Efficient Multi-Timescale Event Representations for Feed-Forward Object Detection

The researchers proposed a multi-time-scale event representation method aimed at addressing the issue of temporal information loss in traditional object detection when dealing with high-dynamic scenarios. By constructing feature representations at different time scales, this method enhances the model’s ability to capture the motion trajectories of objects. Experiments show that this technique significantly improves the detection accuracy and robustness of the feedforward architecture while maintaining computational efficiency in complex dynamic environments.