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The advent of ChatGPT has introduced innovative methods for information gathering and analysis. However, the information provided by ChatGPT is limited to text, and the visualization of this information remains constrained. Previous…

Computer Vision and Pattern Recognition · Computer Science 2023-08-15 Zhichao Wang , Mengyu Dai , Keld Lundgaard

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

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

We present Free-HeadGAN, a person-generic neural talking head synthesis system. We show that modeling faces with sparse 3D facial landmarks are sufficient for achieving state-of-the-art generative performance, without relying on strong…

Computer Vision and Pattern Recognition · Computer Science 2022-08-04 Michail Christos Doukas , Evangelos Ververas , Viktoriia Sharmanska , Stefanos Zafeiriou

Direct speech-to-speech translation achieves high-quality results through the introduction of discrete units obtained from self-supervised learning. This approach circumvents delays and cascading errors associated with model cascading.…

There are many recent research efforts to fine-tune a pre-trained generator with a few target images to generate images of a novel domain. Unfortunately, these methods often suffer from overfitting or under-fitting when fine-tuned with a…

Computer Vision and Pattern Recognition · Computer Science 2023-01-31 Gihyun Kwon , Jong Chul Ye

Motion transfer of talking-head videos involves generating a new video with the appearance of a subject video and the motion pattern of a driving video. Current methodologies primarily depend on a limited number of subject images and 2D…

Computer Vision and Pattern Recognition · Computer Science 2023-11-07 Haomiao Ni , Jiachen Liu , Yuan Xue , Sharon X. Huang

The narrative quality of a video fundamentally determines its perceptual value. Although existing video generation methods can produce visually appealing content, they predominantly rely on sparse conditioning signals such as text prompts…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Zhida Zhang , Jie Ma , Zhan Peng , Haoxue Wu , Yang Han , Jun Liang , Jie Cao , Jing Li

While dynamic Neural Radiance Fields (NeRF) have shown success in high-fidelity 3D modeling of talking portraits, the slow training and inference speed severely obstruct their potential usage. In this paper, we propose an efficient…

Computer Vision and Pattern Recognition · Computer Science 2022-11-23 Jiaxiang Tang , Kaisiyuan Wang , Hang Zhou , Xiaokang Chen , Dongliang He , Tianshu Hu , Jingtuo Liu , Gang Zeng , Jingdong Wang

Given an audio clip and a reference face image, the goal of the talking head generation is to generate a high-fidelity talking head video. Although some audio-driven methods of generating talking head videos have made some achievements in…

Computer Vision and Pattern Recognition · Computer Science 2023-06-07 Jianrong Wang , Yaxin Zhao , Li Liu , Tianyi Xu , Qi Li , Sen Li

We present a self-supervised speech restoration method without paired speech corpora. Because the previous general speech restoration method uses artificial paired data created by applying various distortions to high-quality speech corpora,…

Talking face generation is a novel and challenging generation task, aiming at synthesizing a vivid speaking-face video given a specific audio. To fulfill emotion-controllable talking face generation, current methods need to overcome two…

Computer Vision and Pattern Recognition · Computer Science 2025-08-21 Ziqi Zhang , Cheng Deng

Over the years, performance evaluation has become essential in computer vision, enabling tangible progress in many sub-fields. While talking-head video generation has become an emerging research topic, existing evaluations on this topic…

Computer Vision and Pattern Recognition · Computer Science 2020-05-08 Lele Chen , Guofeng Cui , Ziyi Kou , Haitian Zheng , Chenliang Xu

This paper introduces Stereo-Talker, a novel one-shot audio-driven human video synthesis system that generates 3D talking videos with precise lip synchronization, expressive body gestures, temporally consistent photo-realistic quality, and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Xiang Deng , Youxin Pang , Xiaochen Zhao , Chao Xu , Lizhen Wang , Hongjiang Xiao , Shi Yan , Hongwen Zhang , Yebin Liu

The goal of face reenactment is to transfer a target expression and head pose to a source face while preserving the source identity. With the popularity of face-related applications, there has been much research on this topic. However, the…

Computer Vision and Pattern Recognition · Computer Science 2022-05-27 Wonjun Kang , Geonsu Lee , Hyung Il Koo , Nam Ik Cho

Recent works on audio-driven talking head synthesis using Neural Radiance Fields (NeRF) have achieved impressive results. However, due to inadequate pose and expression control caused by NeRF implicit representation, these methods still…

Computer Vision and Pattern Recognition · Computer Science 2024-08-12 Hongyun Yu , Zhan Qu , Qihang Yu , Jianchuan Chen , Zhonghua Jiang , Zhiwen Chen , Shengyu Zhang , Jimin Xu , Fei Wu , Chengfei Lv , Gang Yu

Audio-driven portrait animation aims to synthesize portrait videos that are conditioned by given audio. Animating high-fidelity and multimodal video portraits has a variety of applications. Previous methods have attempted to capture…

Computer Vision and Pattern Recognition · Computer Science 2023-07-20 Yunfei Liu , Lijian Lin , Fei Yu , Changyin Zhou , Yu Li

Building realistic and animatable avatars still requires minutes of multi-view or monocular self-rotating videos, and most methods lack precise control over gestures and expressions. To push this boundary, we address the challenge of…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Jun Xiang , Yudong Guo , Leipeng Hu , Boyang Guo , Yancheng Yuan , Juyong Zhang

Researchers have shown a growing interest in Audio-driven Talking Head Generation. The primary challenge in talking head generation is achieving audio-visual coherence between the lips and the audio, known as lip synchronization. This paper…

Sound · Computer Science 2026-02-03 Zhipeng Chen , Xinheng Wang , Lun Xie , Haijie Yuan , Hang Pan

A jump cut offers an abrupt, sometimes unwanted change in the viewing experience. We present a novel framework for smoothing these jump cuts, in the context of talking head videos. We leverage the appearance of the subject from the other…

Computer Vision and Pattern Recognition · Computer Science 2024-01-12 Xiaojuan Wang , Taesung Park , Yang Zhou , Eli Shechtman , Richard Zhang