Yifang Men

AI视频后期—

This paper targets to mimicking anyone anywhere with complex motions and object interactions.

以下是对MIMO项目网站内容的整理：

核心内容概述

MIMO（Controllable Character Video Synthesis with Spatial Decomposed Modeling）是一个可控角色视频合成框架，旨在通过简单的用户输入（如参考图像、姿势序列或视频）生成具有可控属性（如角色、动作和场景）的角色视频。该方法采用空间分解建模，能够处理复杂的动作和场景交互，具有高度的可扩展性和通用性。

网站重点功能或内容

1. arXiv：提供论文的预印本，供学术界参考。

2. 在线演示：允许用户上传参考图像和视频，实时体验MIMO模型的合成效果。

3. 前后文链接：提供与MIMO相关的前后续研究项目链接，展示研究的连续性和扩展性。

4. 视频：展示MIMO模型生成的视频示例，展示其效果和应用场景。

5. 代码：提供MIMO模型的实现代码，供研究人员使用和修改。

6. 论文：详细介绍MIMO方法的理论背景和实验结果。

网站内容整理

盾灵安全导航

Given a RGB video captured by a monocular camera, our method can generate editable 3D avatar that enables both text and image-guided 3D editing. A novel representation, Tetrahedron-constrained Gaussian Splatting (TetGS) is introduced to combine the structured nature of tetrahedral grids and the high-precision rendering capabilities of 3DGS.

MIMO, a generalizable model for controllable video synthesis, can Mimic anyone anywhere in complex Motions with Object interactions. It simultaneously achieves advanced scalability to arbitrary characters, generality to novel 3D motions, and applicability to interactive real-world scenes in a unified framework.