Learning 3D-aware Egocentric Spatial-Temporal Interaction via Graph Convolutional Networks
Chengxi Li,Yue Meng,Stanley H. Chan,Yi-Ting Chen,Chengxi Li,Yue Meng,Stanley H. Chan,Yi-Ting Chen
To enable intelligent automated driving systems, a promising strategy is to understand how human drives and interacts with road users in complicated driving situations. In this paper, we propose a 3D-aware egocentric spatial-temporal interaction framework for automated driving applications. Graph convolution networks (GCN) is devised for interaction modeling. We introduce three novel concepts into...
