Noise-Suppressing Deep Tracking

In visual tracking, it is challenging to distinguish the target from similar objects called noises in the background. As deep trackers use convolutional neural networks for image classification as feature extractors, the extracted features are insensitive to different instances in the same class, which is prone to make prediction models confuse the target and the similar noises in the background. ...