T4P: Test-Time Training of Trajectory Prediction via Masked Autoencoder and Actor-specific Token Memory

arXiv:2403.10052v1 Announce Type: new
Abstract: Trajectory prediction is a challenging problem that requires considering interactions among multiple actors and the surrounding environment. While data-driven approaches have been used to address this complex problem, they suffer from unreliable predictions under distribution shifts during test time. Accordingly, several online learning methods have been proposed using regression loss from the ground truth of observed data leveraging the auto-labeling nature of trajectory prediction task. We mainly tackle the following two issues. First, previous works …

actor arxiv autoencoder cs.cv masked autoencoder memory prediction test token training trajectory type via