Humans exhibit a remarkable capacity for anticipating the actions of others and planning
their own actions accordingly. In this study, we strive to replicate this ability by addressing …

Abstract We propose Social Diffusion, a novel method for short-term and long-term
forecasting of the motion of multiple persons as well as their social interactions. Jointly …

We propose a novel framework for multi-person 3D motion trajectory prediction. Our key
observation is that a human's action and behaviors may highly depend on the other persons …

Motion prediction is essential and challenging for autonomous vehicles and social robots.
One challenge of motion prediction is to model the interaction among traffic actors, which …

Human motion prediction is crucial for the human–robot inter-action and self-driving. We
human beings learn an action with two stages, ie, the approximation stage and the …

This paper aims to deal with the ignored real-world complexities in prior work on human
motion forecasting, emphasizing the social properties of multi-person motion, the diversity of …

In this paper, we tackle the task of scene-aware 3D human motion forecasting, which
consists of predicting future human poses given a 3D scene and a past human motion. A key …

Pedestrian trajectory prediction is a challenging task because of the complexity of real-world
human social behaviors and uncertainty of the future motion. For the first issue, existing …

Smooth and seamless robot navigation while interacting with humans depends on
predicting human movements. Forecasting such human dynamics often involves modeling …

In most classical Autonomous Vehicle (AV) stacks, the prediction and planning layers are
separated, limiting the planner to react to predictions that are not informed by the planned …