Generating controllable and photorealistic digital human avatars is a long-standing and
important problem in Vision and Graphics. Recent methods have shown great progress in …

Creating pose-driven human avatars is about modeling the mapping from the low-frequency
driving pose to high-frequency dynamic human appearances, so an effective pose encoding …

Dynamic human rendering from video sequences has achieved remarkable progress by
formulating the rendering as a mapping from static poses to human images. However …

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 …

Convenient 4D modeling of human-object interactions is essential for numerous
applications. However, monocular tracking and rendering of complex interaction scenarios …

This paper focuses on advancing the applicability of human avatar learning methods by
proposing RAM-Avatar which learns a Real-time photo-realistic Avatar that supports full …

We present a system to create Mobile Realistic Fullbody (MoRF) avatars. MoRF avatars are
rendered in real-time on mobile devices, learned from monocular videos, and have high …

Generative DNNs are a powerful tool for image synthesis, but they are limited by their
computational load. On the other hand, given a trained model and a task, eg faces …

Although 3D Gaussian Splatting (3DGS) has recently made progress in 3D human
reconstruction, it primarily relies on 2D pixel-level supervision, overlooking the geometric …

We introduce a method to generate temporally coherent human animation from a single
image, a video, or a random noise. This problem has been formulated as modeling of an …