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Related papers: UniTalking: A Unified Audio-Video Framework for Ta…

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This work considers merging two independent models, TTS and A2F, into a unified model to enable internal feature transfer, thereby improving the consistency between audio and facial expressions generated from text. We also discuss the…

Sound · Computer Science 2026-03-04 Qiangong Zhou , Nagasaka Tomohiro

This paper investigates a novel task of talking face video generation solely from speeches. The speech-to-video generation technique can spark interesting applications in entertainment, customer service, and human-computer-interaction…

Sound · Computer Science 2021-07-15 Shijing Si , Jianzong Wang , Xiaoyang Qu , Ning Cheng , Wenqi Wei , Xinghua Zhu , Jing Xiao

Speech-driven three-dimensional (3D) facial animation synthesis aims to build a mapping from one-dimensional (1D) speech signals to time-varying 3D facial motion signals. Current methods still face challenges in maintaining lip-sync…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Bin Liu , Zhixiang Xiong , Zhifen He , Bo Li

We present UniModel, a unified generative model that jointly supports visual understanding and visual generation within a single pixel-to-pixel diffusion framework. Our goal is to achieve unification along three axes: the model, the tasks,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Chi Zhang , Jiepeng Wang , Youming Wang , Yuanzhi Liang , Xiaoyan Yang , Zuoxin Li , Haibin Huang , Xuelong Li

Talking face generation aims to create realistic videos with accurate lip synchronization and high visual quality, using given audio and reference video while preserving identity and visual characteristics. In this paper, we start by…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Dogucan Yaman , Fevziye Irem Eyiokur , Leonard Bärmann , Hazim Kemal Ekenel , Alexander Waibel

Talking face generation aims to synthesize a sequence of face images that correspond to a clip of speech. This is a challenging task because face appearance variation and semantics of speech are coupled together in the subtle movements of…

Computer Vision and Pattern Recognition · Computer Science 2019-04-24 Hang Zhou , Yu Liu , Ziwei Liu , Ping Luo , Xiaogang Wang

The task of few-shot visual dubbing focuses on synchronizing the lip movements with arbitrary speech input for any talking head video. Albeit moderate improvements in current approaches, they commonly require high-quality homologous data…

Computer Vision and Pattern Recognition · Computer Science 2022-01-19 Tianyi Xie , Liucheng Liao , Cheng Bi , Benlai Tang , Xiang Yin , Jianfei Yang , Mingjie Wang , Jiali Yao , Yang Zhang , Zejun Ma

Audio-driven talking video generation has advanced significantly, but existing methods often depend on video-to-video translation techniques and traditional generative networks like GANs and they typically generate taking heads and…

Computer Vision and Pattern Recognition · Computer Science 2024-09-13 Steven Hogue , Chenxu Zhang , Hamza Daruger , Yapeng Tian , Xiaohu Guo

Text-to-speech (TTS) and singing voice synthesis (SVS) aim at generating high-quality speaking and singing voice according to textual input and music scores, respectively. Unifying TTS and SVS into a single system is crucial to the…

Sound · Computer Science 2022-12-07 Yi Lei , Shan Yang , Xinsheng Wang , Qicong Xie , Jixun Yao , Lei Xie , Dan Su

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

We study two foundational problems in audio language models: (1) how to design an audio tokenizer that can serve as an intermediate representation for both understanding and generation; and (2) how to build an audio foundation model that…

Sound · Computer Science 2026-02-12 Dongchao Yang , Yuanyuan Wang , Dading Chong , Songxiang Liu , Xixin Wu , Helen Meng

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

Current generative video models excel at producing novel content from text and image prompts, but leave a critical gap in editing existing pre-recorded videos, where minor alterations to the spoken script require preserving motion, temporal…

Computer Vision and Pattern Recognition · Computer Science 2026-01-30 John Flynn , Wolfgang Paier , Dimitar Dinev , Sam Nhut Nguyen , Hayk Poghosyan , Manuel Toribio , Sandipan Banerjee , Guy Gafni

In this paper, we introduce V2SFlow, a novel Video-to-Speech (V2S) framework designed to generate natural and intelligible speech directly from silent talking face videos. While recent V2S systems have shown promising results on constrained…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 Jeongsoo Choi , Ji-Hoon Kim , Jinyu Li , Joon Son Chung , Shujie Liu

Recent breakthroughs in video AIGC have ushered in a transformative era for audio-driven human animation. However, conventional video dubbing techniques remain constrained to mouth region editing, resulting in discordant facial expressions…

Computer Vision and Pattern Recognition · Computer Science 2025-08-20 Shaoshu Yang , Zhe Kong , Feng Gao , Meng Cheng , Xiangyu Liu , Yong Zhang , Zhuoliang Kang , Wenhan Luo , Xunliang Cai , Ran He , Xiaoming Wei

Current unified multimodal models typically rely on discrete visual tokenizers to bridge the modality gap. However, discretization inevitably discards fine-grained semantic information, leading to suboptimal performance in visual…

Computer Vision and Pattern Recognition · Computer Science 2026-03-12 Yaqi Zhao , Wang Lin , Zijian Zhang , Miles Yang , Jingyuan Chen , Wentao Zhang , Zhao Zhong , Liefeng Bo

In this paper, we consider a novel and practical case for talking face video generation. Specifically, we focus on the scenarios involving multi-people interactions, where the talking context, such as audience or surroundings, is present.…

Computer Vision and Pattern Recognition · Computer Science 2024-02-29 Meidai Xuanyuan , Yuwang Wang , Honglei Guo , Qionghai Dai

While accurate lip synchronization has been achieved for arbitrary-subject audio-driven talking face generation, the problem of how to efficiently drive the head pose remains. Previous methods rely on pre-estimated structural information…

Computer Vision and Pattern Recognition · Computer Science 2021-04-23 Hang Zhou , Yasheng Sun , Wayne Wu , Chen Change Loy , Xiaogang Wang , Ziwei Liu

Controllable human voice generation, particularly for expressive domains like singing, remains a significant challenge. This paper introduces Vevo2, a unified framework for controllable speech and singing voice generation. To tackle issues…

Pre-training models have been proved effective for a wide range of natural language processing tasks. Inspired by this, we propose a novel dialogue generation pre-training framework to support various kinds of conversations, including…

Computation and Language · Computer Science 2020-05-01 Siqi Bao , Huang He , Fan Wang , Hua Wu , Haifeng Wang
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