TEINet: Towards an Efficient Architecture for Video Recognition

Understand

Efficiency is an important issue in designing video architectures for action recognition.

• 3D CNNs have witnessed remarkable progress in action recognition from videos.
• However, compared with their 2D counterparts, 3D convolutions often introduce a large amount of parameters and cause high computational cost.
• To relieve this problem, we propose an efficient temporal module, termed as Temporal Enhancement-and-Interaction (TEI Module), which could be plugged into the existing 2D CNNs (denoted by TEINet).