Efficient rendering of photo‐realistic virtual worlds is a long standing effort of computer
graphics. Modern graphics techniques have succeeded in synthesizing photo‐realistic …

Generative deep learning algorithms have progressed to a point where it is difficult to tell the
difference between what is real and what is fake. In 2018, it was discovered how easy it is to …

Synthesizing photo‐realistic images and videos is at the heart of computer graphics and has
been the focus of decades of research. Traditionally, synthetic images of a scene are …

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 …

Abstract We present Non-Rigid Neural Radiance Fields (NR-NeRF), a reconstruction and
novel view synthesis approach for general non-rigid dynamic scenes. Our approach takes …

Photorealistic rendering and reposing of humans is important for enabling augmented reality
experiences. We propose a novel framework to reconstruct the human and the scene that …

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 …

Image-to-image translation (I2I) aims to transfer images from a source domain to a target
domain while preserving the content representations. I2I has drawn increasing attention and …

Abstract We present Neural Articulated Radiance Field (NARF), a novel deformable 3D
representation for articulated objects learned from images. While recent advances in 3D …