# Foveated Rendering: a State-of-the-Art Survey

arXiv: https://arxiv.org/abs/2211.07969 · HTML: https://mlsanity.com/paper/2211.07969/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Nov 2022.

## Built on by (most cited first, 7 of 7)

- [VR-Splatting: Foveated Radiance Field Rendering via 3D Gaussian Splatting and Neural Points](https://mlsanity.com/paper/2410.17932/) (2024)
- [GS-Cache: A GS-Cache Inference Framework for Large-scale Gaussian Splatting Models](https://mlsanity.com/paper/2502.14938/) (2025)
- [Human Scanpath Prediction in Target-Present Visual Search with Semantic-Foveal Bayesian Attention](https://mlsanity.com/paper/2507.18503/) (2025)
- [Matryoshka Gaussian Splatting](https://mlsanity.com/paper/2603.19234/) (2026)
- [Policy-based Foveated Imaging and Perception](https://mlsanity.com/paper/2606.02565/) (2026)
- [ObjectVisA-120: Object-based Visual Attention Prediction in Interactive Street-crossing Environments](https://mlsanity.com/paper/2601.13218/) (2026)
- [Understanding and Exploiting Diagonal Attention Sparsity in Autoregressive Image Generation](https://mlsanity.com/paper/2609.19702/) (2026)

## Abstract (arXiv)

Recently, virtual reality (VR) technology has been widely used in medical, military, manufacturing, entertainment, and other fields. These applications must simulate different complex material surfaces, various dynamic objects, and complex physical phenomena, increasing the complexity of VR scenes. Current computing devices cannot efficiently render these complex scenes in real time, and delayed rendering makes the content observed by the user inconsistent with the user's interaction, causing discomfort. Foveated rendering is a promising technique that can accelerate rendering. It takes advantage of human eyes' inherent features and renders different regions with different qualities without sacrificing perceived visual quality. Foveated rendering research has a history of 31 years and is mainly focused on solving the following three problems. The first is to apply perceptual models of the human visual system into foveated rendering. The second is to render the image with different qualities according to foveation principles. The third is to integrate foveated rendering into existing rendering paradigms to improve rendering performance. In this survey, we review foveated rendering research from 1990 to 2021. We first revisit the visual perceptual models related to foveated rendering. Subsequently, we propose a new foveated rendering taxonomy and then classify and review the research on this basis. Finally, we discuss potential opportunities and open questions in the foveated rendering field. We anticipate that this survey will provide new researchers with a high-level overview of the state of the art in this field, furnish experts with up-to-date information and offer ideas alongside a framework to VR display software and hardware designers and engineers.