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Diffusion models have demonstrated remarkable performance in generation tasks. Nevertheless, explaining the diffusion process remains challenging due to it being a sequence of denoising noisy images that are difficult for experts to…

Computer Vision and Pattern Recognition · Computer Science 2024-02-19 Ji-Hoon Park , Yeong-Joon Ju , Seong-Whan Lee

We present a new multi-modal face image generation method that converts a text prompt and a visual input, such as a semantic mask or scribble map, into a photo-realistic face image. To do this, we combine the strengths of Generative…

Computer Vision and Pattern Recognition · Computer Science 2024-05-08 Jihyun Kim , Changjae Oh , Hoseok Do , Soohyun Kim , Kwanghoon Sohn

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

Recent advancements in video diffusion models have significantly enhanced audio-driven portrait animation. However, current methods still suffer from flickering, identity drift, and poor audio-visual synchronization. These issues primarily…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Zhenjie Liu , Jianzhang Lu , Renjie Lu , Cong Liang , Shangfei Wang

We propose a novel method for generating high-resolution videos of talking-heads from speech audio and a single 'identity' image. Our method is based on a convolutional neural network model that incorporates a pre-trained StyleGAN…

Computer Vision and Pattern Recognition · Computer Science 2022-09-12 Mohammed M. Alghamdi , He Wang , Andrew J. Bulpitt , David C. Hogg

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

Diffusion models exhibited tremendous progress in image and video generation, exceeding GANs in quality and diversity. However, they are usually trained on very large datasets and are not naturally adapted to manipulate a given input image…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Yaniv Nikankin , Niv Haim , Michal Irani

The field of generative models has recently witnessed significant progress, with diffusion models showing remarkable performance in image generation. In light of this success, there is a growing interest in exploring the application of…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Ariel Lapid , Idan Achituve , Lior Bracha , Ethan Fetaya

Speech-driven 3D facial animation synthesis has been a challenging task both in industry and research. Recent methods mostly focus on deterministic deep learning methods meaning that given a speech input, the output is always the same.…

Computer Vision and Pattern Recognition · Computer Science 2023-09-21 Stefan Stan , Kazi Injamamul Haque , Zerrin Yumak

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

Diffusion models have achieved great success in modeling continuous data modalities such as images, audio, and video, but have seen limited use in discrete domains such as language. Recent attempts to adapt diffusion to language have…

Computation and Language · Computer Science 2023-11-08 Justin Lovelace , Varsha Kishore , Chao Wan , Eliot Shekhtman , Kilian Q. Weinberger

The latest developments in Artificial Intelligence include diffusion generative models, quite popular tools which can produce original images both unconditionally and, in some cases, conditioned by some inputs provided by the user. Apart…

Computer Vision and Pattern Recognition · Computer Science 2023-02-13 Stefano Scotta , Alberto Messina

Generative models, particularly diffusion models, have made significant success in data synthesis across various modalities, including images, videos, and 3D assets. However, current diffusion models are computationally intensive, often…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Yuanzhi Zhu , Hanshu Yan , Huan Yang , Kai Zhang , Junnan Li

Recent video inpainting algorithms integrate flow-based pixel propagation with transformer-based generation to leverage optical flow for restoring textures and objects using information from neighboring frames, while completing masked…

Computer Vision and Pattern Recognition · Computer Science 2025-01-20 Xiaowen Li , Haolan Xue , Peiran Ren , Liefeng Bo

Audio-driven talking face generation, which aims to synthesize talking faces with realistic facial animations (including accurate lip movements, vivid facial expression details and natural head poses) corresponding to the audio, has…

Computer Vision and Pattern Recognition · Computer Science 2023-04-19 Rongliang Wu , Yingchen Yu , Fangneng Zhan , Jiahui Zhang , Xiaoqin Zhang , Shijian Lu

We propose DiffSHEG, a Diffusion-based approach for Speech-driven Holistic 3D Expression and Gesture generation with arbitrary length. While previous works focused on co-speech gesture or expression generation individually, the joint…

Sound · Computer Science 2024-04-09 Junming Chen , Yunfei Liu , Jianan Wang , Ailing Zeng , Yu Li , Qifeng Chen

Taking inspiration from recent developments in visual generative tasks using diffusion models, we propose a method for end-to-end speech-driven video editing using a denoising diffusion model. Given a video of a talking person, and a…

Computer Vision and Pattern Recognition · Computer Science 2023-05-12 Dan Bigioi , Shubhajit Basak , Michał Stypułkowski , Maciej Zięba , Hugh Jordan , Rachel McDonnell , Peter Corcoran

Deepfake images are fast becoming a serious concern due to their realism. Diffusion models have recently demonstrated highly realistic visual content generation, which makes them an excellent potential tool for Deepfake generation. To curb…

Computer Vision and Pattern Recognition · Computer Science 2023-09-27 Yunzhuo Chen , Nur Al Hasan Haldar , Naveed Akhtar , Ajmal Mian

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

Speech-driven gesture synthesis is a field of growing interest in virtual human creation. However, a critical challenge is the inherent intricate one-to-many mapping between speech and gestures. Previous studies have explored and achieved…

Graphics · Computer Science 2023-02-03 Fan Zhang , Naye Ji , Fuxing Gao , Yongping Li
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