Customized Anchors Can Better Fit the Target in Siamese Tracking

Most existing siamese trackers rely on some fixed anchors to estimate the scale and aspect ratio for all targets. However, in real tracking, different targets have different sizes and shapes, these predefined anchors are not enough to cover all possible scales and aspect ratios caused by various movement and deformation, so an adaptive scale and aspect ratio estimation method is expected for robust online tracking. In this paper, a customized anchor generation module is first proposed to estimate the shape of the target and generate customized anchors adapted to the target. Then, through an anchor adaptation module, each anchor information is embed into corresponding feature to learn more discriminative features. Finally, We design a Target-aware feature correlation module to reduce the interference of background information. It takes the region of interest of template as variable template and its central subregion as central template, and then performs global and local correlation operations, respectively. Experiments on benchmarks including OTB100, VOT2019, LaSOT, UAV123, and VOT2018 show that our tracker achieves promising performance.