NeRF-AD: Neural Radiance Field with Attention-based Disentanglement for Talking Face Synthesis 论文作者: Chongke Bi, Xiaoxing Liu, Zhilei Liu 导读:本文提出了一种新的说话人脸合成框架,该框架在NeRF中加入了基于注意力的解耦模块,从而可以使NeRF在渲染重建过程中,图像生成质量和嘴型同步提高都有得到不同程度...
分享一篇使用神经辐射场方法建模数字人的论文:Audio Driven Neural Radiance Fields for Talking Head Synthesis,ICCV2021,Github code。 模型结构 图1 AD-NeRF模型图 摘要 通过输入音频序列生成高保真说话人脸视频是一个具有挑战性的问题,该问题近来受到了极大关注。在本论文中,作者提出使用神经场景表示网络解决该问题。
论文题目:NeRF-AD: Neural Radiance Field with Attention-based Disentanglement for Talking Face Synthesis 作者:Chongke Bi, Xiaoxing Liu等 作者机构:College of Intelligence and Computing, Tianjin University, Tianjin, China 论文链接:https://arxiv.org/pdf/2401.12852.pdf 本文提出了一种通过具有基于注意力解...
也就是真值与解码器输出值之间的距离。 ■2.3 Nerual Radiance Field for Talking Face Synthesis(NeRF用于说话人脸的合成) 本文提出了一种有条件(音频面部及身份特征)的NeRF用于说话人脸的合成,也就是说,隐函数θ的输入包含了条件、3D位置和视图...
这篇文章主要针对的任务是talking face generation,也有一种说法是audio driven face reenactment。实际上整个流程是给定一段语音,和源人脸,生成一段说话人视频。 很多方法都是身份无关的,即模型训练好之后,可以生成多个人的说话视频。 AD-Nerf使用了Nerf作为基础架构,限定了当前人物的信息,一个模型只可以生成一个人...
GeneFace: Generalized and High-Fidelity 3D Talking Face Synthesis; ICLR 2023; Official code pytorch nerf talking-face-generation Updated Oct 18, 2024 Python Anttwo / SuGaR Star 2.5k Code Issues Pull requests [CVPR 2024] Official PyTorch implementation of SuGaR: Surface-Aligned Gaussian Splat...
[AIGC&CG进展] 上海科技大学、Deemos提出DreamFace,仅通过文本控制生成个性化的3D人脸,并可以支持人脸老化、化妆或通过视频进行人脸动画控制 04:14 [Diffusion生成NeRF] TUM, Apple提出HyperDiffusion,用Diffusion计算神经场权重,统一框架下生成3D权重或4D动画 03:19 [NeRF Relighting进展,SIGGRAPH] 浙大、微软亚研...
First of all, I would like to creditUK Nerf Facebook’s pagefor almost all the Official information, product images and descriptions. Do check out his page too! Also, I would like to creditAbout Nerffor the the Brainsaw, the Modulus Close Quarters Combat Kit and The Zombie Strike Silent...
NERF Legends launches you into a futuristic, sci-fi world where you come face-to-face with legions of robot enemies and ultimate boss masters. Armed with a powerful arsenal of NERF blasters based on their iconic, real-world counterparts, you battle formidable enemies while being challenged to ...
However, these methods still face difficulties during dramatic camera movement. We tackle this challenging problem by incorporating undistorted monocular depth priors. These priors are generated by correcting scale and shift parameters during training, with which we are then able to constrain the relative...