Visual Object Tracking On Otb 2013

AUC

Results

Performance results of various models on this benchmark

		Paper Title
SE-SiamFC	0.68	Scale Equivariance Improves Siamese Tracking
SA-Siam	0.677	A Twofold Siamese Network for Real-Time Object Tracking
RASNet	0.670	Learning Attentions: Residual Attentional Siamese Network for High Performance Online Visual Tracking
SiamVGG	0.665	SiamVGG: Visual Tracking using Deeper Siamese Networks
DSiam	0.656	Learning Dynamic Siamese Network for Visual Object Tracking
CFNet	0.611	End-to-end representation learning for Correlation Filter based tracking
SiamFC-3s	0.607	Fully-Convolutional Siamese Networks for Object Tracking

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