CREST: Convolutional Residual Learning for Visual Tracking

Understand

Discriminative correlation filters (DCFs) have been shown to perform superiorly in visual tracking.

• They only need a small set of training samples from the initial frame to generate an appearance model.
• However, existing DCFs learn the filters separately from feature extraction, and update these filters using a moving average operation with an empirical weight.
• These DCF trackers hardly benefit from the end-to-end training.