class-incremental

New Framework for Class-Incremental Motion Forecasting Enables Autonomous Vehicles to Adapt to Novel Objects

Researchers introduce class-incremental motion forecasting, a setting where autonomous vehicles learn new object classes over time. They propose the first end-to-end framework that adapts to novel classes while mitigating catastrophic forgetting, using pseudo-labels and open-vocabulary segmentation. Evaluations on nuScenes and Argoverse 2 show preserved performance on known classes and effective adaptation to new ones.