Hyeoncheol Noh

A Self-Supervised Sampler for Efficient Action Recognition: Real-World Applications in Surveillance Systems

The common paradigm of CNN-based action recognition modelsis to simply use the average of the dense predictions from every frame. However, these dense predictions are inefficient since all frames are evenly utilized regardless of the existence of the action. In real-time action recognition applicati