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Generating naturalistic and nuanced listener motions for extended interactions remains an open problem. Existing methods often rely on low-dimensional motion codes for facial behavior generation followed by photorealistic rendering,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Maksim Siniukov , Di Chang , Minh Tran , Hongkun Gong , Ashutosh Chaubey , Mohammad Soleymani

Real-time interactive video-chat portraits have been increasingly recognized as the future trend, particularly due to the remarkable progress made in text and voice chat technologies. However, existing methods primarily focus on real-time…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Jinwei Qi , Chaonan Ji , Sheng Xu , Peng Zhang , Bang Zhang , Liefeng Bo

Talking-head generation requires joint modeling of identity, head pose, facial expression, and mouth dynamics. Existing methods typically address only a subset of these factors, and rely on fixed-weight or heuristic fusion when multiple…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Xinyan Ye , Jiankang Deng , Abbas Edalat

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

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

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 human-centric content generation, the pre-trained text-to-image models struggle to produce user-wanted portrait images, which retain the identity of individuals while exhibiting diverse expressions. This paper introduces our efforts…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Renshuai Liu , Bowen Ma , Wei Zhang , Zhipeng Hu , Changjie Fan , Tangjie Lv , Yu Ding , Xuan Cheng

Real-time speech-driven 3D facial animation has been attractive in academia and industry. Traditional methods mainly focus on learning a deterministic mapping from speech to animation. Recent approaches start to consider the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Peng Chen , Xiaobao Wei , Ming Lu , Hui Chen , Feng Tian

For realistic talking head generation, creating natural head motion while maintaining accurate lip synchronization is essential. To fulfill this challenging task, we propose DisCoHead, a novel method to disentangle and control head pose and…

Computer Vision and Pattern Recognition · Computer Science 2023-03-15 Geumbyeol Hwang , Sunwon Hong , Seunghyun Lee , Sungwoo Park , Gyeongsu Chae

One-shot talking face generation aims at synthesizing a high-quality talking face video from an arbitrary portrait image, driven by a video or an audio segment. One challenging quality factor is the resolution of the output video: higher…

Computer Vision and Pattern Recognition · Computer Science 2022-03-18 Fei Yin , Yong Zhang , Xiaodong Cun , Mingdeng Cao , Yanbo Fan , Xuan Wang , Qingyan Bai , Baoyuan Wu , Jue Wang , Yujiu Yang

Recent advances in generative modeling have enabled the generation of high-quality synthetic data that is applicable in a variety of domains, including face recognition. Here, state-of-the-art generative models typically rely on…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Darian Tomašević , Fadi Boutros , Chenhao Lin , Naser Damer , Vitomir Štruc , Peter Peer

Current diffusion-based face animation methods generally adopt a ReferenceNet (a copy of U-Net) and a large amount of curated self-acquired data to learn appearance features, as robust appearance features are vital for ensuring temporal…

Computer Vision and Pattern Recognition · Computer Science 2024-09-24 Yue Han , Junwei Zhu , Yuxiang Feng , Xiaozhong Ji , Keke He , Xiangtai Li , zhucun xue , Yong Liu

Creating content with specified identities (ID) has attracted significant interest in the field of generative models. In the field of text-to-image generation (T2I), subject-driven creation has achieved great progress with the identity…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Ze Ma , Daquan Zhou , Chun-Hsiao Yeh , Xue-She Wang , Xiuyu Li , Huanrui Yang , Zhen Dong , Kurt Keutzer , Jiashi Feng

Long-duration talking video synthesis faces enduring challenges in achieving high video quality, portrait consistency, temporal coherence, and computational efficiency. As video length increases, issues such as visual degradation, portrait…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Haojie Zhang , Zhihao Liang , Ruibo Fu , Bingyan Liu , Zhengqi Wen , Xuefei Liu , Jianhua Tao , Yaling Liang

In this paper, we present a dynamic convolution kernel (DCK) strategy for convolutional neural networks. Using a fully convolutional network with the proposed DCKs, high-quality talking-face video can be generated from multi-modal sources…

Computer Vision and Pattern Recognition · Computer Science 2022-04-20 Zipeng Ye , Mengfei Xia , Ran Yi , Juyong Zhang , Yu-Kun Lai , Xuwei Huang , Guoxin Zhang , Yong-jin Liu

Portrait animation aims to generate photo-realistic videos from a single source image by reenacting the expression and pose from a driving video. While early methods relied on 3D morphable models or feature warping techniques, they often…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Mallikarjun B. R. , Fei Yin , Vikram Voleti , Nikita Drobyshev , Maksim Lapin , Aaryaman Vasishta , Varun Jampani

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

Diffusion models have recently advanced photorealistic human synthesis, although practical talking-head generation (THG) remains constrained by high inference latency, temporal instability such as flicker and identity drift, and imperfect…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Soumya Mazumdar , Vineet Kumar Rakesh

Speech-driven 3D facial animation technology has been developed for years, but its practical application still lacks expectations. The main challenges lie in data limitations, lip alignment, and the naturalness of facial expressions.…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Xiangyu Liang , Wenlin Zhuang , Tianyong Wang , Guangxing Geng , Guangyue Geng , Haifeng Xia , Siyu Xia

We present 3DiFACE, a novel method for personalized speech-driven 3D facial animation and editing. While existing methods deterministically predict facial animations from speech, they overlook the inherent one-to-many relationship between…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Balamurugan Thambiraja , Sadegh Aliakbarian , Darren Cosker , Justus Thies