3 accepted papers
Predicting pedestrian trajectories is crucial for human-interactive systems. This task is compounded by the inherently multimodal nature of human motions and complex external and internal factors such as social interactions and intentions. In this letter, we propose a dynamic attention-based CVAE-GA
Providing guidance about collision avoidance, pedestrian trajectory prediction is an important task for autonomous driving. In this paper, to produce plausible trajectory predictions in the first-person view circumstance, we propose a crossmodal transformer based generative framework which could lev…
Pedestrian trajectory prediction is a challenge because of the complex social interactions in context and the elusive intention of each pedestrian. Collision avoidance is one of the most common social interactions in real world, while existing data-driven works have not handled it well yet. In order…