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While state-of-the-art audio-video generation models like Veo3 and Sora2 demonstrate remarkable capabilities, their closed-source nature makes their architectures and training paradigms inaccessible. To bridge this gap in accessibility and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Hebeizi Li , Zihao Liang , Benyuan Sun , Zihao Yin , Xiao Sha , Chenliang Wang , Yi Yang

We present a method for generating a video of a talking face. The method takes as inputs: (i) still images of the target face, and (ii) an audio speech segment; and outputs a video of the target face lip synched with the audio. The method…

Computer Vision and Pattern Recognition · Computer Science 2017-07-19 Joon Son Chung , Amir Jamaludin , Andrew Zisserman

Audio-driven talking head generation is crucial for applications in virtual reality, digital avatars, and film production. While NeRF-based methods enable high-fidelity reconstruction, they suffer from low rendering efficiency and…

Sound · Computer Science 2025-09-23 Tianheng Zhu , Yinfeng Yu , Liejun Wang , Fuchun Sun , Wendong Zheng

Joint audio-video generation models have shown that unified generation yields stronger cross-modal coherence than cascaded approaches. However, existing models couple modalities throughout denoising via pervasive attention, treating…

Computer Vision and Pattern Recognition · Computer Science 2026-04-28 Zhen Ye , Xu Tan , Aoxiong Yin , Hongzhan Lin , Guangyan Zhang , Peiwen Sun , Yiming Li , Chi-Min Chan , Wei Ye , Shikun Zhang , Wei Xue

Generating speech from a face image is crucial for developing virtual humans capable of interacting using their unique voices, without relying on pre-recorded human speech. In this paper, we propose Face-StyleSpeech, a zero-shot…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Minki Kang , Wooseok Han , Eunho Yang

Recently, talking-face video generation has received considerable attention. So far most methods generate results with neutral expressions or expressions that are implicitly determined by neural networks in an uncontrollable way. In this…

Computer Vision and Pattern Recognition · Computer Science 2022-04-14 Zipeng Ye , Zhiyao Sun , Yu-Hui Wen , Yanan Sun , Tian Lv , Ran Yi , Yong-Jin Liu

Speech-driven three-dimensional (3D) facial animation synthesis aims to build a mapping from one-dimensional (1D) speech signals to time-varying 3D facial motion signals. Current methods still face challenges in maintaining lip-sync…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Bin Liu , Zhixiang Xiong , Zhifen He , Bo Li

While today's large language models exhibit impressive abilities in generating human-like text, they require massive amounts of data during training. We here take inspiration from human cognitive development to train models in limited data…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Badr AlKhamissi , Yingtian Tang , Abdülkadir Gökce , Johannes Mehrer , Martin Schrimpf

Storytelling in real-world videos often unfolds through multiple shots -- discontinuous yet semantically connected clips that together convey a coherent narrative. However, existing multi-shot video generation (MSV) methods struggle to…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Zhaochong An , Menglin Jia , Haonan Qiu , Zijian Zhou , Xiaoke Huang , Zhiheng Liu , Weiming Ren , Kumara Kahatapitiya , Ding Liu , Sen He , Chenyang Zhang , Tao Xiang , Fanny Yang , Serge Belongie , Tian Xie

All previous methods for audio-driven talking head generation assume the input audio to be clean with a neutral tone. As we show empirically, one can easily break these systems by simply adding certain background noise to the utterance or…

Computer Vision and Pattern Recognition · Computer Science 2019-10-03 Gaurav Mittal , Baoyuan Wang

In this paper, we propose a novel learning approach for feed-forward one-shot 4D head avatar synthesis. Different from existing methods that often learn from reconstructing monocular videos guided by 3DMM, we employ pseudo multi-view videos…

Computer Vision and Pattern Recognition · Computer Science 2024-07-12 Yu Deng , Duomin Wang , Baoyuan Wang

Talking head synthesis is an emerging technology with wide applications in film dubbing, virtual avatars and online education. Recent NeRF-based methods generate more natural talking videos, as they better capture the 3D structural…

Computer Vision and Pattern Recognition · Computer Science 2022-07-26 Shuai Shen , Wanhua Li , Zheng Zhu , Yueqi Duan , Jie Zhou , Jiwen Lu

Vivid talking face generation holds immense potential applications across diverse multimedia domains, such as film and game production. While existing methods accurately synchronize lip movements with input audio, they typically ignore…

Computer Vision and Pattern Recognition · Computer Science 2024-06-13 Jiadong Liang , Feng Lu

Traditionally, the main focus of image super-resolution techniques is on recovering the most likely high-quality images from low-quality images, using a one-to-one low- to high-resolution mapping. Proceeding that way, we ignore the fact…

Image and Video Processing · Electrical Eng. & Systems 2021-02-15 Mohamed Abderrahmen Abid , Ihsen Hedhli , Christian Gagné

Hallucinating high frequency image details in single image super-resolution is a challenging task. Traditional super-resolution methods tend to produce oversmoothed output images due to the ambiguity in mapping between low and high…

Computer Vision and Pattern Recognition · Computer Science 2017-01-27 Libin Sun , James Hays

This paper presents a generative adversarial learning-based human upper body video synthesis approach to generate an upper body video of target person that is consistent with the body motion, face expression, and pose of the person in…

Computer Vision and Pattern Recognition · Computer Science 2019-09-13 Zhaoxiang Liu , Huan Hu , Zipeng Wang , Kai Wang , Jinqiang Bai , Shiguo Lian

We present a multimodal learning-based method to simultaneously synthesize co-speech facial expressions and upper-body gestures for digital characters using RGB video data captured using commodity cameras. Our approach learns from sparse…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Uttaran Bhattacharya , Aniket Bera , Dinesh Manocha

Recent digital media advancements have created increasing demands for sophisticated portrait manipulation techniques, particularly head swapping, where one's head is seamlessly integrated with another's body. However, current approaches…

Computer Vision and Pattern Recognition · Computer Science 2026-04-20 Taewoong Kang , Hyojin Jang , Sohyun Jeong , Seunggi Moon , Gihwi Kim , Hoon Jin Jung , Jaegul choo

Talking head synthesis is a practical technique with wide applications. Current Neural Radiance Field (NeRF) based approaches have shown their superiority on driving one-shot talking heads with videos or signals regressed from audio.…

Computer Vision and Pattern Recognition · Computer Science 2024-08-20 Dongze Li , Kang Zhao , Wei Wang , Yifeng Ma , Bo Peng , Yingya Zhang , Jing Dong

Audio-driven talking head generation aims to create vivid and realistic videos from a static portrait and speech. Existing AR-based methods rely on intermediate facial representations, which limit their expressiveness and realism.…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Yuzhe Weng , Haotian Wang , Yuanhong Yu , Jun Du , Shan He , Xiaoyan Wu , Haoran Xu
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