Multi-Person Human Motion Forecasting in Complex Scenes
Object-Conditioned Social Diffusion is proposed, a conditional diffusion model that integrates motion history, multi-person interactions, and object cues into a single framework that reduces the two-second path error, produces more realistic long-term forecasts, and supports sampling multiple plausible futures.