Intra-Model Smoothing Using Depth Aware Multi-Sample Anti-Aliasing for Deferred Rendering Pipelines

Magnussen, Birk Martin

Intra-Model Smoothing Using Depth Aware Multi-Sample Anti-Aliasing for Deferred Rendering Pipelines

Date

2023

Authors

Magnussen, Birk Martin

Publisher

The Eurographics Association

Abstract

Subpixel geometry often causes lighting artifacts. In some cases, post-process anti-aliasing algorithms are not sufficiently able to smooth the resulting image. For forward rendering pipelines, multi-sample anti-aliasing is a powerful tool to avoid such artifacts. However, modern rendering pipelines commonly use deferred shading, which causes issues for multi-sample anti-aliasing. This article proposes a new method of combining a pipeline using deferred shading with multi-sample antialiasing while avoiding common pitfalls. The proposed method achieves this by intelligently resolving the geometry buffers with a custom shader based on the depth of samples. This allows the lighting shader to run unchanged on the geometry buffer on a per-fragment basis without additional performance costs. Furthermore, the proposed method is easy to retrofit to existing engines as no changes are required to either the model rendering shader or the deferred lighting shader. The proposed method is demonstrated and implemented on the example of the open-source game engine FreeSpace Open. It is shown that the proposed method is capable of preventing subpixel geometry artifacts, while also avoiding lighting artifacts from resolving geometry buffers and avoiding the performance overhead of calculating lighting per sample.

CCS Concepts: Computing methodologies -> Antialiasing; Rendering

        @inproceedings{10.2312:cgvc.20231198
,
booktitle = {Computer Graphics and Visual Computing (CGVC)
},
editor = {Vangorp, Peter and 
Hunter, David
},
title = {{Intra-Model Smoothing Using Depth Aware Multi-Sample Anti-Aliasing for Deferred Rendering Pipelines
}},
author = {Magnussen, Birk Martin
},
year = {2023
},
publisher = {The Eurographics Association
},
ISBN = {978-3-03868-231-8
},
DOI = {10.2312/cgvc.20231198
}
}