled areas to fill from broad-scale or precomputed illumination. All techniques described are both practical today for real-time rendering and designed to scale with near-future hardware architecture and content trends. We include pseudocode for deep G-buffer generation, and source code and a demo for the global illumination sampling and filtering.


Michael Mara (NVIDIA)
Morgan McGuire (NVIDIA)
Derek Nowrouzezahrai (University of Montreal)

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