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 …

Fashion is the way we present ourselves to the world and has become one of the world's
largest industries. Fashion, mainly conveyed by vision, has thus attracted much attention …

The combination of deep learning, artist-curated scans, and Implicit Functions (IF), is
enabling the creation of detailed, clothed, 3D humans from images. However, existing …

We introduce a free-viewpoint rendering method--HumanNeRF--that works on a given
monocular video of a human performing complex body motions, eg a video from YouTube …

We present GaussianAvatar an efficient approach to creating realistic human avatars with
dynamic 3D appearances from a single video. We start by introducing animatable 3D …

3D avatar creation plays a crucial role in the digital age. However, the whole production
process is prohibitively time-consuming and labor-intensive. To democratize this technology …

Recent advances in machine learning have led to increased interest in solving visual
computing problems using methods that employ coordinate‐based neural networks. These …

Current methods for learning realistic and animatable 3D clothed avatars need either posed
3D scans or 2D images with carefully controlled user poses. In contrast, our goal is to learn …

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 …

We propose Neural Actor (NA), a new method for high-quality synthesis of humans from
arbitrary viewpoints and under arbitrary controllable poses. Our method is developed upon …