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Related papers: FG-Portrait: 3D Flow Guided Editable Portrait Anim…

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Rectified Flow text-to-image models surpass diffusion models in image quality and text alignment, but adapting ReFlow for real-image editing remains challenging. We propose a new real-image editing method for ReFlow by analyzing the…

Computer Vision and Pattern Recognition · Computer Science 2025-07-03 Jimyeong Kim , Jungwon Park , Yeji Song , Nojun Kwak , Wonjong Rhee

Speech-driven 3D facial animation has gained significant attention for its ability to create realistic and expressive facial animations in 3D space based on speech. Learning-based methods have shown promising progress in achieving accurate…

Computer Vision and Pattern Recognition · Computer Science 2023-10-11 Se Jin Park , Joanna Hong , Minsu Kim , Yong Man Ro

Image-based virtual try-on involves synthesizing perceptually convincing images of a model wearing a particular garment and has garnered significant research interest due to its immense practical applicability. Recent methods involve a two…

Computer Vision and Pattern Recognition · Computer Science 2021-09-16 Ayush Chopra , Rishabh Jain , Mayur Hemani , Balaji Krishnamurthy

Recently, text-to-image generation has exhibited remarkable advancements, with the ability to produce visually impressive results. In contrast, text-to-3D generation has not yet reached a comparable level of quality. Existing methods…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Yukang Cao , Yan-Pei Cao , Kai Han , Ying Shan , Kwan-Yee K. Wong

We propose ID-to-3D, a method to generate identity- and text-guided 3D human heads with disentangled expressions, starting from even a single casually captured in-the-wild image of a subject. The foundation of our approach is anchored in…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Francesca Babiloni , Alexandros Lattas , Jiankang Deng , Stefanos Zafeiriou

Diffusion models have emerged as a powerful generative method, capable of producing stunning photo-realistic images from natural language descriptions. However, these models lack explicit control over the 3D structure in the generated…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Wufei Ma , Qihao Liu , Jiahao Wang , Angtian Wang , Xiaoding Yuan , Yi Zhang , Zihao Xiao , Guofeng Zhang , Beijia Lu , Ruxiao Duan , Yongrui Qi , Adam Kortylewski , Yaoyao Liu , Alan Yuille

Current diffusion or flow-based generative models for 3D shapes divide to two: distilling pre-trained 2D image diffusion models, and training directly on 3D shapes. When training a diffusion or flow models on 3D shapes a crucial design…

Computer Vision and Pattern Recognition · Computer Science 2024-04-25 Lior Yariv , Omri Puny , Natalia Neverova , Oran Gafni , Yaron Lipman

In this paper, we introduce a Key-point-guided Diffusion probabilistic Model (KDM) that gains precise control over images by manipulating the object's key-point. We propose a two-stage generative model incorporating an optical flow map as…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Seok-Hwan Oh , Guil Jung , Myeong-Gee Kim , Sang-Yun Kim , Young-Min Kim , Hyeon-Jik Lee , Hyuk-Sool Kwon , Hyeon-Min Bae

Recent advances in diffusion$/$flow-matching policies have enabled imitation learning of complex, multi-modal action trajectories. However, they are computationally expensive because they sample a trajectory of trajectories: a…

Deep learning models have emerged as a powerful tool for various medical applications. However, their success depends on large, high-quality datasets that are challenging to obtain due to privacy concerns and costly annotation. Generative…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Milad Yazdani , Yasamin Medghalchi , Pooria Ashrafian , Ilker Hacihaliloglu , Dena Shahriari

Existing neural rendering-based text-to-3D-portrait generation methods typically make use of human geometry prior and diffusion models to obtain guidance. However, relying solely on geometry information introduces issues such as the Janus…

Computer Vision and Pattern Recognition · Computer Science 2024-04-17 Yiqian Wu , Hao Xu , Xiangjun Tang , Xien Chen , Siyu Tang , Zhebin Zhang , Chen Li , Xiaogang Jin

Recent advancements in diffusion techniques have propelled image and video generation to unprecedented levels of quality, significantly accelerating the deployment and application of generative AI. However, 3D shape generation technology…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Yangguang Li , Zi-Xin Zou , Zexiang Liu , Dehu Wang , Yuan Liang , Zhipeng Yu , Xingchao Liu , Yuan-Chen Guo , Ding Liang , Wanli Ouyang , Yan-Pei Cao

The task of 3D shape captioning occupies a significant place within the domain of computer graphics and has garnered considerable interest in recent years. Traditional approaches to this challenge frequently depend on the utilization of…

Graphics · Computer Science 2025-09-30 Zhenyu Shu , Jiawei Wen , Shiyang Li , Shiqing Xin , Ligang Liu

Text-driven video editing aims to modify video content based on natural language instructions. While recent training-free methods have leveraged pretrained diffusion models, they often rely on an inversion-editing paradigm. This paradigm…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Guangzhao Li , Yanming Yang , Chenxi Song , Chi Zhang

Text-guided diffusion models have revolutionized image generation and editing, offering exceptional realism and diversity. Specifically, in the context of diffusion-based editing, where a source image is edited according to a target prompt,…

Computer Vision and Pattern Recognition · Computer Science 2023-10-20 Xuan Ju , Ailing Zeng , Yuxuan Bian , Shaoteng Liu , Qiang Xu

3D style transfer enables the creation of visually expressive 3D content, enriching the visual appearance of 3D scenes and objects. However, existing VGG- and CLIP-based methods struggle to model multi-view consistency within the model…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Yitong Yang , Xuexin Liu , Yinglin Wang , Jing Wang , Hao Dou , Changshuo Wang , Shuting He

Talking head generation is a significant research topic that still faces numerous challenges. Previous works often adopt generative adversarial networks or regression models, which are plagued by generation quality and average facial shape…

Computer Vision and Pattern Recognition · Computer Science 2024-08-20 Ziyu Yao , Xuxin Cheng , Zhiqi Huang

This paper focuses on the task of speech-driven 3D facial animation, which aims to generate realistic and synchronized facial motions driven by speech inputs. Recent methods have employed audio-conditioned diffusion models for 3D facial…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Yifan Yang , Zhi Cen , Sida Peng , Xiangwei Chen , Yifu Deng , Xinyu Zhu , Fan Jia , Xiaowei Zhou , Hujun Bao

Two major approaches exist for creating animatable human avatars. The first, a 3D-based approach, optimizes a NeRF- or 3DGS-based avatar from videos of a single person, achieving personalization through a disentangled identity…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Geonhee Sim , Gyeongsik Moon

The task of audio-driven portrait animation involves generating a talking head video using an identity image and an audio track of speech. While many existing approaches focus on lip synchronization and video quality, few tackle the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Jian Zhang , Weijian Mai , Zhijun Zhang
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