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This paper proposes a talking face generation method named "CP-EB" that takes an audio signal as input and a person image as reference, to synthesize a photo-realistic people talking video with head poses controlled by a short video clip…

Computer Vision and Pattern Recognition · Computer Science 2023-11-16 Jianzong Wang , Yimin Deng , Ziqi Liang , Xulong Zhang , Ning Cheng , Jing Xiao

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

Generating synchronized and natural lip movement with speech is one of the most important tasks in creating realistic virtual characters. In this paper, we present a combined deep neural network of one-dimensional convolutions and LSTM to…

Sound · Computer Science 2022-05-03 Xiaohong Li , Xiang Wang , Kai Wang , Shiguo Lian

Audio-driven talking face generation, which aims to synthesize talking faces with realistic facial animations (including accurate lip movements, vivid facial expression details and natural head poses) corresponding to the audio, has…

Computer Vision and Pattern Recognition · Computer Science 2023-04-19 Rongliang Wu , Yingchen Yu , Fangneng Zhan , Jiahui Zhang , Xiaoqin Zhang , Shijian Lu

In this paper, we propose a neural end-to-end system for voice preserving, lip-synchronous translation of videos. The system is designed to combine multiple component models and produces a video of the original speaker speaking in the…

Previous studies have explored generating accurately lip-synced talking faces for arbitrary targets given audio conditions. However, most of them deform or generate the whole facial area, leading to non-realistic results. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2022-12-12 Yasheng Sun , Hang Zhou , Kaisiyuan Wang , Qianyi Wu , Zhibin Hong , Jingtuo Liu , Errui Ding , Jingdong Wang , Ziwei Liu , Hideki Koike

Existing lip-sync deepfake detectors rely on pixel artifacts or audio-visual correspondence, and both fail under generator or language shift because the features they learn are tied to the training distribution. We take a different…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Hao Chen , Junnan Xu

Speech-driven facial animation methods usually contain two main classes, 3D and 2D talking face, both of which attract considerable research attention in recent years. However, to the best of our knowledge, the research on 3D talking face…

Computer Vision and Pattern Recognition · Computer Science 2024-04-22 Yixiang Zhuang , Baoping Cheng , Yao Cheng , Yuntao Jin , Renshuai Liu , Chengyang Li , Xuan Cheng , Jing Liao , Juncong Lin

End-to-end audio-conditioned latent diffusion models (LDMs) have been widely adopted for audio-driven portrait animation, demonstrating their effectiveness in generating lifelike and high-resolution talking videos. However, direct…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Chunyu Li , Chao Zhang , Weikai Xu , Jingyu Lin , Jinghui Xie , Weiguo Feng , Bingyue Peng , Cunjian Chen , Weiwei Xing

Audio-driven emotional 3D facial animation aims to generate synchronized lip movements and vivid facial expressions. However, most existing approaches focus on static and predefined emotion labels, limiting their diversity and naturalness.…

Computer Vision and Pattern Recognition · Computer Science 2025-08-15 Chang Liu , Ye Pan , Chenyang Ding , Susanto Rahardja , Xiaokang Yang

Audio-driven talking head generation is a significant and challenging task applicable to various fields such as virtual avatars, film production, and online conferences. However, the existing GAN-based models emphasize generating…

Computer Vision and Pattern Recognition · Computer Science 2024-08-06 Jintao Tan , Xize Cheng , Lingyu Xiong , Lei Zhu , Xiandong Li , Xianjia Wu , Kai Gong , Minglei Li , Yi Cai

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

Implementing fine-grained emotion control is crucial for emotion generation tasks because it enhances the expressive capability of the generative model, allowing it to accurately and comprehensively capture and express various nuanced…

Computer Vision and Pattern Recognition · Computer Science 2024-02-05 Guanwen Feng , Haoran Cheng , Yunan Li , Zhiyuan Ma , Chaoneng Li , Zhihao Qian , Qiguang Miao , Chi-Man Pun

Talking face generation is the challenging task of synthesizing a natural and realistic face that requires accurate synchronization with a given audio. Due to co-articulation, where an isolated phone is influenced by the preceding or…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Se Jin Park , Minsu Kim , Jeongsoo Choi , Yong Man Ro

Although current deep learning-based face forgery detectors achieve impressive performance in constrained scenarios, they are vulnerable to samples created by unseen manipulation methods. Some recent works show improvements in…

Computer Vision and Pattern Recognition · Computer Science 2021-08-17 Alexandros Haliassos , Konstantinos Vougioukas , Stavros Petridis , Maja Pantic

Automatic lip-reading (ALR) aims to automatically transcribe spoken content from a speaker's silent lip motion captured in video. Current mainstream lip-reading approaches only use a single visual encoder to model input videos of a single…

Computer Vision and Pattern Recognition · Computer Science 2024-05-01 He Wang , Pengcheng Guo , Xucheng Wan , Huan Zhou , Lei Xie

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

Humans are able to imagine a person's voice from the person's appearance and imagine the person's appearance from his/her voice. In this paper, we make the first attempt to develop a method that can convert speech into a voice that matches…

Sound · Computer Science 2019-04-10 Hirokazu Kameoka , Kou Tanaka , Aaron Valero Puche , Yasunori Ohishi , Takuhiro Kaneko

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.…

Audio-driven lip sync has recently drawn significant attention due to its widespread application in the multimedia domain. Individuals exhibit distinct lip shapes when speaking the same utterance, attributed to the unique speaking styles of…

Computer Vision and Pattern Recognition · Computer Science 2025-06-19 Weizhi Zhong , Jichang Li , Yinqi Cai , Ming Li , Feng Gao , Liang Lin , Guanbin Li
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