A Two Step Approach for Joint Detection

Human joints can be used in areas such as activity recognition, animation, augmented reality and robotics. Thus, there is a need to correctly detect these points. This paper proposes a two step method for joint detection. First an initial prediction is performed using the HRNet network. In the second step an improvement is applied on the initial predictions for each joint using a convolutional neural network. Tests were performed using the Unite the People dataset. The new model is able to improve the results of the base model by 1.81%.

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