Argoverse Motion Forecasting

Argoverse motion forecasting focuses on accurately predicting the future trajectories of vehicles and other agents in complex traffic scenarios, using data from the Argoverse dataset. Current research emphasizes improving model efficiency and accuracy through techniques like coreset selection to handle large datasets, incorporating prediction difficulty into model design, and leveraging graph neural networks and attention mechanisms to better understand agent interactions and map information. These advancements are crucial for enhancing the safety and reliability of autonomous driving systems by providing more accurate predictions of surrounding vehicle behavior.