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We introduce PortraitGen, a powerful portrait video editing method that achieves consistent and expressive stylization with multimodal prompts. Traditional portrait video editing methods often struggle with 3D and temporal consistency, and…

Computer Vision and Pattern Recognition · Computer Science 2024-09-23 Xuan Gao , Haiyao Xiao , Chenglai Zhong , Shimin Hu , Yudong Guo , Juyong Zhang

While recent research has made significant progress in speech-driven talking face generation, the quality of the generated video still lags behind that of real recordings. One reason for this is the use of handcrafted intermediate…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Chenpeng Du , Qi Chen , Tianyu He , Xu Tan , Xie Chen , Kai Yu , Sheng Zhao , Jiang Bian

Different forms of customized 2D avatars are widely used in gaming applications, virtual communication, education, and content creation. However, existing approaches often fail to capture fine-grained facial expressions and struggle to…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Hao Yu , Rupayan Mallick , Margrit Betke , Sarah Adel Bargal

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

In recent years, the field of talking faces generation has attracted considerable attention, with certain methods adept at generating virtual faces that convincingly imitate human expressions. However, existing methods face challenges…

Computer Vision and Pattern Recognition · Computer Science 2024-01-17 Bingyuan Zhang , Xulong Zhang , Ning Cheng , Jun Yu , Jing Xiao , Jianzong Wang

Diffusion models can synthesize realistic co-speech video from audio for various applications, such as video creation and virtual agents. However, existing diffusion-based methods are slow due to numerous denoising steps and costly…

Computer Vision and Pattern Recognition · Computer Science 2025-10-06 Beijia Lu , Ziyi Chen , Jing Xiao , Jun-Yan Zhu

While previous audio-driven talking head generation (THG) methods generate head poses from driving audio, the generated poses or lips cannot match the audio well or are not editable. In this study, we propose \textbf{PoseTalk}, a THG system…

Computer Vision and Pattern Recognition · Computer Science 2024-09-05 Jun Ling , Yiwen Wang , Han Xue , Rong Xie , Li Song

Generative models have advanced rapidly, enabling impressive talking head generation that brings AI to life. However, most existing methods focus solely on one-way portrait animation. Even the few that support bidirectional conversational…

Audio and Speech Processing · Electrical Eng. & Systems 2025-11-25 Haijie Yang , Zhenyu Zhang , Hao Tang , Jianjun Qian , Jian Yang

Recently audio-driven talking face video generation has attracted considerable attention. However, very few researches address the issue of emotional editing of these talking face videos with continuously controllable expressions, which is…

Computer Vision and Pattern Recognition · Computer Science 2023-11-29 Zhiyao Sun , Yu-Hui Wen , Tian Lv , Yanan Sun , Ziyang Zhang , Yaoyuan Wang , Yong-Jin Liu

Previous animatable 3D-aware GANs for human generation have primarily focused on either the human head or full body. However, head-only videos are relatively uncommon in real life, and full body generation typically does not deal with…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Yue Wu , Sicheng Xu , Jianfeng Xiang , Fangyun Wei , Qifeng Chen , Jiaolong Yang , Xin Tong

Talking Head Generation aims at synthesizing natural-looking talking videos from speech and a single portrait image. Previous 3D talking head generation methods have relied on domain-specific heuristics such as warping-based facial motion…

Computer Vision and Pattern Recognition · Computer Science 2026-01-27 Tong Shi , Melonie de Almeida , Daniela Ivanova , Nicolas Pugeault , Paul Henderson

Existing facial reenactment methods struggle with a trade-off between expressiveness and fine-grained controllability. Holistic facial reenactment models often sacrifice granular control for expressiveness, while methods designed for…

Computer Vision and Pattern Recognition · Computer Science 2026-04-22 Chaonan Ji , Jinwei Qi , Sheng Xu , Peng Zhang , Bang Zhang

Perpetual view generation aims to synthesize a long-term video corresponding to an arbitrary camera trajectory solely from a single input image. Recent methods commonly utilize a pre-trained text-to-image diffusion model to synthesize new…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Bo Pan , Yang Chen , Yingwei Pan , Ting Yao , Wei Chen , Tao Mei

Caricature is an exaggerated form of artistic portraiture that accentuates unique yet subtle characteristics of human faces. Recently, advancements in deep end-to-end techniques have yielded encouraging outcomes in capturing both style and…

Computer Vision and Pattern Recognition · Computer Science 2023-11-23 Lamyanba Laishram , Muhammad Shaheryar , Jong Taek Lee , Soon Ki Jung

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

2D portrait animation has experienced significant advancements in recent years. Much research has utilized the prior knowledge embedded in large generative diffusion models to enhance high-quality image manipulation. However, most methods…

Computer Vision and Pattern Recognition · Computer Science 2025-01-16 Xinya Ji , Gaspard Zoss , Prashanth Chandran , Lingchen Yang , Xun Cao , Barbara Solenthaler , Derek Bradley

Current motion-conditioned video generation methods suffer from prohibitive latency (minutes per video) and non-causal processing that prevents real-time interaction. We present MotionStream, enabling sub-second latency with up to 29 FPS…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Joonghyuk Shin , Zhengqi Li , Richard Zhang , Jun-Yan Zhu , Jaesik Park , Eli Shechtman , Xun Huang

Talking head generation with arbitrary identities and speech audio remains a crucial problem in the realm of the virtual metaverse. Recently, diffusion models have become a popular generative technique in this field with their strong…

Graphics · Computer Science 2025-08-11 Xinyang Li , Gen Li , Zhihui Lin , Yichen Qian , GongXin Yao , Weinan Jia , Aowen Wang , Weihua Chen , Fan Wang

Audio-driven 3D facial animation has several virtual humans applications for content creation and editing. While several existing methods provide solutions for speech-driven animation, precise control over content (what) and style (how) of…

Sound · Computer Science 2024-08-15 Qingju Liu , Hyeongwoo Kim , Gaurav Bharaj

Generating portrait images by controlling the motions of existing faces is an important task of great consequence to social media industries. For easy use and intuitive control, semantically meaningful and fully disentangled parameters…

Computer Vision and Pattern Recognition · Computer Science 2021-09-20 Yurui Ren , Ge Li , Yuanqi Chen , Thomas H. Li , Shan Liu