Self-supervised Object Tracking with Cycle-consistent Siamese Networks
Weihao Yuan,Michael Yu Wang,Qifeng Chen,Weihao Yuan,Michael Yu Wang,Qifeng Chen
Self-supervised learning for visual object tracking possesses valuable advantages compared to supervised learning, such as the non-necessity of laborious human annotations and online training. In this work, we exploit an end-to-end Siamese network in a cycle-consistent self-supervised framework for object tracking. Self-supervision can be performed by taking advantage of the cycle consistency in t...
