Abstract: Siamese network is an important method for visual object tracking. SiamDW uses RPN to locate the object, which needs to preset more hyperparameters such as height-width ratio of anchors. It is tedious and a bit inaccurate. To address this issue, this paper proposes a Siamese visual object tracking algorithm based on anchor free considering channel attention. On the basis of SiamDW, this method introduced DenseNet with no padding to extract object's feature, and added channel attention module in channel concatenation to improve the feature representation. A rectangular range method was used to discriminate positive and negative samples. Results show that compared with baseline (SiamDW), the AUC of our method was increased by 3 and 6 percentage points on VOT2016 and VOT2018 datasets respectively.