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 …

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 …

Abstract 3D-aware generative adversarial networks (GANs) synthesize high-fidelity and
multi-view-consistent facial images using only collections of single-view 2D imagery …

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 …

Generating high-quality and diverse human images is an important yet challenging task in
vision and graphics. However, existing generative models often fall short under the high …

Unconditional human image generation is an important task in vision and graphics, enabling
various applications in the creative industry. Existing studies in this field mainly focus on …

Efficient generation of 3D digital humans is important in several industries including virtual
reality social media and cinematic production. 3D generative adversarial networks (GANs) …

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 …

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

We present DINAR, an approach for creating realistic rigged fullbody avatars from single
RGB images. Similarly to previous works, our method uses neural textures combined with …