This paper addresses the challenge of reconstructing an animatable human model from a
multi-view video. Some recent works have proposed to decompose a non-rigidly deforming …

This paper addresses the challenge of novel view synthesis for a human performer from a
very sparse set of camera views. Some recent works have shown that learning implicit …

In this paper, we aim at synthesizing a free-viewpoint video of an arbitrary human
performance using sparse multi-view cameras. Recently, several works have addressed this …

Learning 3D human pose prior is essential to human-centered AI. Here, we present GFPose,
a versatile framework to model plausible 3D human poses for various applications. At the …

Due to the lack of camera parameter information for in-the-wild images, existing 3D human
pose and shape (HPS) estimation methods make several simplifying assumptions: weak …

Reconstructing 3D digital models of humans from sensory data is a long-standing problem
in computer vision and graphics with a variety of applications in VR/AR, film production, and …

We present an approach for 3D global human mesh recovery from monocular videos
recorded with dynamic cameras. Our approach is robust to severe and long-term occlusions …

While deep learning reshaped the classical motion capture pipeline with feed-forward
networks, generative models are required to recover fine alignment via iterative refinement …

Movement dataset reviews exist but are limited in coverage, both in terms of size and
research discipline. While topic-specific reviews clearly have their merit, it is critical to have a …

Understanding social interactions from egocentric views is crucial for many applications,
ranging from assistive robotics to AR/VR. Key to reasoning about interactions is to …