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Machine Learning Summit: Differentiable Rendering for Scalable Asset Pipeline in 'Honor of Kings'
In this session, Fei Ling and Frei Zhang will tackle the challenging problem of LOD assets generation for mobile games which run on devices with a wide variety of computational capabilitiesarguing that directly minimizing image space rendering loss is crucial to LOD asset quality. This presentation will introduce a novel and unified way of game assets fitting and generation, the whole pipeline is built on top of an in-house Hybrid Differentiable Renderer called Mythal which combines both rasterization and ray-tracing, taking the advantage of their respective strengthsspeed and realism. Armed with Mythal, they can calculate the image loss between reference rendering and LOD rendering, because the whole rendering pipeline is differentiable they can backpropagate the gradients for different rendering stages' attributes, and finally to interested game asset parameters, and then update these parameters with gradient-descent-based optimization methods. They will dive into several LOD generation applications which make their game Honor Of Kings (HOK) run efficiently on mobile devices with diverse hardware specifications, these applications include baked LOD of PBR shading, auto LOD skinning, auto mesh simplification, visibility baking, and more.
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