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Existing diffusion-based text-to-3D generation methods primarily focus on producing visually realistic shapes and appearances, often neglecting the physical constraints necessary for downstream tasks. Generated models frequently fail to…

Machine Learning · Computer Science 2024-11-19 Yunuo Chen , Tianyi Xie , Zeshun Zong , Xuan Li , Feng Gao , Yin Yang , Ying Nian Wu , Chenfanfu Jiang

Diffusion-based video generation techniques have significantly improved zero-shot talking-head avatar generation, enhancing the naturalness of both head motion and facial expressions. However, existing methods suffer from poor…

Graphics · Computer Science 2025-04-24 Lingzhou Mu , Baiji Liu , Ruonan Zhang , Guiming Mo , Jiawei Jin , Kai Zhang , Haozhi Huang

Capturing and editing full head performances enables the creation of virtual characters with various applications such as extended reality and media production. The past few years witnessed a steep rise in the photorealism of human head…

Computer Vision and Pattern Recognition · Computer Science 2023-06-05 Mohit Mendiratta , Xingang Pan , Mohamed Elgharib , Kartik Teotia , Mallikarjun B R , Ayush Tewari , Vladislav Golyanik , Adam Kortylewski , Christian Theobalt

By lifting the pre-trained 2D diffusion models into Neural Radiance Fields (NeRFs), text-to-3D generation methods have made great progress. Many state-of-the-art approaches usually apply score distillation sampling (SDS) to optimize the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-20 Yuze He , Yushi Bai , Matthieu Lin , Jenny Sheng , Yubin Hu , Qi Wang , Yu-Hui Wen , Yong-Jin Liu

Editable 3D-aware generation, which supports user-interacted editing, has witnessed rapid development recently. However, existing editable 3D GANs either fail to achieve high-accuracy local editing or suffer from huge computational costs.…

Computer Vision and Pattern Recognition · Computer Science 2024-02-28 Fan Yang , Tianyi Chen , Xiaosheng He , Zhongang Cai , Lei Yang , Si Wu , Guosheng Lin

We present Diff3F as a simple, robust, and class-agnostic feature descriptor that can be computed for untextured input shapes (meshes or point clouds). Our method distills diffusion features from image foundational models onto input shapes.…

Computer Vision and Pattern Recognition · Computer Science 2024-04-04 Niladri Shekhar Dutt , Sanjeev Muralikrishnan , Niloy J. Mitra

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

Significant progress has been made for speech-driven 3D face animation, but most works focus on learning the motion of mesh/geometry, ignoring the impact of dynamic texture. In this work, we reveal that dynamic texture plays a key role in…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Xuanchen Li , Jianyu Wang , Yuhao Cheng , Yikun Zeng , Xingyu Ren , Wenhan Zhu , Weiming Zhao , Yichao Yan

Digital humans and, especially, 3D facial avatars have raised a lot of attention in the past years, as they are the backbone of several applications like immersive telepresence in AR or VR. Despite the progress, facial avatars reconstructed…

Computer Vision and Pattern Recognition · Computer Science 2023-11-27 Berna Kabadayi , Wojciech Zielonka , Bharat Lal Bhatnagar , Gerard Pons-Moll , Justus Thies

We present PrismAvatar: a 3D head avatar model which is designed specifically to enable real-time animation and rendering on resource-constrained edge devices, while still enjoying the benefits of neural volumetric rendering at training…

Computer Vision and Pattern Recognition · Computer Science 2025-02-12 Prashant Raina , Felix Taubner , Mathieu Tuli , Eu Wern Teh , Kevin Ferreira

Advances in 3D generation have facilitated sequential 3D model generation (a.k.a 4D generation), yet its application for animatable objects with large motion remains scarce. Our work proposes AnimatableDreamer, a text-to-4D generation…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Xinzhou Wang , Yikai Wang , Junliang Ye , Zhengyi Wang , Fuchun Sun , Pengkun Liu , Ling Wang , Kai Sun , Xintong Wang , Bin He

Diffusion-based audio-driven talking avatar methods have recently gained attention for their high-fidelity, vivid, and expressive results. However, their slow inference speed limits practical applications. Despite the development of various…

Computer Vision and Pattern Recognition · Computer Science 2025-04-07 Tianyun Zhong , Chao Liang , Jianwen Jiang , Gaojie Lin , Jiaqi Yang , Zhou Zhao

Text-to-image diffusion models pre-trained on billions of image-text pairs have recently enabled 3D content creation by optimizing a randomly initialized differentiable 3D representation with score distillation. However, the optimization…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Yukun Huang , Jianan Wang , Yukai Shi , Boshi Tang , Xianbiao Qi , Lei Zhang

We introduce TurboPortrait3D: a method for low-latency novel-view synthesis of human portraits. Our approach builds on the observation that existing image-to-3D models for portrait generation, while capable of producing renderable 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-10-29 Emily Kim , Julieta Martinez , Timur Bagautdinov , Jessica Hodgins

Recent progress in text-to-3D generation has been achieved through the utilization of score distillation methods: they make use of the pre-trained text-to-image (T2I) diffusion models by distilling via the diffusion model training…

Computer Vision and Pattern Recognition · Computer Science 2024-03-25 Kyungmin Lee , Kihyuk Sohn , Jinwoo Shin

Recently, 2D speaking avatars have increasingly participated in everyday scenarios due to the fast development of facial animation techniques. However, most existing works neglect the explicit control of human bodies. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Jiazhi Guan , Quanwei Yang , Kaisiyuan Wang , Hang Zhou , Shengyi He , Zhiliang Xu , Haocheng Feng , Errui Ding , Jingdong Wang , Hongtao Xie , Youjian Zhao , Ziwei Liu

Recent advances in 3D generation have been remarkable, with methods such as DreamFusion leveraging large-scale text-to-image diffusion-based models to guide 3D object generation. These methods enable the synthesis of detailed and…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Bohan Zeng , Shanglin Li , Yutang Feng , Ling Yang , Hong Li , Sicheng Gao , Jiaming Liu , Conghui He , Wentao Zhang , Jianzhuang Liu , Baochang Zhang , Shuicheng Yan

Creating personalized 3D animations with precise control and realistic head motions remains challenging for current speech-driven 3D facial animation methods. Editing these animations is especially complex and time consuming, requires…

Graphics · Computer Science 2025-10-01 Balamurugan Thambiraja , Malte Prinzler , Sadegh Aliakbarian , Darren Cosker , Justus Thies

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

We study the problem of 3D-aware full-body human generation, aiming at creating animatable human avatars with high-quality textures and geometries. Generally, two challenges remain in this field: i) existing methods struggle to generate…

Computer Vision and Pattern Recognition · Computer Science 2023-10-05 Xuanmeng Zhang , Jianfeng Zhang , Rohan Chacko , Hongyi Xu , Guoxian Song , Yi Yang , Jiashi Feng