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 …

GAN inversion aims to invert a given image back into the latent space of a pretrained GAN
model so that the image can be faithfully reconstructed from the inverted code by the …

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 …

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 …

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 …

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 …

We present ARCH++, an image-based method to reconstruct 3D avatars with arbitrary
clothing styles. Our reconstructed avatars are animation-ready and highly realistic, in both …

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 …