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While recent advances in deep neural networks have made it possible to render high-quality images, generating photo-realistic and personalized talking head remains challenging. With given audio, the key to tackling this task is…

Computer Vision and Pattern Recognition · Computer Science 2022-01-04 Shunyu Yao , RuiZhe Zhong , Yichao Yan , Guangtao Zhai , Xiaokang Yang

We present a novel one-shot talking head synthesis method that achieves disentangled and fine-grained control over lip motion, eye gaze&blink, head pose, and emotional expression. We represent different motions via disentangled latent…

Computer Vision and Pattern Recognition · Computer Science 2022-11-29 Duomin Wang , Yu Deng , Zixin Yin , Heung-Yeung Shum , Baoyuan Wang

Generating talking face videos from audio attracts lots of research interest. A few person-specific methods can generate vivid videos but require the target speaker's videos for training or fine-tuning. Existing person-generic methods have…

Computer Vision and Pattern Recognition · Computer Science 2023-05-16 Weizhi Zhong , Chaowei Fang , Yinqi Cai , Pengxu Wei , Gangming Zhao , Liang Lin , Guanbin Li

Real-time interactive video-chat portraits have been increasingly recognized as the future trend, particularly due to the remarkable progress made in text and voice chat technologies. However, existing methods primarily focus on real-time…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Jinwei Qi , Chaonan Ji , Sheng Xu , Peng Zhang , Bang Zhang , Liefeng Bo

Recent advancements in diffusion models have significantly improved the realism and generalizability of character-driven animation, enabling the synthesis of high-quality motion from just a single RGB image and a set of driving poses.…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Alireza Javanmardi , Pragati Jaiswal , Tewodros Amberbir Habtegebrial , Christen Millerdurai , Shaoxiang Wang , Alain Pagani , Didier Stricker

We present VideoReTalking, a new system to edit the faces of a real-world talking head video according to input audio, producing a high-quality and lip-syncing output video even with a different emotion. Our system disentangles this…

Computer Vision and Pattern Recognition · Computer Science 2022-11-29 Kun Cheng , Xiaodong Cun , Yong Zhang , Menghan Xia , Fei Yin , Mingrui Zhu , Xuan Wang , Jue Wang , Nannan Wang

The ability to envisage the visual of a talking face based just on hearing a voice is a unique human capability. There have been a number of works that have solved for this ability recently. We differ from these approaches by enabling a…

Computer Vision and Pattern Recognition · Computer Science 2020-11-24 Ravindra Yadav , Ashish Sardana , Vinay P Namboodiri , Rajesh M Hegde

Recent talking avatar generation models have made strides in achieving realistic and accurate lip synchronization with the audio, but often fall short in controlling and conveying detailed expressions and emotions of the avatar, making the…

Computer Vision and Pattern Recognition · Computer Science 2024-05-27 Yuchi Wang , Junliang Guo , Jianhong Bai , Runyi Yu , Tianyu He , Xu Tan , Xu Sun , Jiang Bian

Generating vivid and diverse 3D co-speech gestures is crucial for various applications in animating virtual avatars. While most existing methods can generate gestures from audio directly, they usually overlook that emotion is one of the key…

Computer Vision and Pattern Recognition · Computer Science 2024-01-04 Xingqun Qi , Chen Liu , Lincheng Li , Jie Hou , Haoran Xin , Xin Yu

Generating realistic, dyadic talking head video requires ultra-low latency. Existing chunk-based methods require full non-causal context windows, introducing significant delays. This high latency critically prevents the immediate,…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Bohong Chen , Haiyang Liu

Speech-driven 3D facial animation has advanced rapidly, yet most approaches remain tied to registered template meshes, preventing effective deployment on raw 3D scans with arbitrary topology. At the same time, modeling controllable…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Federico Nocentini , Thomas Besnier , Claudio Ferrari , Stefano Berretti , Mohamed Daoudi

This paper introduces a new model to generate rhythmically relevant non-verbal facial behaviors for virtual agents while they speak. The model demonstrates perceived performance comparable to behaviors directly extracted from the data and…

Computer Vision and Pattern Recognition · Computer Science 2023-11-23 Alice Delbosc , Magalie Ochs , Nicolas Sabouret , Brian Ravenet , Stéphane Ayache

Current talking avatars mostly generate co-speech gestures based on audio and text of the utterance, without considering the non-speaking motion of the speaker. Furthermore, previous works on co-speech gesture generation have designed…

Multimedia · Computer Science 2024-01-09 Sicheng Yang , Zunnan Xu , Haiwei Xue , Yongkang Cheng , Shaoli Huang , Mingming Gong , Zhiyong Wu

Speech-driven animation has gained significant traction in recent years, with current methods achieving near-photorealistic results. However, the field remains underexplored regarding non-verbal communication despite evidence demonstrating…

Computer Vision and Pattern Recognition · Computer Science 2023-08-31 Antoni Bigata Casademunt , Rodrigo Mira , Nikita Drobyshev , Konstantinos Vougioukas , Stavros Petridis , Maja Pantic

We present a novel approach for synthesizing 3D facial motions from audio sequences using key motion embeddings. Despite recent advancements in data-driven techniques, accurately mapping between audio signals and 3D facial meshes remains…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Zhihao Xu , Shengjie Gong , Jiapeng Tang , Lingyu Liang , Yining Huang , Haojie Li , Shuangping Huang

Audio-driven talking head generation aims to create vivid and realistic videos from a static portrait and speech. Existing AR-based methods rely on intermediate facial representations, which limit their expressiveness and realism.…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Yuzhe Weng , Haotian Wang , Yuanhong Yu , Jun Du , Shan He , Xiaoyan Wu , Haoran Xu

Creating realistic, natural, and lip-readable talking face videos remains a formidable challenge. Previous research primarily concentrated on generating and aligning single-frame images while overlooking the smoothness of frame-to-frame…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Shuheng Ge , Haoyu Xing , Li Zhang , Xiangqian Wu

Generating videos of complex human motions such as flips, cartwheels, and martial arts remains challenging for current video diffusion models. Text-only conditioning is temporally ambiguous for fine-grained motion control, while explicit…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Ashkan Taghipour , Morteza Ghahremani , Zinuo Li , Hamid Laga , Farid Boussaid , Mohammed Bennamoun

Achieving disentangled control over multiple facial motions and accommodating diverse input modalities greatly enhances the application and entertainment of the talking head generation. This necessitates a deep exploration of the decoupling…

Computer Vision and Pattern Recognition · Computer Science 2025-08-20 Shuai Tan , Bin Ji

One-shot talking face generation aims at synthesizing a high-quality talking face video from an arbitrary portrait image, driven by a video or an audio segment. One challenging quality factor is the resolution of the output video: higher…

Computer Vision and Pattern Recognition · Computer Science 2022-03-18 Fei Yin , Yong Zhang , Xiaodong Cun , Mingdeng Cao , Yanbo Fan , Xuan Wang , Qingyan Bai , Baoyuan Wu , Jue Wang , Yujiu Yang