English
Related papers

Related papers: Head3D: Complete 3D Head Generation via Tri-plane …

200 papers

Tri-plane-like representations have been widely adopted in 3D-aware GANs for head image synthesis and other 3D object/scene modeling tasks due to their efficiency. However, querying features via Cartesian coordinate projection often leads…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Heyuan Li , Kenkun Liu , Lingteng Qiu , Qi Zuo , Keru Zheng , Zilong Dong , Xiaoguang Han

Human head detection, keypoint estimation, and 3D head model fitting are essential tasks with many applications. However, traditional real-world datasets often suffer from bias, privacy, and ethical concerns, and they have been recorded in…

Computer Vision and Pattern Recognition · Computer Science 2024-12-06 Orest Kupyn , Eugene Khvedchenia , Christian Rupprecht

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

Recent progress in NeRF-based GANs has introduced a number of approaches for high-resolution and high-fidelity generative modeling of human heads with a possibility for novel view rendering. At the same time, one must solve an inverse…

Computer Vision and Pattern Recognition · Computer Science 2023-10-27 Ananta R. Bhattarai , Matthias Nießner , Artem Sevastopolsky

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

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

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

Previous animatable 3D-aware GANs for human generation have primarily focused on either the human head or full body. However, head-only videos are relatively uncommon in real life, and full body generation typically does not deal with…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Yue Wu , Sicheng Xu , Jianfeng Xiang , Fangyun Wei , Qifeng Chen , Jiaolong Yang , Xin Tong

In contrast to the traditional avatar creation pipeline which is a costly process, contemporary generative approaches directly learn the data distribution from photographs. While plenty of works extend unconditional generative models and…

Computer Vision and Pattern Recognition · Computer Science 2022-10-18 Junshu Tang , Bo Zhang , Binxin Yang , Ting Zhang , Dong Chen , Lizhuang Ma , Fang Wen

Current advances in human head modeling allow the generation of plausible-looking 3D head models via neural representations, such as NeRFs and SDFs. Nevertheless, constructing complete high-fidelity head models with explicitly controlled…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Artem Sevastopolsky , Philip-William Grassal , Simon Giebenhain , ShahRukh Athar , Luisa Verdoliva , Matthias Niessner

3D face modeling has been an active area of research in computer vision and computer graphics, fueling applications ranging from facial expression transfer in virtual avatars to synthetic data generation. Existing 3D deep learning…

Computer Vision and Pattern Recognition · Computer Science 2022-08-31 Fariborz Taherkhani , Aashish Rai , Quankai Gao , Shaunak Srivastava , Xuanbai Chen , Fernando de la Torre , Steven Song , Aayush Prakash , Daeil Kim

In this paper, we present Export3D, a one-shot 3D-aware portrait animation method that is able to control the facial expression and camera view of a given portrait image. To achieve this, we introduce a tri-plane generator with an effective…

Computer Vision and Pattern Recognition · Computer Science 2026-03-05 Taekyung Ki , Dongchan Min , Gyeongsu Chae

3D scene generation is in high demand across various domains, including virtual reality, gaming, and the film industry. Owing to the powerful generative capabilities of text-to-image diffusion models that provide reliable priors, the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Haiyang Zhou , Xinhua Cheng , Wangbo Yu , Yonghong Tian , Li Yuan

Head avatar reconstruction, crucial for applications in virtual reality, online meetings, gaming, and film industries, has garnered substantial attention within the computer vision community. The fundamental objective of this field is to…

Computer Vision and Pattern Recognition · Computer Science 2024-01-19 Xuangeng Chu , Yu Li , Ailing Zeng , Tianyu Yang , Lijian Lin , Yunfei Liu , Tatsuya Harada

Despite having tremendous progress in image-to-3D generation, existing methods still struggle to produce multi-view consistent images with high-resolution textures in detail, especially in the paradigm of 2D diffusion that lacks 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Haibo Yang , Yang Chen , Yingwei Pan , Ting Yao , Zhineng Chen , Chong-Wah Ngo , Tao Mei

Recent CLIP-guided 3D optimization methods, such as DreamFields and PureCLIPNeRF, have achieved impressive results in zero-shot text-to-3D synthesis. However, due to scratch training and random initialization without prior knowledge, these…

Computer Vision and Pattern Recognition · Computer Science 2023-04-04 Jiale Xu , Xintao Wang , Weihao Cheng , Yan-Pei Cao , Ying Shan , Xiaohu Qie , Shenghua Gao

Recent strides in Text-to-3D techniques have been propelled by distilling knowledge from powerful large text-to-image diffusion models (LDMs). Nonetheless, existing Text-to-3D approaches often grapple with challenges such as…

Computer Vision and Pattern Recognition · Computer Science 2023-08-23 Yiwen Chen , Chi Zhang , Xiaofeng Yang , Zhongang Cai , Gang Yu , Lei Yang , Guosheng Lin

Text-to-3D generation by distilling pretrained large-scale text-to-image diffusion models has shown great promise but still suffers from inconsistent 3D geometric structures (Janus problems) and severe artifacts. The aforementioned problems…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Baorui Ma , Haoge Deng , Junsheng Zhou , Yu-Shen Liu , Tiejun Huang , Xinlong Wang

Audio-driven talking head generation is a core component of digital avatars, and 3D Gaussian Splatting has shown strong performance in real-time rendering of high-fidelity talking heads. However, achieving precise control over fine-grained…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Shaoyang Xie , Xiaofeng Cong , Baosheng Yu , Zhipeng Gui , Jie Gui , Yuan Yan Tang , James Tin-Yau Kwok

Denoising diffusion models have demonstrated outstanding results in 2D image generation, yet it remains a challenge to replicate its success in 3D shape generation. In this paper, we propose leveraging multi-view depth, which represents…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Zhen Wang , Qiangeng Xu , Feitong Tan , Menglei Chai , Shichen Liu , Rohit Pandey , Sean Fanello , Achuta Kadambi , Yinda Zhang