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Related papers: Audio-Driven Talking Face Video Generation with Jo…

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Face-to-face communication is a common scenario including roles of speakers and listeners. Most existing research methods focus on producing speaker videos, while the generation of listener heads remains largely overlooked. Responsive…

Computer Vision and Pattern Recognition · Computer Science 2023-09-01 Jin Liu , Xi Wang , Xiaomeng Fu , Yesheng Chai , Cai Yu , Jiao Dai , Jizhong Han

Motivated by the success of unsupervised neural machine translation (UNMT), we introduce an unsupervised sign language translation and generation network (USLNet), which learns from abundant single-modality (text and video) data without…

Computation and Language · Computer Science 2024-02-13 Zhengsheng Guo , Zhiwei He , Wenxiang Jiao , Xing Wang , Rui Wang , Kehai Chen , Zhaopeng Tu , Yong Xu , Min Zhang

Creating realistic, natural, and lip-readable talking face videos remains a formidable challenge. Previous research primarily concentrated on generating and aligning single-frame images while overlooking the smoothness of frame-to-frame…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Shuheng Ge , Haoyu Xing , Li Zhang , Xiangqian Wu

This work proposes a novel method to generate realistic talking head videos using audio and visual streams. We animate a source image by transferring head motion from a driving video using a dense motion field generated using learnable…

Computer Vision and Pattern Recognition · Computer Science 2022-10-07 Madhav Agarwal , Rudrabha Mukhopadhyay , Vinay Namboodiri , C V Jawahar

Audio-driven one-shot talking face generation methods are usually trained on video resources of various persons. However, their created videos often suffer unnatural mouth shapes and asynchronous lips because those methods struggle to learn…

Computer Vision and Pattern Recognition · Computer Science 2021-12-07 Suzhen Wang , Lincheng Li , Yu Ding , Xin Yu

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

Talking head generation is to generate video based on a given source identity and target motion. However, current methods face several challenges that limit the quality and controllability of the generated videos. First, the generated face…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Yue Gao , Yuan Zhou , Jinglu Wang , Xiao Li , Xiang Ming , Yan Lu

DeepFake based digital facial forgery is threatening public media security, especially when lip manipulation has been used in talking face generation, and the difficulty of fake video detection is further improved. By only changing lip…

Computer Vision and Pattern Recognition · Computer Science 2023-07-11 Ganglai Wang , Peng Zhang , Junwen Xiong , Feihan Yang , Wei Huang , Yufei Zha

Precise audio-visual synchronization in speech videos is crucial for content quality and viewer comprehension. Existing methods have made significant strides in addressing this challenge through rule-based approaches and end-to-end learning…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Tao Feng , Yifan Xie , Xun Guan , Jiyuan Song , Zhou Liu , Fei Ma , Fei Yu

Recent advances in generative video models have led to significant breakthroughs in high-fidelity video synthesis, specifically in controllable video generation where the generated video is conditioned on text and action inputs, e.g., in…

Computer Vision and Pattern Recognition · Computer Science 2026-03-12 Zhiting Mei , Tenny Yin , Micah Baker , Ola Shorinwa , Anirudha Majumdar

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

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

Generating talking person portraits with arbitrary speech audio is a crucial problem in the field of digital human and metaverse. A modern talking face generation method is expected to achieve the goals of generalized audio-lip…

Computer Vision and Pattern Recognition · Computer Science 2023-05-02 Zhenhui Ye , Jinzheng He , Ziyue Jiang , Rongjie Huang , Jiawei Huang , Jinglin Liu , Yi Ren , Xiang Yin , Zejun Ma , Zhou Zhao

The task of talking head generation is to synthesize a lip synchronized talking head video by inputting an arbitrary face image and audio clips. Most existing methods ignore the local driving information of the mouth muscles. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2021-10-20 Sen Chen , Zhilei Liu , Jiaxing Liu , Zhengxiang Yan , Longbiao 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

When people deliver a speech, they naturally move heads, and this rhythmic head motion conveys prosodic information. However, generating a lip-synced video while moving head naturally is challenging. While remarkably successful, existing…

Computer Vision and Pattern Recognition · Computer Science 2020-07-20 Lele Chen , Guofeng Cui , Celong Liu , Zhong Li , Ziyi Kou , Yi Xu , Chenliang Xu

Deepfake generation has witnessed remarkable progress, contributing to highly realistic generated images, videos, and audio. While technically intriguing, such progress has raised serious concerns related to the misuse of manipulated media.…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Maheswar Bora , Tashvik Dhamija , Shukesh Reddy , Baptiste Chopin , Pranav Balaji , Abhijit Das , Antitza Dantcheva

Whenever we speak, our voice is accompanied by facial movements and expressions. Several recent works have shown the synthesis of highly photo-realistic videos of talking faces, but they either require a source video to drive the target…

Computer Vision and Pattern Recognition · Computer Science 2020-11-03 Prateek Manocha , Prithwijit Guha

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

Generating photo-realistic video portrait with arbitrary speech audio is a crucial problem in film-making and virtual reality. Recently, several works explore the usage of neural radiance field in this task to improve 3D realness and image…

Computer Vision and Pattern Recognition · Computer Science 2023-02-01 Zhenhui Ye , Ziyue Jiang , Yi Ren , Jinglin Liu , JinZheng He , Zhou Zhao