2025
Imagine-2-Drive: Leveraging High-Fidelity World Models via Multi-Modal Diffusion Policies
IROS 2025
World Model-based Reinforcement Learning (WMRL) enables sample efficient policy learning by reducing the need for online interactions which can potentially be costly and unsafe, especially for autonomous driving. However, existing world models often suffer from low prediction fidelity and compoundin