本文介绍我们在"TalkingGaussian: Structure-Persistent 3D Talking Head Synthesis viaGaussian Splatting". 作者: Jiahe Li, Jiawei Zhang, Xiao Bai, Jin Zheng, Xin Ning, Jun Zhou, Lin Gu 单位: 北京航空航天大学,中科院半导体所,格里菲斯大学,RIKEP AIP,东京大学 链接:Paper|Project|Video|Code 除了在视觉...
MonoGaussianAvatar是在PointAvatar的框架基础上,将点修改为高斯点表示,并结合gaussian-splatting技术,针对PointAvatar的一些问题进行优化而最终得到的一个talkinghead生成框架。 PointAvatar github.com/zhengyuf/Poi呵呵哒:【talkinghead】3D-GS系列1:PointAvatar学习 摘要 单目视频序列重建高清数字人技术。基于3DMM的方法...
除此之外,Gaussian Splatting根本不涉及任何神经网络,甚至没有一个小型的 MLP,也没有什么 "神经"的东西,场景本质上只是空间中的一组点。在大家都在研究数十亿个参数组成的模型的人工智能世界里,这种方法越来越受欢迎,令人耳目一新。它的想法源于 "Surface splatting"(2001 年),说明经典的计算机视觉方法仍然可以激发...
To tackle this challenge, we introduce TalkingGaussian, a deformation-based radiance fields framework for high-fidelity talking head synthesis. Leveraging the point-based Gaussian Splatting, facial motions can be represented in our method by applying smooth and continuous deformations to persistent ...
【GaussianTalker: Real-Time High-Fidelity Talking Head Synthesis with Audio-Driven 3D Gaussian Splatting】 文章链接:http://arxiv.org/abs/2404.16012 项目主页: https://ku-cvlab.github.io/GaussianTalker 我们提出了一种新的框架GaussianTalker,用于实时生成姿势可控的说话者的头部。它利用了3D高斯泼溅( 3D...
Add "TranSplat: Lighting-Consistent Cross-Scene Object Transfer with 3D Gaussian Splatting" Add "Audio-Plane: Audio Factorization Plane Gaussian Splatting for Real-Time Talking Head Synthesis" Add "EndoLRMGS: Complete Endoscopic Scene Reconstruction combining Large Reconstruction Modelling and Gaussian Sp...
"GaussianTalker: Real-Time High-Fidelity Talking Head Synthesis with Audio-Driven 3D Gaussian Splatting" by Kyusun Cho*, Joungbin Lee*, Heeji Yoon*, Yeobin Hong, Jaehoon Ko, Sangjun Ahn, Seungryong Kim† ⚡️News ❗️2024.06.13: We also generated the torso in the same space as...
To breathe life into the static world, we propose Gaussians2Life, a method for animating parts of high-quality 3D scenes in a Gaussian Splatting representation. Our key idea is to leverage powerful video diffusion models as the generative component of our model and to combine these with a ...
首先简单介绍一下,3DGS是如何表示真实场景的,前面也有提过,在Gaussian Splatting中,3D世界用一组3D点表示,实际上是数百万个,大致在0.5到5百万之间。每个点是一个3D高斯,具有其独特的参数,这些参数是为每个场景拟合的,以便该场景的渲染与已知数据集图像紧密匹配,接下来就介绍他的属性。
【GaussianTalker: Real-Time High-Fidelity Talking Head Synthesis with Audio-Driven 3D Gaussian Splatting】 文章链接:http://arxiv.org/abs/2404.16012 项目主页: https://ku-cvlab.github.io/GaussianTalker 我们提出了一种新的框架GaussianTalker,用于实时生成姿势可控的说话者的头部。它利用了3D高斯泼溅( 3D...