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In this work, we tackle the challenge of enhancing the realism and expressiveness in talking head video generation by focusing on the dynamic and nuanced relationship between audio cues and facial movements. We identify the limitations of…

Computer Vision and Pattern Recognition · Computer Science 2024-08-09 Linrui Tian , Qi Wang , Bang Zhang , Liefeng Bo

Neural implicit fields are powerful for representing 3D scenes and generating high-quality novel views, but it remains challenging to use such implicit representations for creating a 3D human avatar with a specific identity and artistic…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Ruixiang Jiang , Can Wang , Jingbo Zhang , Menglei Chai , Mingming He , Dongdong Chen , Jing Liao

Recently, diffusion models have exhibited superior performance in the area of image inpainting. Inpainting methods based on diffusion models can usually generate realistic, high-quality image content for masked areas. However, due to the…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Ruichen Wang , Junliang Zhang , Qingsong Xie , Chen Chen , Haonan Lu

Face inpainting techniques recover missing or occluded facial regions in a visually realistic manner, but preserving the identity in the final output remains a fundamental challenge. Identity consistency is crucial for downstream…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 João Santos , Carlos Santiago , Manuel Marques

Speech-driven animation has gained significant traction in recent years, with current methods achieving near-photorealistic results. However, the field remains underexplored regarding non-verbal communication despite evidence demonstrating…

Computer Vision and Pattern Recognition · Computer Science 2023-08-31 Antoni Bigata Casademunt , Rodrigo Mira , Nikita Drobyshev , Konstantinos Vougioukas , Stavros Petridis , Maja Pantic

This paper studies the human image animation task, which aims to generate a video of a certain reference identity following a particular motion sequence. Existing animation works typically employ the frame-warping technique to animate the…

Computer Vision and Pattern Recognition · Computer Science 2023-11-29 Zhongcong Xu , Jianfeng Zhang , Jun Hao Liew , Hanshu Yan , Jia-Wei Liu , Chenxu Zhang , Jiashi Feng , Mike Zheng Shou

While modern diffusion models excel at generating diverse single images, extending this to sequential generation reveals a fundamental challenge: balancing narrative dynamism with multi-character coherence. Existing methods often falter at…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Qi Zhao , Jun Chen , Ivor Tsang , Guang Dai

The utilization of synthetic data for fingerprint recognition has garnered increased attention due to its potential to alleviate privacy concerns surrounding sensitive biometric data. However, current methods for generating fingerprints…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Steven A. Grosz , Anil K. Jain

We present AvatarPopUp, a method for fast, high quality 3D human avatar generation from different input modalities, such as images and text prompts and with control over the generated pose and shape. The common theme is the use of…

Computer Vision and Pattern Recognition · Computer Science 2024-07-15 Nikos Kolotouros , Thiemo Alldieck , Enric Corona , Eduard Gabriel Bazavan , Cristian Sminchisescu

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

The increasing reliance on large-scale datasets in machine learning poses significant privacy and ethical challenges, particularly in sensitive domains such as face recognition. Synthetic data generation offers a promising alternative;…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Parsa Rahimi , Damien Teney , Sebastien Marcel

Diffusion models have recently shown strong progress in generative tasks, offering a more stable alternative to GAN-based approaches for makeup transfer. Existing methods often suffer from limited datasets, poor disentanglement between…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Qihe Pan , Yiming Wu , Xing Zhao , Liang Xie , Guodao Sun , Ronghua Liang

Emotional talking head synthesis aims to generate talking portrait videos with vivid expressions. Existing methods still exhibit limitations in control flexibility, motion naturalness, and expression quality. Moreover, currently available…

Computer Vision and Pattern Recognition · Computer Science 2025-12-24 Yiguo Jiang , Xiaodong Cun , Yong Zhang , Yudian Zheng , Fan Tang , Chi-Man Pun

Despite promising progress in face swapping task, realistic swapped images remain elusive, often marred by artifacts, particularly in scenarios involving high pose variation, color differences, and occlusion. To address these issues, we…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Sanoojan Baliah , Qinliang Lin , Shengcai Liao , Xiaodan Liang , Muhammad Haris Khan

Image fusion seeks to seamlessly integrate foreground objects with background scenes, producing realistic and harmonious fused images. Unlike existing methods that directly insert objects into the background, adaptive and interactive fusion…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Junjia Huang , Pengxiang Yan , Jiyang Liu , Jie Wu , Zhao Wang , Yitong Wang , Liang Lin , Guanbin Li

Recent advances in diffusion models have made significant progress in digital human generation. However, most existing models still struggle to maintain 3D consistency, temporal coherence, and motion accuracy. A key reason for these…

Graphics · Computer Science 2025-03-21 Xuan Gao , Jingtao Zhou , Dongyu Liu , Yuqi Zhou , Juyong Zhang

This paper aims to bring fine-grained expression control while maintaining high-fidelity identity in portrait generation. This is challenging due to the mutual interference between expression and identity: (i) fine expression control…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Liangwei Jiang , Ruida Li , Zhifeng Zhang , Shuo Fang , Chenguang Ma

Editing real facial images is a crucial task in computer vision with significant demand in various real-world applications. While GAN-based methods have showed potential in manipulating images especially when combined with CLIP, these…

Computer Vision and Pattern Recognition · Computer Science 2023-06-06 Dongxu Yue , Qin Guo , Munan Ning , Jiaxi Cui , Yuesheng Zhu , Li Yuan

Text-to-story visualization is challenging due to the need for consistent interaction among multiple characters across frames. Existing methods struggle with character consistency, leading to artifact generation and inaccurate dialogue…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Ayan Banerjee , Josep Llados , Umapada Pal , Anjan Dutta

Facial expression editing methods can be mainly categorized into two types based on their architectures: 2D-based and 3D-based methods. The former lacks 3D face modeling capabilities, making it difficult to edit 3D factors effectively. The…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Yikang He , Jichao Zhang , Wei Wang , Nicu Sebe , Yao Zhao
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