End-to-end Conditional Diffusion for Realistic and Controllable Visual Traffic Scenario Generation
Generating closed-loop traffic scenarios that are both realistic and controllable is crucial for evaluating autonomous driving systems, especially under rare safety-critical interactions. Existing learning-based methods often struggle to balance controllability and realism, offering either limited fine-grained control...