Tag
SPARC introduces a Bayesian–conformal uncertainty layer for motion forecasting, achieving first rank in NLL and combined criteria with efficient, calibrated uncertainty estimates.
INTraJ is a unified framework for trajectory prediction that decomposes social influence into two stages: planning with future social information and local reaction from residuals, achieving state-of-the-art results on Argoverse 2, ETH/UCY, and SDD benchmarks.
MolmoMotion is a new language-guided 3D motion forecasting model that predicts future 3D point trajectories from video frames and action descriptions, achieving stronger performance than existing methods. Alongside the model, a large dataset (MolmoMotion-1M) and a benchmark (PointMotionBench) are released.