Once for All: A Two-Flow Convolutional Neural Network for Visual Tracking

Volume: 28, Issue: 12, Pages: 3377 - 3386
Published: Dec 1, 2018
Abstract
The main challenges of visual object tracking arise from the arbitrary appearance of the objects that need to be tracked. Most existing algorithms try to solve this problem by training a new model to regenerate or classify each tracked object. As a result, the model needs to be initialized and retrained for each new object. In this paper, we propose to track different objects in an object-independent approach with a novel two-flow convolutional...
Paper Details
Title
Once for All: A Two-Flow Convolutional Neural Network for Visual Tracking
Published Date
Dec 1, 2018
Volume
28
Issue
12
Pages
3377 - 3386
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