Spatio-Temporal Recurrent Networks for Event-Based Optical Flow Estimation

Understand

Event camera has offered promising alternative for visual perception, especially in high speed and high dynamic range scenes.

• Recently, many deep learning methods have shown great success in providing promising solutions to many event-based problems, such as optical flow estimation.
• However, existing deep learning methods did not address the importance of temporal information well from the perspective of architecture design and cannot effectively extract spatio-temporal features.
• Another line of research that utilizes Spiking Neural Network suffers from training issues for deeper architecture.To address these points, a novel input representation is proposed that captures the events' temporal distribution for signal enhancement.