Sign language, as a different form of the communication language, is important to large
groups of people in society. There are different signs in each sign language with variability …

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 …

We present HOI4D, a large-scale 4D egocentric dataset with rich annotations, to catalyze the
research of category-level human-object interaction. HOI4D consists of 2.4 M RGB-D …

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 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 …

Low-cost consumer depth cameras and deep learning have enabled reasonable 3D hand
pose estimation from single depth images. In this paper, we present an approach that …

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 …

Regression based methods are not performing as well as detection based methods for
human pose estimation. A central problem is that the structural information in the pose is not …

Deep learning for predicting or generating 3D human pose sequences is an active research
area. Previous work regresses either joint rotations or joint positions. The former strategy is …

Estimating 3D hand meshes from single RGB images is challenging, due to intrinsic 2D-3D
mapping ambiguities and limited training data. We adopt a compact parametric 3D hand …