The ability of computers to recognise hand gestures visually is essential for progress in
human–computer interaction. Gesture recognition has applications ranging from sign …

Hand gesture recognition is viewed as a significant field of exploration in computer vision
with assorted applications in the human–computer communication (HCI) community. The …

We propose a unified formulation for the problem of 3D human pose estimation from a single
raw RGB image that reasons jointly about 2D joint estimation and 3D pose reconstruction to …

This paper addresses the challenge of 3D full-body human pose estimation from a
monocular image sequence. Here, two cases are considered:(i) the image locations of the …

Temporal interpolation often plays a crucial role to learn meaningful representations in
dynamic scenes. In this paper, we propose a novel method to train spatiotemporal neural …

Recovering 3D full-body human pose is a challenging problem with many applications. It
has been successfully addressed by motion capture systems with body worn markers and …

We propose C3DPO, a method for extracting 3D models of deformable objects from 2D
keypoint annotations in unconstrained images. We do so by learning a deep network that …

We present an approach to dense depth estimation from a single monocular camera that is
moving through a dynamic scene. The approach produces a dense depth map from two …

Accurately and efficiently modeling dynamic scenes and motions is considered so
challenging a task due to temporal dynamics and motion complexity. To address these …

This paper offers the first variational approach to the problem of dense 3D reconstruction of
non-rigid surfaces from a monocular video sequence. We formulate nonrigid structure from …