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Related papers: IMTalker: Efficient Audio-driven Talking Face Gene…

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Recent methods for audio-driven talking head synthesis often optimize neural radiance fields (NeRF) on a monocular talking portrait video, leveraging its capability to render high-fidelity and 3D-consistent novel-view frames. However, they…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Jaehoon Ko , Kyusun Cho , Joungbin Lee , Heeji Yoon , Sangmin Lee , Sangjun Ahn , Seungryong Kim

We present X-Actor, a novel audio-driven portrait animation framework that generates lifelike, emotionally expressive talking head videos from a single reference image and an input audio clip. Unlike prior methods that emphasize lip…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Chenxu Zhang , Zenan Li , Hongyi Xu , You Xie , Xiaochen Zhao , Tianpei Gu , Guoxian Song , Xin Chen , Chao Liang , Jianwen Jiang , Linjie Luo

Audio-driven talking head animation is a challenging research topic with many real-world applications. Recent works have focused on creating photo-realistic 2D animation, while learning different talking or singing styles remains an open…

Computer Vision and Pattern Recognition · Computer Science 2023-03-23 Trong-Thang Pham , Nhat Le , Tuong Do , Hung Nguyen , Erman Tjiputra , Quang D. Tran , Anh Nguyen

Talking face generation has historically struggled to produce head movements and natural facial expressions without guidance from additional reference videos. Recent developments in diffusion-based generative models allow for more realistic…

Computer Vision and Pattern Recognition · Computer Science 2023-08-01 Michał Stypułkowski , Konstantinos Vougioukas , Sen He , Maciej Zięba , Stavros Petridis , Maja Pantic

Precise representations of 3D faces are beneficial to various computer vision and graphics applications. Due to the data discretization and model linearity, however, it remains challenging to capture accurate identity and expression clues…

Computer Vision and Pattern Recognition · Computer Science 2022-04-26 Mingwu Zheng , Hongyu Yang , Di Huang , Liming Chen

Accurate representations of 3D faces are of paramount importance in various computer vision and graphics applications. However, the challenges persist due to the limitations imposed by data discretization and model linearity, which hinder…

Computer Vision and Pattern Recognition · Computer Science 2024-10-14 Mingwu Zheng , Haiyu Zhang , Hongyu Yang , Liming Chen , Di Huang

Recent breakthroughs in video AIGC have ushered in a transformative era for audio-driven human animation. However, conventional video dubbing techniques remain constrained to mouth region editing, resulting in discordant facial expressions…

Computer Vision and Pattern Recognition · Computer Science 2025-08-20 Shaoshu Yang , Zhe Kong , Feng Gao , Meng Cheng , Xiangyu Liu , Yong Zhang , Zhuoliang Kang , Wenhan Luo , Xunliang Cai , Ran He , Xiaoming Wei

In this paper, we propose a talking face generation method that takes an audio signal as input and a short target video clip as reference, and synthesizes a photo-realistic video of the target face with natural lip motions, head poses, and…

Computer Vision and Pattern Recognition · Computer Science 2021-08-19 Chenxu Zhang , Yifan Zhao , Yifei Huang , Ming Zeng , Saifeng Ni , Madhukar Budagavi , Xiaohu Guo

Implementing fine-grained emotion control is crucial for emotion generation tasks because it enhances the expressive capability of the generative model, allowing it to accurately and comprehensively capture and express various nuanced…

Computer Vision and Pattern Recognition · Computer Science 2024-02-05 Guanwen Feng , Haoran Cheng , Yunan Li , Zhiyuan Ma , Chaoneng Li , Zhihao Qian , Qiguang Miao , Chi-Man Pun

Recent diffusion-based talking face generation models have demonstrated impressive potential in synthesizing videos that accurately match a speech audio clip with a given reference identity. However, existing approaches still encounter…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Xingpei Ma , Jiaran Cai , Yuansheng Guan , Shenneng Huang , Qiang Zhang , Shunsi Zhang

We leverage the modern advancements in talking head generation to propose an end-to-end system for talking head video compression. Our algorithm transmits pivot frames intermittently while the rest of the talking head video is generated by…

Computer Vision and Pattern Recognition · Computer Science 2022-10-10 Madhav Agarwal , Anchit Gupta , Rudrabha Mukhopadhyay , Vinay P. Namboodiri , C V Jawahar

Recent advances have demonstrated compelling capabilities in synthesizing real individuals into generated videos, reflecting the growing demand for identity-aware content creation. Nevertheless, an openly accessible framework enabling…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Yingjie Chen , Shilun Lin , Cai Xing , Binxin Yang , Long Zhou , Qixin Yan , Wenjing Wang , Dingming Liu , Hao Liu , Chen Li , Jing Lyu

Recent advancements in audio-driven talking face generation have made great progress in lip synchronization. However, current methods often lack sufficient control over facial animation such as speaking style and emotional expression,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Baiqin Wang , Xiangyu Zhu , Fan Shen , Hao Xu , Zhen Lei

We propose GaussianTalker, a novel framework for real-time generation of pose-controllable talking heads. It leverages the fast rendering capabilities of 3D Gaussian Splatting (3DGS) while addressing the challenges of directly controlling…

Computer Vision and Pattern Recognition · Computer Science 2024-04-26 Kyusun Cho , Joungbin Lee , Heeji Yoon , Yeobin Hong , Jaehoon Ko , Sangjun Ahn , Seungryong Kim

We devise a cascade GAN approach to generate talking face video, which is robust to different face shapes, view angles, facial characteristics, and noisy audio conditions. Instead of learning a direct mapping from audio to video frames, we…

Computer Vision and Pattern Recognition · Computer Science 2019-05-13 Lele Chen , Ross K. Maddox , Zhiyao Duan , Chenliang Xu

We propose an audio-driven talking-head method to generate photo-realistic talking-head videos from a single reference image. In this work, we tackle two key challenges: (i) producing natural head motions that match speech prosody, and (ii)…

Computer Vision and Pattern Recognition · Computer Science 2021-07-21 Suzhen Wang , Lincheng Li , Yu Ding , Changjie Fan , Xin Yu

In this paper, we present a method for reprogramming pre-trained audio-driven talking face synthesis models to operate in a text-driven manner. Consequently, we can easily generate face videos that articulate the provided textual sentences,…

Graphics · Computer Science 2024-01-19 Jeongsoo Choi , Minsu Kim , Se Jin Park , Yong Man Ro

Speech-driven facial animation is useful for a variety of applications such as telepresence, chatbots, etc. The necessary attributes of having a realistic face animation are 1) audio-visual synchronization (2) identity preservation of the…

Computer Vision and Pattern Recognition · Computer Science 2020-05-27 Sanjana Sinha , Sandika Biswas , Brojeshwar Bhowmick

Real-world talking faces often accompany with natural head movement. However, most existing talking face video generation methods only consider facial animation with fixed head pose. In this paper, we address this problem by proposing a…

Computer Vision and Pattern Recognition · Computer Science 2020-03-06 Ran Yi , Zipeng Ye , Juyong Zhang , Hujun Bao , Yong-Jin Liu

Talking head generation is gaining significant importance across various domains, with a growing demand for high-quality rendering. However, existing methods often suffer from identity leakage (IL) and rendering artifacts (RA), particularly…

Computer Vision and Pattern Recognition · Computer Science 2025-07-03 Shuai Tan , Bill Gong , Bin Ji , Ye Pan