The field of vision-based human hand three-dimensional (3D) shape and pose estimation
has attracted significant attention recently owing to its key role in various applications, such …

With increasing applications of 3D hand pose estimation in various human-computer
interaction applications, convolution neural networks (CNNs) based estimation models have …

Depth images and point clouds are the two most commonly used data representations for
depth-based 3D hand pose estimation. Benefiting from the structuring of image data and the …

Abstract 3D hand pose estimation methods have made significant progress recently.
However, estimation accuracy is often far from sufficient for specific real-world applications …

The field of 3D hand pose estimation has been gaining a lot of attention recently, due to its
significance in several applications that require human-computer interaction (HCI). The …

Reconstructing interacting hands from a single RGB image is a very challenging task. On the
one hand, severe mutual occlusion and similar local appearance between two hands …

In this paper, we propose an adaptive weighting regression (AWR) method to leverage the
advantages of both detection-based and regression-based method. Hand joint coordinates …

Abstract 3D hand pose estimation is a critical task in various human-computer interaction
applications. Numerous deep learning based estimation models in this domain have been …

In this work, we study the cross-view information fusion problem in the task of self-
supervised 3D hand pose estimation from the depth image. Previous methods usually adopt …

We study how well different types of approaches generalise in the task of 3D hand pose
estimation under single hand scenarios and hand-object interaction. We show that the …