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Talking head generation creates lifelike avatars from static portraits for virtual communication and content creation. However, current models do not yet convey the feeling of truly interactive communication, often generating one-way…

Machine Learning · Computer Science 2026-01-05 Taekyung Ki , Sangwon Jang , Jaehyeong Jo , Jaehong Yoon , Sung Ju Hwang

The task of audio-driven portrait animation involves generating a talking head video using an identity image and an audio track of speech. While many existing approaches focus on lip synchronization and video quality, few tackle the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Jian Zhang , Weijian Mai , Zhijun Zhang

Diffusion models have shown impressive potential on talking head generation. While plausible appearance and talking effect are achieved, these methods still suffer from temporal, 3D or expression inconsistency due to the error accumulation…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Haijie Yang , Zhenyu Zhang , Hao Tang , Jianjun Qian , Jian Yang

Human conversation involves continuous exchanges of speech and nonverbal cues such as head nods, gaze shifts, and facial expressions that convey attention and emotion. Modeling these bidirectional dynamics in 3D is essential for building…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Junjie Chen , Fei Wang , Zhihao Huang , Qing Zhou , Kun Li , Dan Guo , Linfeng Zhang , Xun Yang

In this paper, we propose a novel text-based talking-head video generation framework that synthesizes high-fidelity facial expressions and head motions in accordance with contextual sentiments as well as speech rhythm and pauses. To be…

Computer Vision and Pattern Recognition · Computer Science 2021-05-10 Lincheng Li , Suzhen Wang , Zhimeng Zhang , Yu Ding , Yixing Zheng , Xin Yu , Changjie Fan

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

Despite the significant progress in recent years, very few of the AI-based talking face generation methods attempt to render natural emotions. Moreover, the scope of the methods is majorly limited to the characteristics of the training…

Computer Vision and Pattern Recognition · Computer Science 2022-05-04 Sanjana Sinha , Sandika Biswas , Ravindra Yadav , Brojeshwar Bhowmick

We present EmbodiedHead, a speech-driven talking-head framework that equips LLMs with real-time visual avatars for conversation. A practical embodied avatar must achieve real-time generation, unified listening-speaking behavior, and high…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Yu Zhang , Kaiyuan Shen , Yang Li

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

Multimodal-driven talking face generation refers to animating a portrait with the given pose, expression, and gaze transferred from the driving image and video, or estimated from the text and audio. However, existing methods ignore the…

Computer Vision and Pattern Recognition · Computer Science 2023-05-10 Chao Xu , Shaoting Zhu , Junwei Zhu , Tianxin Huang , Jiangning Zhang , Ying Tai , Yong Liu

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

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

Diffusion models have revolutionized the field of talking head generation, yet still face challenges in expressiveness, controllability, and stability in long-time generation. In this research, we propose an EmotiveTalk framework to address…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Haotian Wang , Yuzhe Weng , Yueyan Li , Zilu Guo , Jun Du , Shutong Niu , Jiefeng Ma , Shan He , Xiaoyan Wu , Qiming Hu , Bing Yin , Cong Liu , Qingfeng Liu

A key component of dyadic spoken interactions is the contextually relevant non-verbal gestures, such as head movements that reflect a listener's response to the interlocutor's speech. Although significant progress has been made in the…

Robotics · Computer Science 2024-10-01 Bishal Ghosh , Emma Li , Tanaya Guha

In this paper, we propose a novel audio-driven talking head method capable of simultaneously generating highly expressive facial expressions and hand gestures. Unlike existing methods that focus on generating full-body or half-body poses,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 Linrui Tian , Siqi Hu , Qi Wang , Bang Zhang , Liefeng Bo

Emotional talking head generation has attracted growing attention. Previous methods, which are mainly GAN-based, still struggle to consistently produce satisfactory results across diverse emotions and cannot conveniently specify…

Computer Vision and Pattern Recognition · Computer Science 2024-08-13 Yifeng Ma , Shiwei Zhang , Jiayu Wang , Xiang Wang , Yingya Zhang , Zhidong Deng

Laughter is a unique expression, essential to affirmative social interactions of humans. Although current 3D talking head generation methods produce convincing verbal articulations, they often fail to capture the vitality and subtleties of…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Kim Sung-Bin , Lee Hyun , Da Hye Hong , Suekyeong Nam , Janghoon Ju , Tae-Hyun Oh

Human emotional expression is inherently dynamic, complex, and fluid, characterized by smooth transitions in intensity throughout verbal communication. However, the modeling of such intensity fluctuations has been largely overlooked by…

Sound · Computer Science 2024-10-01 Jingyi Xu , Hieu Le , Zhixin Shu , Yang Wang , Yi-Hsuan Tsai , Dimitris Samaras

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

Audio-driven talking-head synthesis is a popular research topic for virtual human-related applications. However, the inflexibility and inefficiency of existing methods, which necessitate expensive end-to-end training to transfer emotions…

Sound · Computer Science 2023-10-13 Yuan Gan , Zongxin Yang , Xihang Yue , Lingyun Sun , Yi Yang
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