VidGen-2 generates predictive video sequences with highly realistic appearances and dynamic scene modeling. Our generative AI video model enhances prediction tasks and generative simulation capabilities, enabling scalable and cost-efficient autonomous driving development and validation.
VidGen-2 produces highly realistic images of virtual driving environments, including variations in illumination, weather conditions, times of day, geography, road geometries, road markings, vehicles and pedestrians, all at a resolution of 696x696 and up to 30 fps.
Our generative AI video model produces diverse driving scenes, encompassing various geographies, vehicle types, pedestrians, cyclists, intersections, turns, weather conditions, lighting effects, and accurate reflections.
VidGen-2 supports multi-camera views, generating footage from three cameras at 640 x 384 (VGA) resolution for each. The model ensures self-consistency across all camera perspectives, providing accurate simulation for various sensor configurations.
The model reproduces realistic, human-like driving behaviors, generating motions for the ego-vehicle and surrounding agents in accordance with traffic rules.
VidGen-2 can be used to generate a wide variety of scenarios that would be too rare or dangerous to encounter in real world driving.
Beyond automotive applications, our model can be applied to various domains, including robotics and off-road autonomy.
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