Abstract
We present a novel method for high detail-preserving human avatar creation from monocular video. A parameterized body model is refined and optimized to maximally resemble subjects from a video showing them from all sides. Our avatars feature a natural face, hairstyle, clothes with garment wrinkles, and high-resolution texture. Our paper contributes facial landmark and shading-based human body shape refinement, a semantic texture prior, and a novel texture stitching strategy, resulting in the most sophisticated-looking human avatars obtained from a single video to date. Numerous results show the robustness and versatility of our method. A user study illustrates its superiority over the state-of-the-art in terms of identity preservation, level of detail, realism, and overall user preference.
Abstract (translated)
我们提出了一种新的方法，用于从单眼视频中保留高细节的人类头像。对参数化的身体模型进行了细化和优化，以最大限度地模拟来自所有侧面的视频中的主体。我们的头像具有自然的面容，发型，衣服，皱纹和高分辨率的质地。我们的论文提供面部标志和基于阴影的人体形状细化，语义纹理优先和新颖的纹理拼接策略，从而产生从迄今为止的单个视频获得的最复杂的人类化身。大量结果表明了我们方法的稳健性和多功能性。用户研究表明其在身份保护，细节水平，现实主义和整体用户偏好方面优于现有技术。
URL
https://arxiv.org/abs/1808.01338
