Crossmodal Transformer Based Generative Framework for Pedestrian Trajectory Prediction
Zhaoxin Su,Gang Huang,Sanyuan Zhang,Wei Hua,Zhaoxin Su,Gang Huang,Sanyuan Zhang,Wei Hua
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 leverage sequences of cues from multiple modalities as well as pedestrian attributes. For the encoder, ...
