VGGTWorld-VLA: Intent-Conditioned 3D World Evolution for Autonomous Driving
Overview
VGGTWorld-VLA improves 3D world prediction by integrating driving intentions and actions, enabling controllable future geometry forecasts. Evaluated on NAVSIM with ablations examining semantic and action contributions.
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- arXiv Robotics — research abstractsVGGTWorld-VLA: Intent-Conditioned 3D World Evolution for Autonomous Driving
VGGTWorld-VLA improves 3D world prediction by integrating driving intentions and actions. It enables controllable future geometry forecasts through semantic and action conditioning. Results show competitive performance in autonomous driving scenarios.
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