Increased global competition has placed a premium on customer satisfaction, and there is a
greater demand for manufacturers to be flexible with their products and services. This …

Recently, the concept of human-robot collaboration has raised many research interests.
Instead of robots replacing human workers in workplaces, human-robot collaboration allows …

Abstract Analysis of hand-hand interactions is a crucial step towards better understanding
human behavior. However, most researches in 3D hand pose estimation have focused on …

We propose a method for annotating images of a hand manipulating an object with the 3D
poses of both the hand and the object, together with a dataset created using this method …

We present an approach that uses a multi-camera system to train fine-grained detectors for
keypoints that are prone to occlusion, such as the joints of a hand. We call this procedure …

We address the highly challenging problem of real-time 3D hand tracking based on a
monocular RGB-only sequence. Our tracking method combines a convolutional neural …

We present a unified deformation model for the markerless capture of multiple scales of
human movement, including facial expressions, body motion, and hand gestures. An initial …

The two-hand interaction is one of the most challenging signals to analyze due to the self-
similarity, complicated articulations, and occlusions of hands. Although several datasets …

Most of the existing deep learning-based methods for 3D hand and human pose estimation
from a single depth map are based on a common framework that takes a 2D depth map and …

In this work we study the use of 3D hand poses to recognize first-person dynamic hand
actions interacting with 3D objects. Towards this goal, we collected RGB-D video sequences …