Hand gesture recognition from images is a critical task with various real-world applications,
particularly in the field of human–robot interaction. Industrial environments, where non …

Surface electromyography (sEMG)-based gesture recognition can achieve high intra-
session performance. However, the inter-session performance of gesture recognition …

Hand gesture recognition has a wide range of applications, including in the automotive and
industrial sectors, health assistive systems, authentication, and so on. Thermal images are …

Neuromuscular diseases or physical disabilities have the potential to impair hand dexterity,
significantly affecting daily life. To date, technologies for hand gesture recognition based on …

Hand gesture recognition is one of the most widely explored areas under the human–
computer interaction domain. Although various modalities of hand gesture recognition have …

Despite recent successes in hand pose estimation, there yet remain challenges on RGB-
based 3D hand pose estimation (HPE) under hand-object interaction (HOI) scenarios where …

The uncertainty of hand gestures, the variability of gestures across subjects, and the high
cost of collecting a large amount of annotated data lead to a great challenge to the robust …

We designed an interface to support hand rehabilitation tasks to restore hand function and
relieve discomfort. The interface requires accurate hand segmentation, which is impeded by …

We aim to improve the performance of regressing hand keypoints and segmenting pixel-
level hand masks under new imaging conditions (eg., outdoors) when we only have labeled …

Deep learning solutions for hand pose estimation are now very reliant on comprehensive
datasets covering diverse camera perspectives, lighting conditions, shapes, and pose …