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

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In this paper, we introduce a novel 3D-aware image generation method that leverages 2D diffusion models. We formulate the 3D-aware image generation task as multiview 2D image set generation, and further to a sequential…

Computer Vision and Pattern Recognition · Computer Science 2023-04-03 Jianfeng Xiang , Jiaolong Yang , Binbin Huang , Xin Tong

We present a 3D-aware one-shot head reenactment method based on a fully volumetric neural disentanglement framework for source appearance and driver expressions. Our method is real-time and produces high-fidelity and view-consistent output,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-11 Phong Tran , Egor Zakharov , Long-Nhat Ho , Anh Tuan Tran , Liwen Hu , Hao Li

Hairstyles are intricate and culturally significant with various geometries, textures, and structures. Existing text or image-guided generation methods fail to handle the richness and complexity of diverse styles. We present TANGLED, a…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Pengyu Long , Zijun Zhao , Min Ouyang , Qingcheng Zhao , Qixuan Zhang , Wei Yang , Lan Xu , Jingyi Yu

Talking head generation is to generate video based on a given source identity and target motion. However, current methods face several challenges that limit the quality and controllability of the generated videos. First, the generated face…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Yue Gao , Yuan Zhou , Jinglu Wang , Xiao Li , Xiang Ming , Yan Lu

The evolution of 3D generative modeling has been notably propelled by the adoption of 2D diffusion models. Despite this progress, the cumbersome optimization process per se presents a critical hurdle to efficiency. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2024-04-10 Xingyi Yang , Xinchao Wang

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

3D-aware generative adversarial networks (GANs) synthesize high-fidelity and multi-view-consistent facial images using only collections of single-view 2D imagery. Towards fine-grained control over facial attributes, recent efforts…

Computer Vision and Pattern Recognition · Computer Science 2023-03-14 Jingxiang Sun , Xuan Wang , Lizhen Wang , Xiaoyu Li , Yong Zhang , Hongwen Zhang , Yebin Liu

We propose a new view synthesis method via synthesizing a 3D neural field from both single or few-view input images. To address the ill-posed nature of the image-to-3D generation problem, we devise a two-stage method that involves a…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Tung Do , Thuan Hoang Nguyen , Anh Tuan Tran , Rang Nguyen , Binh-Son Hua

Recently, multi-view diffusion-based 3D generation methods have gained significant attention. However, these methods often suffer from shape and texture misalignment across generated multi-view images, leading to low-quality 3D generation…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Zhuojiang Cai , Yiheng Zhang , Meitong Guo , Mingdao Wang , Yuwang Wang

The scarcity of large-scale 3D-text paired data poses a great challenge on open vocabulary 3D scene understanding, and hence it is popular to leverage internet-scale 2D data and transfer their open vocabulary capabilities to 3D models…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Pengfei Wang , Yuxi Wang , Shuai Li , Zhaoxiang Zhang , Zhen Lei , Lei Zhang

Three-dimensional Morphable Models (3DMMs) are powerful statistical tools for representing the 3D shapes and textures of an object class. Here we present the most complete 3DMM of the human head to date that includes face, cranium, ears,…

Computer Vision and Pattern Recognition · Computer Science 2020-02-21 Stylianos Ploumpis , Evangelos Ververas , Eimear O' Sullivan , Stylianos Moschoglou , Haoyang Wang , Nick Pears , William A. P. Smith , Baris Gecer , Stefanos Zafeiriou

Emotional Talking Face synthesis is pivotal in multimedia and signal processing, yet existing 3D methods suffer from two critical challenges: poor audio-vision emotion alignment, manifested as difficult audio emotion extraction and…

Artificial Intelligence · Computer Science 2026-01-28 Nanhan Shen , Zhilei Liu

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

We present Envision3D, a novel method for efficiently generating high-quality 3D content from a single image. Recent methods that extract 3D content from multi-view images generated by diffusion models show great potential. However, it is…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Yatian Pang , Tanghui Jia , Yujun Shi , Zhenyu Tang , Junwu Zhang , Xinhua Cheng , Xing Zhou , Francis E. H. Tay , Li Yuan

Reconstructing a complete 3D head from a single portrait remains challenging because existing methods still face a sharp quality-speed trade-off: high-fidelity pipelines often rely on multi-stage processing and per-subject optimization,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-16 Yujie Gao , Yao Xiao , Xiangnan Zhu , Ya Li , Yiyi Zhang , Liqing Zhang , Jianfu Zhang

Generating diverse and high-quality 3D assets automatically poses a fundamental yet challenging task in 3D computer vision. Despite extensive efforts in 3D generation, existing optimization-based approaches struggle to produce large-scale…

Computer Vision and Pattern Recognition · Computer Science 2024-05-15 Ziang Cao , Fangzhou Hong , Tong Wu , Liang Pan , Ziwei Liu

Creating a 360{\deg} parametric model of a human head is a very challenging task. While recent advancements have demonstrated the efficacy of leveraging synthetic data for building such parametric head models, their performance remains…

Computer Vision and Pattern Recognition · Computer Science 2024-08-02 Yuxiao He , Yiyu Zhuang , Yanwen Wang , Yao Yao , Siyu Zhu , Xiaoyu Li , Qi Zhang , Xun Cao , Hao Zhu

Using image as prompts for 3D generation demonstrate particularly strong performances compared to using text prompts alone, for images provide a more intuitive guidance for the 3D generation process. In this work, we delve into the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-29 Seungwook Kim , Yichun Shi , Kejie Li , Minsu Cho , Peng Wang

Creating realistic 3D objects and clothed avatars from a single RGB image is an attractive yet challenging problem. Due to its ill-posed nature, recent works leverage powerful prior from 2D diffusion models pretrained on large datasets.…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Yuxuan Xue , Xianghui Xie , Riccardo Marin , Gerard Pons-Moll

Three-dimensional (3D) technologies have been developing rapidly recent years, and have influenced industrial, medical, cultural, and many other fields. In this paper, we introduce an automatic 3D human head scanning-printing system, which…

Robotics · Computer Science 2023-01-02 Longyu Zhang , Bote Han , Haiwei Dong , Abdulmotaleb El Saddik
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