Human pose estimation aims to locate the human body parts and build human body
representation (eg, body skeleton) from input data such as images and videos. It has drawn …

Estimating human pose and shape from monocular images is a long-standing problem in
computer vision. Since the release of statistical body models, 3D human mesh recovery has …

Abstract We present Vid2Avatar, a method to learn human avatars from monocular in-the-
wild videos. Reconstructing humans that move naturally from monocular in-the-wild videos …

It is extremely challenging to create an animatable clothed human avatar from RGB videos,
especially for loose clothes due to the difficulties in motion modeling. To address this …

Animating virtual avatars with free-view control is crucial for various applications like virtual
reality and digital entertainment. Previous studies have attempted to utilize the …

Modelling interactions between humans and objects in natural environments is central to
many applications including gaming, virtual and mixed reality, as well as human behavior …

Motion capture from sparse inertial sensors has shown great potential compared to image-
based approaches since occlusions do not lead to a reduced tracking quality and the …

Human volumetric capture is a long-standing topic in computer vision and computer
graphics. Although high-quality results can be achieved using sophisticated off-line systems …

Recent neural human representations can produce high-quality multi-view rendering but
require using dense multi-view inputs and costly training. They are hence largely limited to …

Abstract We present Non-Rigid Neural Radiance Fields (NR-NeRF), a reconstruction and
novel view synthesis approach for general non-rigid dynamic scenes. Our approach takes …