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Siamese adversarial network for object tracking

Siamese adversarial network for object tracking

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In this Letter, a Siamese adversarial network tracker (SANT) is proposed. Recently, in computer vision field, generative adversarial network (GAN) has been widely used for image and video generation. Using the GAN, the proposed method constructs a Siamese adversarial network (SAN) for object tracking. Unlike existing GANs, the proposed SAN uses similarity learning with SAN discriminator. To show the effectiveness of the proposed SAN, the same structure as the residual long-short-term memory tracker is used. Experimental results show that the proposed SANT achieves the highest performance among existing Siamese trackers.

http://iet.metastore.ingenta.com/content/journals/10.1049/el.2018.7104
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