Graphics Programming weekly - Issue 250 - August 28, 2022

Barycentric Quad Rasterization

  • presents why and when a quad is being drawn as two triangles can cause discontinuities along the edge
  • the paper presents a geometry shader implementation of generalized barycentric coordinates for quads
  • this concept was introduced in 2004 for CPU rasterization when hardware support was not available

Practical Real-Time Hex-Tiling

  • the paper introduces an adaptation of the Heitz and Neyret texture tiling technique
  • the original technique required offline preprocessing to enable histogram-preserving tiling
  • the new method removes the requirement and presents the implementation in shader code only
  • presents how to apply the technique for color and normal maps

Clip control on the Apple GPU

  • the blog post provides an insight into how the apple metal driver is separated into components
  • shows how it’s possible to call internal APIs and reconstruct hardware behavior
  • presents a discussion of OpenGL clip space mapping and limitations of different emulation behaviors

[video] Creating an Outline Effect as a Post-Process in Unity

  • the video tutorial explains how to implement an outline effect in Unity
  • presents how to detect edges using the depth buffer, create an outline at the edges
  • it additionally shows how to adjust the effect so that objects behind objects get a separate show-through-wall effect

HPG 2022 Keynote: The Journey to Nanite - Brian Karis, Epic Games

  • the talk discusses the issues artist encounter and how Nanite goals are designed to resolve them
  • presents a large number of topics Brian Karis had researched along the way
  • shows a brief overview of the techniques, shortcomings, and reasons why they failed
  • discusses how to structure long-term research, focusing on challenges of the field and the importance of coding like a scientist

CoG 2022: Automatic Testing and Validation of LoD Reductions Through Supervised Learning

  • the paper introduces two convolutional neural networks (CNN) based techniques that can detect LOD transitions and the quality of that transition
  • two models are presented to solve these two issues separately
  • discusses the issue with the current approaches and how the presented techniques could be used to support artists

Thanks to Daniel Fortes for support of this series.

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