Abstract Existing Human NeRF methods for reconstructing 3D humans typically rely on
multiple 2D images from multi-view cameras or monocular videos captured from fixed …

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

Reconstructing 3D clothed human avatars from single images is a challenging task,
especially when encountering complex poses and loose clothing. Current methods exhibit …

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 …

Creating high-quality 3D models of clothed humans from single images for real-world
applications is crucial. Despite recent advancements accurately reconstructing humans in …

We present an approach to generate a 360-degree view of a person with a consistent, high-
resolution appearance from a single input image. NeRF and its variants typically require …

Generating a 3D human model from a single reference image is challenging because it
requires inferring textures and geometries in invisible views while maintaining consistency …

In this work we propose a method to address the challenge of rendering a 3D human from a
single image in a free-view manner. Some existing approaches could achieve this by using …

A long-standing goal of 3D human reconstruction is to create lifelike and fully detailed 3D
humans from single-view images. The main challenge lies in inferring unknown body …

We propose RANA, a relightable and articulated neural avatar for the photorealistic
synthesis of humans under arbitrary viewpoints, body poses, and lighting. We only require a …