RANA: Relightable Articulated Neural Avatars

Understand

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 short video clip of the person to create the avatar and assume no knowledge about the lighting environment.
• We present a novel framework to model humans while disentangling their geometry, texture, and also lighting environment from monocular RGB videos.
• To simplify this otherwise ill-posed task we first estimate the coarse geometry and texture of the person via SMPL+D model fitting and then learn an articulated neural representation for photorealistic image generation.