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Video generation has achieved remarkable progress, with generated videos increasingly resembling real ones. However, the rapid advance in generation has outpaced the development of adequate evaluation metrics. Currently, the assessment of…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Nabyl Quignon , Baptiste Chopin , Yaohui Wang , Antitza Dantcheva

The one-shot talking-head synthesis task aims to animate a source image to another pose and expression, which is dictated by a driving frame. Recent methods rely on warping the appearance feature extracted from the source, by using motion…

Computer Vision and Pattern Recognition · Computer Science 2023-05-01 Kangning Liu , Yu-Chuan Su , Wei , Hong , Ruijin Cang , Xuhui Jia

In this paper, we present our method for neural face reenactment, called HyperReenact, that aims to generate realistic talking head images of a source identity, driven by a target facial pose. Existing state-of-the-art face reenactment…

Computer Vision and Pattern Recognition · Computer Science 2023-07-21 Stella Bounareli , Christos Tzelepis , Vasileios Argyriou , Ioannis Patras , Georgios Tzimiropoulos

In this paper, we present StyleLipSync, a style-based personalized lip-sync video generative model that can generate identity-agnostic lip-synchronizing video from arbitrary audio. To generate a video of arbitrary identities, we leverage…

Computer Vision and Pattern Recognition · Computer Science 2024-02-13 Taekyung Ki , Dongchan Min

Video-to-video synthesis is a challenging problem aiming at learning a translation function between a sequence of semantic maps and a photo-realistic video depicting the characteristics of a driving video. We propose a head-to-head system…

Computer Vision and Pattern Recognition · Computer Science 2020-06-19 Mohammad Rami Koujan , Michail Christos Doukas , Anastasios Roussos , Stefanos Zafeiriou

The field of portrait image animation, driven by speech audio input, has experienced significant advancements in the generation of realistic and dynamic portraits. This research delves into the complexities of synchronizing facial movements…

Computer Vision and Pattern Recognition · Computer Science 2024-06-18 Mingwang Xu , Hui Li , Qingkun Su , Hanlin Shang , Liwei Zhang , Ce Liu , Jingdong Wang , Yao Yao , Siyu Zhu

Audio-driven talking face video generation has attracted increasing attention due to its huge industrial potential. Some previous methods focus on learning a direct mapping from audio to visual content. Despite progress, they often struggle…

Computer Vision and Pattern Recognition · Computer Science 2024-08-13 Weizhi Zhong , Junfan Lin , Peixin Chen , Liang Lin , Guanbin Li

The rapid advancement of talking-head deepfake generation fueled by advanced generative models has elevated the realism of synthetic videos to a level that poses substantial risks in domains such as media, politics, and finance. However,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Xinqi Xiong , Prakrut Patel , Qingyuan Fan , Amisha Wadhwa , Sarathy Selvam , Xiao Guo , Luchao Qi , Xiaoming Liu , Roni Sengupta

Current co-speech motion generation approaches usually focus on upper body gestures following speech contents only, while lacking supporting the elaborate control of synergistic full-body motion based on text prompts, such as talking while…

Computer Vision and Pattern Recognition · Computer Science 2024-10-02 Bohong Chen , Yumeng Li , Yao-Xiang Ding , Tianjia Shao , Kun Zhou

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

Talking face generation has a wide range of potential applications in the field of virtual digital humans. However, rendering high-fidelity facial video while ensuring lip synchronization is still a challenge for existing audio-driven…

Computer Vision and Pattern Recognition · Computer Science 2023-10-17 Yaosen Chen , Yu Yao , Zhiqiang Li , Wei Wang , Yanru Zhang , Han Yang , Xuming Wen

Generating talking head videos through a face image and a piece of speech audio still contains many challenges. ie, unnatural head movement, distorted expression, and identity modification. We argue that these issues are mainly because of…

Computer Vision and Pattern Recognition · Computer Science 2023-03-14 Wenxuan Zhang , Xiaodong Cun , Xuan Wang , Yong Zhang , Xi Shen , Yu Guo , Ying Shan , Fei Wang

With the recent success of deep neural networks, remarkable progress has been achieved on face recognition. However, collecting large-scale real-world training data for face recognition has turned out to be challenging, especially due to…

Computer Vision and Pattern Recognition · Computer Science 2021-12-06 Haibo Qiu , Baosheng Yu , Dihong Gong , Zhifeng Li , Wei Liu , Dacheng Tao

In this paper, we introduce a simple and novel framework for one-shot audio-driven talking head generation. Unlike prior works that require additional driving sources for controlled synthesis in a deterministic manner, we instead…

Graphics · Computer Science 2022-12-09 Zhentao Yu , Zixin Yin , Deyu Zhou , Duomin Wang , Finn Wong , Baoyuan Wang

Talking face generation with great practical significance has attracted more attention in recent audio-visual studies. How to achieve accurate lip synchronization is a long-standing challenge to be further investigated. Motivated by xxx, in…

Computer Vision and Pattern Recognition · Computer Science 2022-04-12 Ganglai Wang , Peng Zhang , Lei Xie , Wei Huang , Yufei Zha

Recent advances in diffusion models have led to significant progress in audio-driven lip synchronization. However, existing methods typically rely on constrained audio-visual alignment priors or multi-stage learning of intermediate…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Junxian Ma , Shiwen Wang , Jian Yang , Junyi Hu , Jian Liang , Guosheng Lin , Jingbo chen , Kai Li , Yu Meng

Although existing speech-driven talking face generation methods achieve significant progress, they are far from real-world application due to the avatar-specific training demand and unstable lip movements. To address the above issues, we…

Computer Vision and Pattern Recognition · Computer Science 2023-12-13 Haiming Zhang , Zhihao Yuan , Chaoda Zheng , Xu Yan , Baoyuan Wang , Guanbin Li , Song Wu , Shuguang Cui , Zhen Li

Recent studies in speech-driven 3D talking head generation have achieved convincing results in verbal articulations. However, generating accurate lip-syncs degrades when applied to input speech in other languages, possibly due to the lack…

Computer Vision and Pattern Recognition · Computer Science 2024-06-21 Kim Sung-Bin , Lee Chae-Yeon , Gihun Son , Oh Hyun-Bin , Janghoon Ju , Suekyeong Nam , Tae-Hyun Oh

We propose a novel talking head synthesis pipeline called "DiT-Head", which is based on diffusion transformers and uses audio as a condition to drive the denoising process of a diffusion model. Our method is scalable and can generalise to…

Artificial Intelligence · Computer Science 2023-12-12 Aaron Mir , Eduardo Alonso , Esther Mondragón

We tackle the challenging task of generating complete 3D facial animations for two interacting, co-located participants from a mixed audio stream. While existing methods often produce disembodied "talking heads" akin to a video conference…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Mengyi Shan , Shouchieh Chang , Ziqian Bai , Shichen Liu , Yinda Zhang , Luchuan Song , Rohit Pandey , Sean Fanello , Zeng Huang