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Significant progress has been made in audio-driven human animation, while most existing methods focus mainly on facial movements, limiting their ability to create full-body animations with natural synchronization and fluidity. They also…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Qijun Gan , Ruizi Yang , Jianke Zhu , Shaofei Xue , Steven Hoi

We present a method that generates expressive talking heads from a single facial image with audio as the only input. In contrast to previous approaches that attempt to learn direct mappings from audio to raw pixels or points for creating…

Computer Vision and Pattern Recognition · Computer Science 2021-02-26 Yang Zhou , Xintong Han , Eli Shechtman , Jose Echevarria , Evangelos Kalogerakis , Dingzeyu Li

Current talking-head generation has gradually shifted from GAN-based methods to diffusion-based paradigms, achieving remarkable progress in visual fidelity and temporal consistency. However, inter-frame flicker remains prevalent in existing…

Computer Vision and Pattern Recognition · Computer Science 2026-04-22 Yuchen Deng , Xiuyang Wu , Hai-Tao Zheng , Suiyang Zhang , Yi He , Yuxing Han

Emotional Talking Face synthesis is pivotal in multimedia and signal processing, yet existing 3D methods suffer from two critical challenges: poor audio-vision emotion alignment, manifested as difficult audio emotion extraction and…

Artificial Intelligence · Computer Science 2026-01-28 Nanhan Shen , Zhilei Liu

Talking head synthesis has emerged as a prominent research topic in computer graphics and multimedia, yet most existing methods often struggle to strike a balance between generation quality and computational efficiency, particularly under…

Graphics · Computer Science 2025-06-30 Shuai Shen , Wanhua Li , Yunpeng Zhang , Yap-Peng Tan , Jiwen Lu

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

Current co-speech motion generation approaches usually focus on upper body gestures following speech contents only, while lacking supporting the elaborate control of synergistic full-body motion based on text prompts, such as talking while…

Computer Vision and Pattern Recognition · Computer Science 2024-10-02 Bohong Chen , Yumeng Li , Yao-Xiang Ding , Tianjia Shao , Kun Zhou

In this work, we introduce the first autoregressive framework for real-time, audio-driven portrait animation, a.k.a, talking head. Beyond the challenge of lengthy animation times, a critical challenge in realistic talking head generation…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Dingcheng Zhen , Shunshun Yin , Shiyang Qin , Hou Yi , Ziwei Zhang , Siyuan Liu , Gan Qi , Ming Tao

Recently, 2D speaking avatars have increasingly participated in everyday scenarios due to the fast development of facial animation techniques. However, most existing works neglect the explicit control of human bodies. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Jiazhi Guan , Quanwei Yang , Kaisiyuan Wang , Hang Zhou , Shengyi He , Zhiliang Xu , Haocheng Feng , Errui Ding , Jingdong Wang , Hongtao Xie , Youjian Zhao , Ziwei Liu

Recently, talking-face video generation has received considerable attention. So far most methods generate results with neutral expressions or expressions that are implicitly determined by neural networks in an uncontrollable way. In this…

Computer Vision and Pattern Recognition · Computer Science 2022-04-14 Zipeng Ye , Zhiyao Sun , Yu-Hui Wen , Yanan Sun , Tian Lv , Ran Yi , Yong-Jin Liu

In this paper, we present a dynamic convolution kernel (DCK) strategy for convolutional neural networks. Using a fully convolutional network with the proposed DCKs, high-quality talking-face video can be generated from multi-modal sources…

Computer Vision and Pattern Recognition · Computer Science 2022-04-20 Zipeng Ye , Mengfei Xia , Ran Yi , Juyong Zhang , Yu-Kun Lai , Xuwei Huang , Guoxin Zhang , Yong-jin Liu

The ability to create realistic, animatable and relightable head avatars from casual video sequences would open up wide ranging applications in communication and entertainment. Current methods either build on explicit 3D morphable meshes…

Computer Vision and Pattern Recognition · Computer Science 2023-03-01 Yufeng Zheng , Wang Yifan , Gordon Wetzstein , Michael J. Black , Otmar Hilliges

Generating 3D speech-driven talking head has received more and more attention in recent years. Recent approaches mainly have following limitations: 1) most speaker-independent methods need handcrafted features that are time-consuming to…

Audio and Speech Processing · Electrical Eng. & Systems 2020-06-23 Huirong Huang , Zhiyong Wu , Shiyin Kang , Dongyang Dai , Jia Jia , Tianxiao Fu , Deyi Tuo , Guangzhi Lei , Peng Liu , Dan Su , Dong Yu , Helen Meng

This work proposes a novel method to generate realistic talking head videos using audio and visual streams. We animate a source image by transferring head motion from a driving video using a dense motion field generated using learnable…

Computer Vision and Pattern Recognition · Computer Science 2022-10-07 Madhav Agarwal , Rudrabha Mukhopadhyay , Vinay Namboodiri , C V Jawahar

Generating realistic human motions that naturally respond to both spoken language and physical objects is crucial for interactive digital experiences. Current methods, however, address speech-driven gestures or object interactions…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Sreehari Rajan , Kunal Bhosikar , Charu Sharma

Talking head generation intends to produce vivid and realistic talking head videos from a single portrait and speech audio clip. Although significant progress has been made in diffusion-based talking head generation, almost all methods rely…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Hanbo Cheng , Limin Lin , Chenyu Liu , Pengcheng Xia , Pengfei Hu , Jiefeng Ma , Jun Du , Jia Pan

Text-to-motion generation is a crucial task in computer vision, which generates the target 3D motion by the given text. The existing annotated datasets are limited in scale, resulting in most existing methods overfitting to the small…

Computer Vision and Pattern Recognition · Computer Science 2024-11-07 Ke Fan , Jiangning Zhang , Ran Yi , Jingyu Gong , Yabiao Wang , Yating Wang , Xin Tan , Chengjie Wang , Lizhuang Ma

Recent advances in audio-driven portrait animation have demonstrated impressive capabilities. However, existing methods struggle to align with fine-grained human preferences across multiple dimensions, such as motion naturalness, lip-sync…

Computer Vision and Pattern Recognition · Computer Science 2025-08-18 MengChao Wang , Qiang Wang , Fan Jiang , Mu Xu

Speech-driven 3D facial animation has garnered lots of attention thanks to its broad range of applications. Despite recent advancements in achieving realistic lip motion, current methods fail to capture the nuanced emotional undertones…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Jisoo Kim , Jungbin Cho , Joonho Park , Soonmin Hwang , Da Eun Kim , Geon Kim , Youngjae Yu

Recent advances in video diffusion models have unlocked new potential for realistic audio-driven talking video generation. However, achieving seamless audio-lip synchronization, maintaining long-term identity consistency, and producing…

Computer Vision and Pattern Recognition · Computer Science 2024-12-06 Longtao Zheng , Yifan Zhang , Hanzhong Guo , Jiachun Pan , Zhenxiong Tan , Jiahao Lu , Chuanxin Tang , Bo An , Shuicheng Yan
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