Energy-guided diffusion for socially plausible multiagent trajectory prediction
An energy-guided diffusion framework that injects interpretable constraints directly into the denoising process at inference time is proposed that shows consistent improvements in best-of-K accuracy (minADE/minFDE) and a substantial reduction in collision rate.