Learning Objectness Transfer Networks for Visual Tracking
Abstract
Existing deep trackers mainly use deep neural networks pre-trained on the object recognition training sets to generate deep features as target representation. However, pre-trained deep features are not effective in representing arbitrary forms of target objects which are likely to be unseen for the pre-trained deep networks. To narrow the gap of representation capability, we propose to transfer the objectness information within pre-trained deep...
Paper Details
Title
Learning Objectness Transfer Networks for Visual Tracking
Published Date
Jan 1, 2019
Journal
Volume
7
Pages
148706 - 148717
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