Gesture recognition has attracted considerable attention owing to its great potential in
applications. Although the great progress has been made recently in multi-modal learning …

Decoupling spatiotemporal representation refers to decomposing the spatial and temporal
features into dimension-independent factors. Although previous RGB-D-based motion …

The increasing integration of technology in our daily lives demands the development of
more convenient human–computer interaction (HCI) methods. Most of the current hand …

Dynamic action recognition has promising applications in human–computer interaction,
information encryption, and high-speed image processing. However, it is challenging for a …

The ability to discern the shape of hands can be a vital issue in improving the performance
of hand gesture recognition for human–computer interaction. Segmentation itself is a very …

Automatic hand gesture recognition in video sequences has widespread applications,
ranging from home automation to sign language interpretation and clinical operations. The …

Gesture recognition is an important direction in computer vision research. Information from
the hands is crucial in this task. However, current methods consistently achieve attention on …

Motion recognition is a promising direction in computer vision, but the training of video
classification models is much harder than images due to insufficient data and considerable …

Recent improvements in dynamic hand gesture recognition have seen a shift from traditional
convolutional architectures to attention-based networks. These attention networks have …

Transformer models have achieved state-of-the-art results in many applications like NLP
classification etc. But their exploration in gesture recognition task is still limited. So we …