Object Dynamic

Object dynamics research focuses on modeling and predicting the movement and interaction of objects, particularly in complex, multi-object scenarios. Current efforts concentrate on developing robust and efficient models, often employing graph neural networks, transformers, and neural radiance fields, to handle diverse object types, interactions (including contact and friction), and varying levels of occlusion. These advancements are crucial for improving applications in robotics, autonomous driving, virtual and augmented reality, and scientific simulation by enabling more realistic and accurate predictions of object behavior in dynamic environments.