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Related papers: Everybody's Talkin': Let Me Talk as You Want

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To the best of our knowledge, we first present a live system that generates personalized photorealistic talking-head animation only driven by audio signals at over 30 fps. Our system contains three stages. The first stage is a deep neural…

Graphics · Computer Science 2021-09-27 Yuanxun Lu , Jinxiang Chai , Xun Cao

We present a novel approach that enables photo-realistic re-animation of portrait videos using only an input video. In contrast to existing approaches that are restricted to manipulations of facial expressions only, we are the first to…

Computer Vision and Pattern Recognition · Computer Science 2018-05-31 Hyeongwoo Kim , Pablo Garrido , Ayush Tewari , Weipeng Xu , Justus Thies , Matthias Nießner , Patrick Pérez , Christian Richardt , Michael Zollhöfer , Christian Theobalt

One-shot 3D talking portrait generation aims to reconstruct a 3D avatar from an unseen image, and then animate it with a reference video or audio to generate a talking portrait video. The existing methods fail to simultaneously achieve the…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Zhenhui Ye , Tianyun Zhong , Yi Ren , Jiaqi Yang , Weichuang Li , Jiawei Huang , Ziyue Jiang , Jinzheng He , Rongjie Huang , Jinglin Liu , Chen Zhang , Xiang Yin , Zejun Ma , Zhou Zhao

Creating a realistic animatable avatar from a single static portrait remains challenging. Existing approaches often struggle to capture subtle facial expressions, the associated global body movements, and the dynamic background. To address…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Mengchao Wang , Qiang Wang , Fan Jiang , Yaqi Fan , Yunpeng Zhang , Yonggang Qi , Kun Zhao , Mu Xu

Real-world talking faces often accompany with natural head movement. However, most existing talking face video generation methods only consider facial animation with fixed head pose. In this paper, we address this problem by proposing a…

Computer Vision and Pattern Recognition · Computer Science 2020-03-06 Ran Yi , Zipeng Ye , Juyong Zhang , Hujun Bao , Yong-Jin Liu

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

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

Audio-driven talking face generation is a challenging task in digital communication. Despite significant progress in the area, most existing methods concentrate on audio-lip synchronization, often overlooking aspects such as visual quality,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-02 Fatemeh Nazarieh , Zhenhua Feng , Diptesh Kanojia , Muhammad Awais , Josef Kittler

Portrait video editing focuses on modifying specific attributes of portrait videos, guided by audio or video streams. Previous methods typically either concentrate on lip-region reenactment or require training specialized models to extract…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Tianrui Pan , Lin Liu , Jie Liu , Xiaopeng Zhang , Jie Tang , Gangshan Wu , Qi Tian

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

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

Editing talking-head video to change the speech content or to remove filler words is challenging. We propose a novel method to edit talking-head video based on its transcript to produce a realistic output video in which the dialogue of the…

Computer Vision and Pattern Recognition · Computer Science 2019-06-05 Ohad Fried , Ayush Tewari , Michael Zollhöfer , Adam Finkelstein , Eli Shechtman , Dan B Goldman , Kyle Genova , Zeyu Jin , Christian Theobalt , Maneesh Agrawala

In this study, we propose AniPortrait, a novel framework for generating high-quality animation driven by audio and a reference portrait image. Our methodology is divided into two stages. Initially, we extract 3D intermediate representations…

Computer Vision and Pattern Recognition · Computer Science 2024-03-27 Huawei Wei , Zejun Yang , Zhisheng Wang

How much can we infer about a person's looks from the way they speak? In this paper, we study the task of reconstructing a facial image of a person from a short audio recording of that person speaking. We design and train a deep neural…

Computer Vision and Pattern Recognition · Computer Science 2019-05-24 Tae-Hyun Oh , Tali Dekel , Changil Kim , Inbar Mosseri , William T. Freeman , Michael Rubinstein , Wojciech Matusik

Recent methods for audio-driven talking head synthesis often optimize neural radiance fields (NeRF) on a monocular talking portrait video, leveraging its capability to render high-fidelity and 3D-consistent novel-view frames. However, they…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Jaehoon Ko , Kyusun Cho , Joungbin Lee , Heeji Yoon , Sangmin Lee , Sangjun Ahn , Seungryong Kim

We propose a method for synthesizing photo-realistic digital avatars from only one portrait as the reference. Given a portrait, our method synthesizes a coarse talking head video using driving keypoints features. And with the coarse video,…

Computer Vision and Pattern Recognition · Computer Science 2023-07-20 Shaoxu Li

Automatically generating videos in which synthesized speech is synchronized with lip movements in a talking head has great potential in many human-computer interaction scenarios. In this paper, we present an automatic method to generate…

Computer Vision and Pattern Recognition · Computer Science 2021-08-29 Xinsheng Wang , Qicong Xie , Jihua Zhu , Lei Xie , Scharenborg

This paper presents a simple method for "do as I do" motion transfer: given a source video of a person dancing, we can transfer that performance to a novel (amateur) target after only a few minutes of the target subject performing standard…

Graphics · Computer Science 2019-08-29 Caroline Chan , Shiry Ginosar , Tinghui Zhou , Alexei A. Efros

We present a framework for generating full-bodied photorealistic avatars that gesture according to the conversational dynamics of a dyadic interaction. Given speech audio, we output multiple possibilities of gestural motion for an…

Computer Vision and Pattern Recognition · Computer Science 2024-01-04 Evonne Ng , Javier Romero , Timur Bagautdinov , Shaojie Bai , Trevor Darrell , Angjoo Kanazawa , Alexander Richard

The one-shot talking-head generation learns to synthesize a talking-head video with one source portrait image under the driving of same or different identity video. Usually these methods require plane-based pixel transformations via Jacobin…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Luchuan Song , Pinxin Liu , Guojun Yin , Chenliang Xu
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