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Diffusion models have shown impressive potential on talking head generation. While plausible appearance and talking effect are achieved, these methods still suffer from temporal, 3D or expression inconsistency due to the error accumulation…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Haijie Yang , Zhenyu Zhang , Hao Tang , Jianjun Qian , Jian Yang

We present a novel framework for generating high-quality, animatable 4D avatar from a single image. While recent advances have shown promising results in 4D avatar creation, existing methods either require extensive multiview data or…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Fei Yin , Mallikarjun B R , Chun-Han Yao , Rafał Mantiuk , Varun Jampani

Recent advancements in text-to-image generation have enabled significant progress in zero-shot 3D shape generation. This is achieved by score distillation, a methodology that uses pre-trained text-to-image diffusion models to optimize the…

Computer Vision and Pattern Recognition · Computer Science 2023-05-29 Zhenzhen Weng , Zeyu Wang , Serena Yeung

Diffusion-based models have gained wide adoption in the virtual human generation due to their outstanding expressiveness. However, their substantial computational requirements have constrained their deployment in real-time interactive…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Haojie Yu , Zhaonian Wang , Yihan Pan , Meng Cheng , Hao Yang , Chao Wang , Tao Xie , Xiaoming Xu , Xiaoming Wei , Xunliang Cai

Recent advances in generative diffusion models have enabled the previously unfeasible capability of generating 3D assets from a single input image or a text prompt. In this work, we aim to enhance the quality and functionality of these…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Xiyi Chen , Marko Mihajlovic , Shaofei Wang , Sergey Prokudin , Siyu Tang

Despite the remarkable process of talking-head-based avatar-creating solutions, directly generating anchor-style videos with full-body motions remains challenging. In this study, we propose Make-Your-Anchor, a novel system necessitating…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Ziyao Huang , Fan Tang , Yong Zhang , Xiaodong Cun , Juan Cao , Jintao Li , Tong-Yee Lee

Creating high-quality animatable 3D human avatars from a single image remains a significant challenge in computer vision due to the inherent difficulty of reconstructing complete 3D information from a single viewpoint. Current approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-05-09 Yonwoo Choi

Existing single-image 3D human avatar methods primarily rely on rigid joint transformations, limiting their ability to model realistic cloth dynamics. We present DynaAvatar, a zero-shot framework that reconstructs animatable 3D human…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Joohyun Kwon , Geonhee Sim , Gyeongsik Moon

The generation of high-quality, animatable 3D head avatars from text has enormous potential in content creation applications such as games, movies, and embodied virtual assistants. Current text-to-3D generation methods typically combine…

Computer Vision and Pattern Recognition · Computer Science 2025-04-23 Yiqian Wu , Malte Prinzler , Xiaogang Jin , Siyu Tang

Creating human avatars is a highly desirable yet challenging task. Recent advancements in radiance field rendering have achieved unprecedented photorealism and real-time performance for personalized dynamic human avatars. However, these…

Graphics · Computer Science 2025-09-09 Dongliang Cao , Guoxing Sun , Marc Habermann , Florian Bernard

Real-time, streaming interactive avatars represent a critical yet challenging goal in digital human research. Although diffusion-based human avatar generation methods achieve remarkable success, their non-causal architecture and high…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Zhiyao Sun , Ziqiao Peng , Yifeng Ma , Yi Chen , Zhengguang Zhou , Zixiang Zhou , Guozhen Zhang , Youliang Zhang , Yuan Zhou , Qinglin Lu , Yong-Jin Liu

We present a novel approach for generating animatable 3D-aware art avatars from a single image, with controllable facial expressions, head poses, and shoulder movements. Unlike previous reenactment methods, our approach utilizes a…

Computer Vision and Pattern Recognition · Computer Science 2024-03-27 Shaoxu Li

We present a unified and generalizable framework for synthesizing view-consistent and temporally coherent avatars from a single image, addressing the challenging task of single-image avatar generation. Existing diffusion-based methods often…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Yixing Lu , Junting Dong , Youngjoong Kwon , Qin Zhao , Bo Dai , Fernando De la Torre

Large-scale pre-trained vision-language models allow for the zero-shot text-based generation of 3D avatars. The previous state-of-the-art method utilized CLIP to supervise neural implicit models that reconstructed a human body mesh.…

Computer Vision and Pattern Recognition · Computer Science 2023-09-15 Shuo Huang , Zongxin Yang , Liangting Li , Yi Yang , Jia Jia

Digital human avatars aim to simulate the dynamic appearance of humans in virtual environments, enabling immersive experiences across gaming, film, virtual reality, and more. However, the conventional process for creating and animating…

Computer Vision and Pattern Recognition · Computer Science 2025-10-15 Felix Taubner , Ruihang Zhang , Mathieu Tuli , Sherwin Bahmani , David B. Lindell

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

Large-scale text-to-video (T2V) diffusion models have great progress in recent years in terms of visual quality, motion and temporal consistency. However, the generation process is still a black box, where all attributes (e.g., appearance,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Jiwen Yu , Xiaodong Cun , Chenyang Qi , Yong Zhang , Xintao Wang , Ying Shan , Jian Zhang

Reconstructing photorealistic and dynamic portrait avatars from images is essential to many applications including advertising, visual effects, and virtual reality. Depending on the application, avatar reconstruction involves different…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Felix Taubner , Ruihang Zhang , Mathieu Tuli , David B. Lindell

We propose a method for synthesizing edited photo-realistic digital avatars with text instructions. Given a short monocular RGB video and text instructions, our method uses an image-conditioned diffusion model to edit one head image and…

Computer Vision and Pattern Recognition · Computer Science 2023-06-06 Shaoxu Li

Reconstructing photorealistic and animatable 4D head avatars from a single portrait image remains a fundamental challenge in computer vision. While diffusion models have enabled remarkable progress in image and video generation for avatar…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Chao Xu , Xiaochen Zhao , Xiang Deng , Jingxiang Sun , Donglin Di , Zhuo Su , Yebin Liu
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