Understanding Dynamic Scenes using Graph Convolution Networks
Sravan Mylavarapu,Mahtab Sandhu,Priyesh Vijayan,K Madhava Krishna,Balaraman Ravindran,Anoop Namboodiri,Sravan Mylavarapu,Mahtab Sandhu,Priyesh Vijayan,K Madhava Krishna,Balaraman Ravindran,Anoop Namboodiri
We present a novel Multi-Relational Graph Convolutional Network (MRGCN) based framework to model on-road vehicle behaviors from a sequence of temporally ordered frames as grabbed by a moving monocular camera. The input to MRGCN is a multi-relational graph where the graph's nodes represent the active and passive agents/objects in the scene, and the bidirectional edges that connect every pair of nod...
