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In this work, we present HyperFlow - a novel generative model that leverages hypernetworks to create continuous 3D object representations in a form of lightweight surfaces (meshes), directly out of point clouds. Efficient object…

Computer Vision and Pattern Recognition · Computer Science 2020-06-17 Przemysław Spurek , Maciej Zięba , Jacek Tabor , Tomasz Trzciński

We introduce AvatarBooth, a novel method for generating high-quality 3D avatars using text prompts or specific images. Unlike previous approaches that can only synthesize avatars based on simple text descriptions, our method enables the…

Computer Vision and Pattern Recognition · Computer Science 2023-06-19 Yifei Zeng , Yuanxun Lu , Xinya Ji , Yao Yao , Hao Zhu , Xun Cao

Whole-body multimodal motion generation, controlled by text, speech, or music, has numerous applications including video generation and character animation. However, employing a unified model to achieve various generation tasks with…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Yuxuan Bian , Ailing Zeng , Xuan Ju , Xian Liu , Zhaoyang Zhang , Wei Liu , Qiang Xu

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

The creation of increasingly vivid 3D talking face has become a hot topic in recent years. Currently, most speech-driven works focus on lip synchronisation but neglect to effectively capture the correlations between emotions and facial…

Computer Vision and Pattern Recognition · Computer Science 2025-05-19 Yihong Lin , Liang Peng , Zhaoxin Fan , Xianjia Wu , Jianqiao Hu , Xiandong Li , Wenxiong Kang , Songju Lei

Generating photorealistic 3D faces from given conditions is a challenging task. Existing methods often rely on time-consuming one-by-one optimization approaches, which are not efficient for modeling the same distribution content, e.g.,…

Computer Vision and Pattern Recognition · Computer Science 2024-01-12 Xiaolong Shen , Jianxin Ma , Chang Zhou , Zongxin Yang

Recent advancements in 2D/3D generative techniques have facilitated the generation of dynamic 3D objects from monocular videos. Previous methods mainly rely on the implicit neural radiance fields (NeRF) or explicit Gaussian Splatting as the…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Zhiqi Li , Yiming Chen , Peidong Liu

Compared with the remarkable progress made in parallel numerical solvers of partial differential equations,the development of algorithms for generating unstructured triangular/tetrahedral meshes has been relatively sluggish. In this paper,…

Numerical Analysis · Mathematics 2024-09-19 Chengdi Ma , Jizu Huang , Hao Luo , Chao Yang

Despite the latest remarkable advances in generative modeling, efficient generation of high-quality 3D assets from textual prompts remains a difficult task. A key challenge lies in data scarcity: the most extensive 3D datasets encompass…

Computer Vision and Pattern Recognition · Computer Science 2024-01-17 Antoine Mercier , Ramin Nakhli , Mahesh Reddy , Rajeev Yasarla , Hong Cai , Fatih Porikli , Guillaume Berger

Metaverse platforms are rapidly evolving to provide immersive spaces for user interaction and content creation. However, the generation of dynamic and interactive 3D objects remains challenging due to the need for advanced 3D modeling and…

Human-Computer Interaction · Computer Science 2025-05-01 Ryutaro Kurai , Takefumi Hiraki , Yuichi Hiroi , Yutaro Hirao , Monica Perusquía-Hernández , Hideaki Uchiyama , Kiyoshi Kiyokawa

As several industries are moving towards modeling massive 3D virtual worlds, the need for content creation tools that can scale in terms of the quantity, quality, and diversity of 3D content is becoming evident. In our work, we aim to train…

Computer Vision and Pattern Recognition · Computer Science 2022-09-23 Jun Gao , Tianchang Shen , Zian Wang , Wenzheng Chen , Kangxue Yin , Daiqing Li , Or Litany , Zan Gojcic , Sanja Fidler

A fundamental problem in the texturing of 3D meshes using pre-trained text-to-image models is to ensure multi-view consistency. State-of-the-art approaches typically use diffusion models to aggregate multi-view inputs, where common issues…

Computer Vision and Pattern Recognition · Computer Science 2024-08-05 Zhengyi Zhao , Chen Song , Xiaodong Gu , Yuan Dong , Qi Zuo , Weihao Yuan , Liefeng Bo , Zilong Dong , Qixing Huang

We present NaTex, a native texture generation framework that predicts texture color directly in 3D space. In contrast to previous approaches that rely on baking 2D multi-view images synthesized by geometry-conditioned Multi-View Diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Zeqiang Lai , Yunfei Zhao , Zibo Zhao , Xin Yang , Xin Huang , Jingwei Huang , Xiangyu Yue , Chunchao Guo

Diffusion models have become a leading approach for high-fidelity medical image synthesis. However, most existing methods for 3D medical image generation rely on convolutional U-Net backbones within latent diffusion frameworks. While…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Marvin Seyfarth , Salman Ul Hassan Dar , Yannik Frisch , Philipp Wild , Norbert Frey , Florian André , Sandy Engelhardt

3D content generation has wide applications in various fields. One of its dominant paradigms is by sparse-view reconstruction using multi-view images generated by diffusion models. However, since directly reconstructing triangle meshes from…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Ruowen Zhao , Zhengyi Wang , Yikai Wang , Zihan Zhou , Jun Zhu

In this work, we focus on synthesizing high-quality textures on 3D meshes. We present Point-UV diffusion, a coarse-to-fine pipeline that marries the denoising diffusion model with UV mapping to generate 3D consistent and high-quality…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Xin Yu , Peng Dai , Wenbo Li , Lan Ma , Zhengzhe Liu , Xiaojuan Qi

Controllable face generation poses critical challenges in generative modeling due to the intricate balance required between semantic controllability and photorealism. While existing approaches struggle with disentangling semantic controls…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Xuechao Zou , Shun Zhang , Xing Fu , Yue Li , Kai Li , Yushe Cao , Congyan Lang , Pin Tao , Junliang Xing

Generating high-quality 3D assets from text and images has long been challenging, primarily due to the absence of scalable 3D representations capable of capturing intricate geometry distributions. In this work, we introduce Direct3D, a…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Shuang Wu , Youtian Lin , Feihu Zhang , Yifei Zeng , Jingxi Xu , Philip Torr , Xun Cao , Yao Yao

Despite recent advancements in neural 3D reconstruction, the dependence on dense multi-view captures restricts their broader applicability. In this work, we propose \textbf{ViewCrafter}, a novel method for synthesizing high-fidelity novel…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Wangbo Yu , Jinbo Xing , Li Yuan , Wenbo Hu , Xiaoyu Li , Zhipeng Huang , Xiangjun Gao , Tien-Tsin Wong , Ying Shan , Yonghong Tian

Modern 3D engines and graphics pipelines require mesh as a memory-efficient representation, which allows efficient rendering, geometry processing, texture editing, and many other downstream operations. However, it is still highly difficult…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Isabella Liu , Hao Su , Xiaolong Wang