Lune

NeurIPS2023顶会

DELIFFAS: Deformable Light Fields for Fast Avatar Synthesis

Youngjoong Kwon, Lingjie Liu, Henry Fuchs, Marc Habermann, Christian Theobalt

2023年份
45被引次数
18顶会引用

摘要

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 terms of either photorealism or inference speed while the combination of the two desired properties still remains unsolved. To this end, we propose a novel method, called DELIFFAS, which parameterizes the appearance of the human as a surface light field that is attached to a controllable and deforming human mesh model. At the core, we represent the light field around the human with a deformable two-surface parameterization, which enables fast and accurate inference of the human appearance. This allows perceptual supervision on the full image compared to previous approaches that could only supervise individual pixels or small patches due to their slow runtime. Our carefully designed human representation and supervision strategy leads to state-of-the-art synthesis results and inference time. The video results and code are available at https://vcai. mpi-inf.mpg.de/projects/DELIFFAS .

问问这篇 Paper

智能体会读完全文。

Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。

可以从这些问题问起

智能体调用

Luneget_paper_fulltext

在 Lune 里问

免费开始,无需绑卡

引用它的顶会 Paper18

问问它们各自怎么用它

它引用的顶会 Paper18

相关 Paper

黄昏的海面,两侧是细线勾勒的悬崖