A system for generating complex physically accurate sensor images for automotive applications
Not on the map. Why?
Abstract (arXiv)
We describe an open-source simulator that creates sensor irradiance and sensor images of typical automotive scenes in urban settings. The purpose of the system is to support camera design and testing for automotive applications. The user can specify scene parameters (e.g., scene type, road type, traffic density, time of day) to assemble a large number of random scenes from graphics assets stored in a database. The sensor irradiance is generated using quantitative computer graphics methods, and the sensor images are created using image systems sensor simulation. The synthetic sensor images have pixel level annotations; hence, they can be used to train and evaluate neural networks for imaging tasks, such as object detection and classification. The end-to-end simulation system supports quantitative assessment, from scene to camera to network accuracy, for automotive applications.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 12 Feb 2019.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 3; 2025: 1.
5 papers.
- 2024SynFog: A Photo-realistic Synthetic Fog Dataset based on End-to-end Imaging Simulation for Advancing Real-World Defogging in Autonomous Drivingcited by 9
- 2021ISETAuto: Detecting vehicles with depth and radiance informationcited by 3
- 2024TaCOS: Task-Specific Camera Optimization with Simulationcited by 2
- 2024Data-driven Camera and Lidar Simulation Models for Autonomous Driving: A Review from Generative Models to Volume Rendererscited by 0
- 2025JOCA: Task-Driven Joint Optimisation of Camera Hardware and Adaptive Camera Control Algorithmscited by 0
- 2025JOCA: Task-Driven Joint Optimisation of Camera Hardware and Adaptive Camera Control Algorithms7 Dec 2025
- 2024TaCOS: Task-Specific Camera Optimization with Simulation17 Apr 2024
- 2024SynFog: A Photo-realistic Synthetic Fog Dataset based on End-to-end Imaging Simulation for Advancing Real-World Defogging in Autonomous Driving25 Mar 2024
- 2024Data-driven Camera and Lidar Simulation Models for Autonomous Driving: A Review from Generative Models to Volume Renderers29 Jan 2024
- 2021ISETAuto: Detecting vehicles with depth and radiance information6 Jan 2021