11 DAILY CVPR Thursday traffic scene and modify that data into safety-critical scenarios or something we’re more interested in,” Carl reveals. Additionally, Adam points out the method’s usefulness in simulating different sensor setups: “Our company is an AD company, so we care about this real-world application. Maybe we want to try different sensors or lidars. Our method can simulate how that lidar would look on our old collected data. We can virtually try out different sensor configurations and see what works best for us.” NeuRAD can be applied to multiple datasets out of the box and has demonstrated state-of-the-art performance on five popular AD datasets. The team has made it open source and released it on GitHub. They would welcome people to contribute, expand the work with more features, and improve the NeRF renderings of automotive data in general. To learn more about the team’s work, visit Poster Session 4 & Exhibit Hall (Arch 4A-E) from 17:15 to 18:45 [Poster 28]. NEURAD “We focus on trying to capture the full sensor setup commonly used in AD!”
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