End-to-end feature fusion siamese network for adaptive visual tracking

@article{Guo2019EndtoendFF,
  title={End-to-end feature fusion siamese network for adaptive visual tracking},
  author={Dongyan Guo and J. Wang and W. Zhao and Ying Cui and Zhenhua Wang and S. Chen},
  journal={ArXiv},
  year={2019},
  volume={abs/1902.01057}
}
According to observations, different visual objects have different salient features in different scenarios. Even for the same object, its salient shape and appearance features may change greatly from time to time in a long-term tracking task. Motivated by them, we proposed an end-to-end feature fusion framework based on Siamese network, named FF-Siam, which can effectively fuse different features for adaptive visual tracking. The framework consists of four layers. A feature extraction layer is… Expand

References

SHOWING 1-10 OF 42 REFERENCES
Convolutional Features for Correlation Filter Based Visual Tracking
  • 622
  • PDF
Once for All: A Two-Flow Convolutional Neural Network for Visual Tracking
  • Kai Chen, Wenbing Tao
  • Computer Science
  • IEEE Transactions on Circuits and Systems for Video Technology
  • 2018
  • 69
  • PDF
Hierarchical Convolutional Features for Visual Tracking
  • 1,214
  • PDF
End-to-End Representation Learning for Correlation Filter Based Tracking
  • 824
  • Highly Influential
  • PDF
Learning by Tracking: Siamese CNN for Robust Target Association
  • 240
  • PDF
Transfer Learning Based Visual Tracking with Gaussian Processes Regression
  • 396
  • PDF
Fully-Convolutional Siamese Networks for Object Tracking
  • 1,621
  • Highly Influential
  • PDF
Adaptive Color Attributes for Real-Time Visual Tracking
  • 1,097
  • PDF
Siamese Instance Search for Tracking
  • 612
  • PDF
An Incremental Framework for Video-Based Traffic Sign Detection, Tracking, and Recognition
  • 97
  • PDF
...
1
2
3
4
5
...