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Graph Convolutional Tracking
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Tracking by siamese networks has achieved favorable performance in recent years. However, most of existing siamese methods do not take full advantage of spatialtemporal target appearance modeling under different contextual situations. In fact, the spatial-temporal information can provide diverse features to enhance the target representation, and the context information is important for online adaption of target localization. To comprehensively leverage the spatial-temporal structure ofdoi:10.1109/cvpr.2019.00478 dblp:conf/cvpr/GaoZX19 fatcat:gbvsjl2szjccnciwhajkynipwe