AVGCN: Trajectory Prediction using Graph Convolutional Networks Guided by Human Attention
Congcong Liu,Yuying Chen,Ming Liu,Bertram E. Shi,Congcong Liu,Yuying Chen,Ming Liu,Bertram E. Shi
Pedestrian trajectory prediction is a critical yet challenging task especially for crowded scenes. We suggest that introducing an attention mechanism to infer the importance of different neighbors is critical for accurate trajectory prediction in scenes with varying crowd size. In this work, we propose a novel method, AVGCN, for trajectory prediction utilizing graph convolutional networks (GCN) ba...
