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

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 …

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 …

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 …

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 …

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 …

We present SCANimate, an end-to-end trainable framework that takes raw 3D scans of a
clothed human and turns them into an animatable avatar. These avatars are driven by pose …

This paper targets high-fidelity and real-time view synthesis of dynamic 3D scenes at 4K
resolution. Recent methods on dynamic view synthesis have shown impressive rendering …