GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond

+ Re-interpretation and connection of two top popular techniques proposed in CVPR 2018 (Non-local neural networks and SE-Net). + Unification of these the two techniques into a general framework. + Better instantiation of the general framework, which is about 50x faster than the non-local neural block, while achieving better accuracy than both techniques (non-local and SE-Net) on several recognition tasks such as ImageNet classification, COCO object detection and Kinetics action recognition.