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In this paper, a MDSPF method is proposed to learn a robust observation model for representing the targets by training a CNN with a number of video sequences. The CNN architecture is composed of three shared convolutional units, two shared fully connected (Fc) units and a multiple domain Fc unit, and it is offline trained by a multi-domain learning strategy. After training, the shared convolutional units are remained as an observation model for our tracking framework. The features from thedoi:10.1109/access.2020.2973338 fatcat:uqz67quz65finoaioieegyakbe