Adaptive feature fusion for visual object tracking

•We propose an adaptive feature fusion mechanism to provide both semantic and discriminative feature representations by automatically fusing multi-level convolutional layers.•We reformulate the update strategy. Through joint training the projection matrix layer and correlation layer, a more convincing target localization formulation can be achieved.•We validate our method on several benchmarking datasets with state-of-the-art methods. The experimental results and corresponding analysis demonstrate the merit of the proposed tracker.