2 posts tagged with "gaussian-splatting"

Simulators are great for autonomous driving testing because they're safe, reproducible, and fully controllable — but their rendered worlds usually look nothing like the real world. A perception or end-to-end driving model that performs well in simulation can behave very differently once it sees real camera data. This is the classic sim-to-real gap, and it's the problem a recent paper called Cam2Sim: Neural Scenario Reconstruction for Closed-Loop Autonomous Driving Simulation sets out to close.

If you've spent any time in CARLA, you know its strength and its limit at the same time: it's a fantastic, fully controllable simulator, but its Unreal Engine art assets look like a simulator. Buildings, road textures, foliage — it's all clearly synthetic. For a lot of autonomous driving development, that's fine. But when you're trying to close the sim-to-real gap, that visual gap matters.