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In computer graphics, we rarely encounter continuous data. We often work with digital data, and in the context of geometric modeling, this means we typically work with polygon meshes rather than procedural surfaces like Bézier patches. The most popular technique for constructing digital three-dimensional objects in dedicated modeling software is polygon modeling. The result of the creation phase is a set of polygons (mesh), where the polygons in the mesh can share vertices and edges with other polygons.

Creating realistic images has been a persistently challenging problem in computer graphics, especially when it comes to rendering scenes with complex lighting. Path tracing achieves photorealistic quality rendering by simulating the way light rays bounce around the scene and interact with different materials, but it also requires significant computation to generate clean images. This is where neural supersampling and denoising come into play. In this blog post, we describe how our neural supersampling and denoising work together to push the boundary for real-time path tracing.

AMD’s ISAs are all stored here on gpuopen.com.