🙌 DiffusionAD is a research team focused on fully harnessing the power of diffusion models for autonomous driving systems. Our research interests lie in:
- Diffusion model with efficient and effective architecture design for autonomous driving systems
- Diffusion-based IL/RL algorithms for generalizable and robust autonomous driving systems
- Diffusion-based autonomous driving systems (Perception-Planning / End-to-End / VLA)
Projects:
- Flow-Planner (NeurIPS 2025): Flow Matching-Based Autonomous Driving Planning with Advanced Interactive Behavior Modeling
- BREEZE (NeurIPS 2025): Towards Robust Zero-Shot Reinforcement Learning
- Diffusion-Planner (ICLR 2025 Oral): Diffusion-Based Planning for Autonomous Driving with Flexible Guidance
- FISOR (ICLR 2024): Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model
