4 papers · 1 filter
Ctrl-Crash: Controllable Diffusion for Realistic Car Crashes
Anthony Gosselin, Ge Ya Luo, Luis Lara +5
Video diffusion techniques have advanced significantly in recent years; however, they struggle to generate realistic imagery of car crashes due to the scarcity of accident events i…
Neural Coherence : Find higher performance to out-of-distribution tasks from few samples
Simon Guiroy, Mats Richter, Sarath Chandar +1
To create state-of-the-art models for many downstream tasks, it has become common practice to fine-tune a pre-trained large vision model. However, it remains an open question of ho…
Poutine: Vision-Language-Trajectory Pre-Training and Reinforcement Learning Post-Training Enable Robust End-to-End Autonomous Driving
Luke Rowe, Rodrigue de Schaetzen, Roger Girgis +2
Maintaining good driving behavior in out-of-distribution scenarios remains a critical challenge in autonomous driving. A promising direction is to leverage the generalist knowledge…
Scenario Dreamer: Vectorized Latent Diffusion for Generating Driving Simulation Environments
Luke Rowe, Roger Girgis, Anthony Gosselin +3
We introduce Scenario Dreamer, a fully data-driven generative simulator for autonomous vehicle planning that generates both the initial traffic scene - comprising a lane graph and…