Relational Action Forecasting

Understand

This paper focuses on multi-person action forecasting in videos.

• More precisely, given a history of H previous frames, the goal is to detect actors and to predict their future actions for the next T frames.
• Our approach jointly models temporal and spatial interactions among different actors by constructing a recurrent graph, using actor proposals obtained with Faster R-CNN as nodes.
• Our method learns to select a subset of discriminative relations without requiring explicit supervision, thus enabling us to tackle challenging visual data.