In this paper we introduce a large-scale hand pose dataset, collected using a novel capture
method. Existing datasets are either generated synthetically or captured using depth …

Real-time sensing and modeling of the human body, especially the hands, is an important
research endeavor for various applicative purposes such as in natural human computer …

To facilitate the analysis of human actions, interactions and emotions, we compute a 3D
model of human body pose, hand pose, and facial expression from a single monocular …

This work addresses a novel and challenging problem of estimating the full 3D hand shape
and pose from a single RGB image. Most current methods in 3D hand analysis from …

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 …

We present the first method to capture the 3D total motion of a target person from a
monocular view input. Given an image or a monocular video, our method reconstructs the …

The human hand moves in complex and high-dimensional ways, making estimation of 3D
hand pose configurations from images alone a challenging task. In this work we propose a …