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Audio-driven talking-head generation is a crucial and useful technology for virtual human interaction and film-making. While recent advances have focused on improving image fidelity and lip synchronization, generating accurate emotional…

Computer Vision and Pattern Recognition · Computer Science 2025-05-05 Wenqing Wang , Yun Fu

Talking head generation is to synthesize a lip-synchronized talking head video by inputting an arbitrary face image and corresponding audio clips. Existing methods ignore not only the interaction and relationship of cross-modal information,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Sen Chen , Zhilei Liu , Jiaxing Liu , Longbiao Wang

How much can we infer about an emotional voice solely from an expressive face? This intriguing question holds great potential for applications such as virtual character dubbing and aiding individuals with expressive language disorders.…

Sound · Computer Science 2025-02-04 Jiaxin Ye , Boyuan Cao , Hongming Shan

Recent advancements in video diffusion models have significantly enhanced audio-driven portrait animation. However, current methods still suffer from flickering, identity drift, and poor audio-visual synchronization. These issues primarily…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Zhenjie Liu , Jianzhang Lu , Renjie Lu , Cong Liang , Shangfei Wang

In this paper, we introduce a simple and novel framework for one-shot audio-driven talking head generation. Unlike prior works that require additional driving sources for controlled synthesis in a deterministic manner, we instead…

Graphics · Computer Science 2022-12-09 Zhentao Yu , Zixin Yin , Deyu Zhou , Duomin Wang , Finn Wong , Baoyuan Wang

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

Joint audio-video generation models have shown that unified generation yields stronger cross-modal coherence than cascaded approaches. However, existing models couple modalities throughout denoising via pervasive attention, treating…

Computer Vision and Pattern Recognition · Computer Science 2026-04-28 Zhen Ye , Xu Tan , Aoxiong Yin , Hongzhan Lin , Guangyan Zhang , Peiwen Sun , Yiming Li , Chi-Min Chan , Wei Ye , Shikun Zhang , Wei Xue

Audio-driven talking-head generation has advanced rapidly with diffusion-based generative models, yet producing temporally coherent videos with fine-grained motion control remains challenging. We propose DEMO, a flow-matching generative…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Peiyin Chen , Zhuowei Yang , Hui Feng , Sheng Jiang , Rui Yan

We propose a novel talking head synthesis pipeline called "DiT-Head", which is based on diffusion transformers and uses audio as a condition to drive the denoising process of a diffusion model. Our method is scalable and can generalise to…

Artificial Intelligence · Computer Science 2023-12-12 Aaron Mir , Eduardo Alonso , Esther Mondragón

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

We introduce FaceTalk, a novel generative approach designed for synthesizing high-fidelity 3D motion sequences of talking human heads from input audio signal. To capture the expressive, detailed nature of human heads, including hair, ears,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Shivangi Aneja , Justus Thies , Angela Dai , Matthias Nießner

Despite previous success in generating audio-driven talking heads, most of the previous studies focus on the correlation between speech content and the mouth shape. Facial emotion, which is one of the most important features on natural…

Computer Vision and Pattern Recognition · Computer Science 2021-05-21 Xinya Ji , Hang Zhou , Kaisiyuan Wang , Wayne Wu , Chen Change Loy , Xun Cao , Feng Xu

Several works have developed end-to-end pipelines for generating lip-synced talking faces with various real-world applications, such as teaching and language translation in videos. However, these prior works fail to create realistic-looking…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Sahil Goyal , Shagun Uppal , Sarthak Bhagat , Yi Yu , Yifang Yin , Rajiv Ratn Shah

Audio-driven talking head generation has drawn growing attention. To produce talking head videos with desired facial expressions, previous methods rely on extra reference videos to provide expression information, which may be difficult to…

Computer Vision and Pattern Recognition · Computer Science 2024-08-13 Yifeng Ma , Suzhen Wang , Yu Ding , Bowen Ma , Tangjie Lv , Changjie Fan , Zhipeng Hu , Zhidong Deng , Xin Yu

Audio-driven 3D facial animation synthesis has been an active field of research with attention from both academia and industry. While there are promising results in this area, recent approaches largely focus on lip-sync and identity…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Sichun Wu , Kazi Injamamul Haque , Zerrin Yumak

In this work, we tackle the challenge of enhancing the realism and expressiveness in talking head video generation by focusing on the dynamic and nuanced relationship between audio cues and facial movements. We identify the limitations of…

Computer Vision and Pattern Recognition · Computer Science 2024-08-09 Linrui Tian , Qi Wang , Bang Zhang , Liefeng Bo

Recent advances in talking face generation have significantly improved facial animation synthesis. However, existing approaches face fundamental limitations: 3DMM-based methods maintain temporal consistency but lack fine-grained regional…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Kangwei Liu , Junwu Liu , Yun Cao , Jinlin Guo , Xiaowei Yi

Visual emotion expression plays an important role in audiovisual speech communication. In this work, we propose a novel approach to rendering visual emotion expression in speech-driven talking face generation. Specifically, we design an…

Audio and Speech Processing · Electrical Eng. & Systems 2021-07-23 Sefik Emre Eskimez , You Zhang , Zhiyao Duan

Vivid talking face generation holds immense potential applications across diverse multimedia domains, such as film and game production. While existing methods accurately synchronize lip movements with input audio, they typically ignore…

Computer Vision and Pattern Recognition · Computer Science 2024-06-13 Jiadong Liang , Feng Lu

While considerable progress has been made in achieving accurate lip synchronization for 3D speech-driven talking face generation, the task of incorporating expressive facial detail synthesis aligned with the speaker's speaking status…

Computer Vision and Pattern Recognition · Computer Science 2024-02-27 Yasheng Sun , Wenqing Chu , Hang Zhou , Kaisiyuan Wang , Hideki Koike