Boosting Visual Fidelity in Driving Simulations through Diffusion Models

TL;DR

This paper introduces DRIVE, a diffusion model-based system that significantly enhances visual realism in driving simulations, supported by user studies and practical guidelines for future integration.

Contribution

The paper presents a novel diffusion model pipeline, DRIVE, specifically designed to improve visual fidelity in driving simulations, marking a new application of diffusion models in virtual environments.

Findings

DRIVE produces more photorealistic visuals in driving simulations.

User study shows improved realism and task performance.

Provides practical guidelines for diffusion model integration.

Abstract

Diffusion models have made substantial progress in facilitating image generation and editing. As the technology matures, we see its potential in the context of driving simulations to enhance the simulated experience. In this paper, we explore this potential through the introduction of a novel system designed to boost visual fidelity. Our system, DRIVE (Diffusion-based Realism Improvement for Virtual Environments), leverages a diffusion model pipeline to give a simulated environment a photorealistic view, with the flexibility to be adapted for other applications. We conducted a preliminary user study to assess the system's effectiveness in rendering realistic visuals and supporting participants in performing driving tasks. Our work not only lays the groundwork for future research on the integration of diffusion models in driving simulations but also provides practical guidelines and best practices for their application in this context.