Learning Policies for Adaptive Tracking with Deep Feature Cascades

@article{Huang2017LearningPF,
  title={Learning Policies for Adaptive Tracking with Deep Feature Cascades},
  author={Chen Huang and Simon Lucey and Deva Ramanan},
  journal={2017 IEEE International Conference on Computer Vision (ICCV)},
  year={2017},
  pages={105-114}
}
Visual object tracking is a fundamental and time-critical vision task. Recent years have seen many shallow tracking methods based on real-time pixel-based correlation filters, as well as deep methods that have top performance but need a high-end GPU. In this paper, we learn to improve the speed of deep trackers without losing accuracy. Our fundamental insight is to take an adaptive approach, where easy frames are processed with cheap features (such as pixel values), while challenging frames are… 

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    2021 7th International Conference on Control, Automation and Robotics (ICCAR)
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