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 …

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 …

Recent advances in neural rendering have improved both training and rendering times by
orders of magnitude. While these methods demonstrate state-of-the-art quality and speed …

Modeling animatable human avatars from RGB videos is a long-standing and challenging
problem. Recent works usually adopt MLP-based neural radiance fields (NeRF) to represent …

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 …

In this paper, we take one step further towards real-world applicability of monocular neural
avatar reconstruction by contributing InstantAvatar, a system that can reconstruct human …

We introduce TADA, a simple-yet-effective approach that takes textual descriptions and
produces expressive 3D avatars with high-quality geometry and lifelike textures, that can be …

While progress in 2D generative models of human appearance has been rapid, many
applications require 3D avatars that can be animated and rendered. Unfortunately, most …

Real-time rendering of photorealistic and controllable human avatars stands as a
cornerstone in Computer Vision and Graphics. While recent advances in neural implicit …

Despite recent research advancements in reconstructing clothed humans from a single
image, accurately restoring the “unseen regions” with high-level details remains an …