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We propose StyleTalker, a novel audio-driven talking head generation model that can synthesize a video of a talking person from a single reference image with accurately audio-synced lip shapes, realistic head poses, and eye blinks.…

Computer Vision and Pattern Recognition · Computer Science 2024-03-18 Dongchan Min , Minyoung Song , Eunji Ko , Sung Ju Hwang

Understanding the lip movement and inferring the speech from it is notoriously difficult for the common person. The task of accurate lip-reading gets help from various cues of the speaker and its contextual or environmental setting. Every…

Computer Vision and Pattern Recognition · Computer Science 2022-08-23 Munender Varshney , Ravindra Yadav , Vinay P. Namboodiri , Rajesh M Hegde

In this paper, we introduce a novel approach to address the task of synthesizing speech from silent videos of any in-the-wild speaker solely based on lip movements. The traditional approach of directly generating speech from lip videos…

Multimedia · Computer Science 2024-03-05 Sindhu Hegde , Rudrabha Mukhopadhyay , C. V. Jawahar , Vinay Namboodiri

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

Video editing-based talking face generation aims to preserve video details such as pose, lighting, and gestures while modifying only lip motion, often using an identity reference image to maintain speaker consistency. However, this…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Dogucan Yaman , Fevziye Irem Eyiokur , Hazım Kemal Ekenel , Alexander Waibel

Formulated as a conditional generation problem, face animation aims at synthesizing continuous face images from a single source image driven by a set of conditional face motion. Previous works mainly model the face motion as conditions with…

Computer Vision and Pattern Recognition · Computer Science 2022-05-16 Xintian Wu , Qihang Zhang , Yiming Wu , Huanyu Wang , Songyuan Li , Lingyun Sun , Xi Li

In this work, we address the task of unconditional head motion generation to animate still human faces in a low-dimensional semantic space from a single reference pose. Different from traditional audio-conditioned talking head generation…

Computer Vision and Pattern Recognition · Computer Science 2023-04-18 Louis Airale , Xavier Alameda-Pineda , Stéphane Lathuilière , Dominique Vaufreydaz

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

Audio-driven talking head generation is advancing from 2D to 3D content. Notably, Neural Radiance Field (NeRF) is in the spotlight as a means to synthesize high-quality 3D talking head outputs. Unfortunately, this NeRF-based approach…

Computer Vision and Pattern Recognition · Computer Science 2024-05-13 Gihoon Kim , Kwanggyoon Seo , Sihun Cha , Junyong Noh

Recent neural talking radiance field methods have shown great success in photorealistic audio-driven talking face synthesis. In this paper, we propose a novel interactive framework that utilizes human instructions to edit such implicit…

Computer Vision and Pattern Recognition · Computer Science 2023-08-17 Yuqi Sun , Ruian He , Weimin Tan , Bo Yan

Powerful generative adversarial networks (GAN) have been developed to automatically synthesize realistic images from text. However, most existing tasks are limited to generating simple images such as flowers from captions. In this work, we…

Machine Learning · Computer Science 2019-11-27 Osaid Rehman Nasir , Shailesh Kumar Jha , Manraj Singh Grover , Yi Yu , Ajit Kumar , Rajiv Ratn Shah

Synthesizing realistic videos according to a given speech is still an open challenge. Previous works have been plagued by issues such as inaccurate lip shape generation and poor image quality. The key reason is that only motions and…

Computer Vision and Pattern Recognition · Computer Science 2023-09-12 Xiuzhe Wu , Pengfei Hu , Yang Wu , Xiaoyang Lyu , Yan-Pei Cao , Ying Shan , Wenming Yang , Zhongqian Sun , Xiaojuan Qi

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

Text-guided image generation aimed to generate desired images conditioned on given texts, while text-guided image manipulation refers to semantically edit parts of a given image based on specified texts. For these two similar tasks, the key…

Computer Vision and Pattern Recognition · Computer Science 2023-09-22 Xiaozhou You , Jian Zhang

Most methods for conditional video synthesis use a single modality as the condition. This comes with major limitations. For example, it is problematic for a model conditioned on an image to generate a specific motion trajectory desired by…

Computer Vision and Pattern Recognition · Computer Science 2022-03-08 Ligong Han , Jian Ren , Hsin-Ying Lee , Francesco Barbieri , Kyle Olszewski , Shervin Minaee , Dimitris Metaxas , Sergey Tulyakov

In this paper, we present StyleLipSync, a style-based personalized lip-sync video generative model that can generate identity-agnostic lip-synchronizing video from arbitrary audio. To generate a video of arbitrary identities, we leverage…

Computer Vision and Pattern Recognition · Computer Science 2024-02-13 Taekyung Ki , Dongchan Min

In this paper, we propose a novel lip-to-speech generative adversarial network, Visual Context Attentional GAN (VCA-GAN), which can jointly model local and global lip movements during speech synthesis. Specifically, the proposed VCA-GAN…

Computer Vision and Pattern Recognition · Computer Science 2022-04-06 Minsu Kim , Joanna Hong , Yong Man Ro

Recent studies in speech-driven talking face generation achieve promising results, but their reliance on fixed-driven speech limits further applications (e.g., face-voice mismatch). Thus, we extend the task to a more challenging setting:…

Sound · Computer Science 2025-07-28 Fang Kang , Yin Cao , Haoyu Chen

Recently, emotional talking face generation has received considerable attention. However, existing methods only adopt one-hot coding, image, or audio as emotion conditions, thus lacking flexible control in practical applications and failing…

Computer Vision and Pattern Recognition · Computer Science 2023-06-01 Chao Xu , Junwei Zhu , Jiangning Zhang , Yue Han , Wenqing Chu , Ying Tai , Chengjie Wang , Zhifeng Xie , Yong Liu

Conversation is an essential component of virtual avatar activities in the metaverse. With the development of natural language processing, textual and vocal conversation generation has achieved a significant breakthrough. However,…

Computer Vision and Pattern Recognition · Computer Science 2023-08-15 Yichao Yan , Zanwei Zhou , Zi Wang , Jingnan Gao , Xiaokang Yang