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4D content generation focuses on creating dynamic 3D objects that change over time. Existing methods primarily rely on pre-trained video diffusion models, utilizing sampling processes or reference videos. However, these approaches face…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Jiajing Lin , Zhenzhong Wang , Yongjie Hou , Yuzhou Tang , Min Jiang

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

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

Efficiently generating a freestyle 3D portrait with high quality and 3D-consistency is a promising yet challenging task. The portrait styles generated by most existing methods are usually restricted by their 3D generators, which are learned…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Tianxiang Ma , Kang Zhao , Jianxin Sun , Yingya Zhang , Jing Dong

Recent advancements in deep learning for 3D models have propelled breakthroughs in generation, detection, and scene understanding. However, the effectiveness of these algorithms hinges on large training datasets. We address the challenge by…

Computer Vision and Pattern Recognition · Computer Science 2024-05-16 Mingxiang Chen , Jian Zhang , Boli Zhou , Yang Song

3D assets are essential in the digital age. While automatic 3D generation, such as image-to-3d, has made significant strides in recent years, it often struggles to achieve fast, detailed, and high-fidelity generation simultaneously. In this…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Huanning Dong , Yinuo Huang , Fan Li , Ping Kuang

While recent works have achieved great success on image-to-3D object generation, high quality and fidelity 3D head generation from a single image remains a great challenge. Previous text-based methods for generating 3D heads were limited by…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Jinkun Hao , Junshu Tang , Jiangning Zhang , Ran Yi , Yijia Hong , Moran Li , Weijian Cao , Yating Wang , Chengjie Wang , Lizhuang Ma

Recent one image to 3D generation methods commonly adopt Score Distillation Sampling (SDS). Despite the impressive results, there are multiple deficiencies including multi-view inconsistency, over-saturated and over-smoothed textures, as…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Junwu Zhang , Zhenyu Tang , Yatian Pang , Xinhua Cheng , Peng Jin , Yida Wei , Munan Ning , Li Yuan

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

Recently, 3D generative models have made impressive progress, enabling the generation of almost arbitrary 3D assets from text or image inputs. However, these approaches generate objects in isolation without any consideration for the scene…

Computer Vision and Pattern Recognition · Computer Science 2025-05-02 Jinghao Zhou , Tomas Jakab , Philip Torr , Christian Rupprecht

Despite significant advancements in customizing text-to-image and video generation models, generating images and videos that effectively integrate multiple personalized concepts remains a challenging task. To address this, we present…

Computer Vision and Pattern Recognition · Computer Science 2025-03-05 Gihyun Kwon , Jong Chul Ye

Recent multimodal large language models have achieved strong performance in unified text and image understanding and generation, yet extending such native capability to 3D remains challenging due to limited data. Compared to abundant 2D…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Chongjie Ye , Cheng Cao , Chuanyu Pan , Yiming Hao , Yihao Zhi , Yuanming Hu , Xiaoguang Han

Recent advancements in text-to-image generation models have dramatically enhanced the generation of photorealistic images from textual prompts, leading to an increased interest in personalized text-to-image applications, particularly in…

Computer Vision and Pattern Recognition · Computer Science 2025-03-05 Xierui Wang , Siming Fu , Qihan Huang , Wanggui He , Hao Jiang

3D digital garment generation and editing play a pivotal role in fashion design, virtual try-on, and gaming. Traditional methods struggle to meet the growing demand due to technical complexity and high resource costs. Learning-based…

Graphics · Computer Science 2025-09-23 Ruiyan Wang , Zhengxue Cheng , Zonghao Lin , Jun Ling , Yuzhou Liu , Yanru An , Rong Xie , Li Song

Generating high-quality 3D objects from textual descriptions remains a challenging problem due to computational cost, the scarcity of 3D data, and complex 3D representations. We introduce Geometry Image Diffusion (GIMDiffusion), a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-09-06 Slava Elizarov , Ciara Rowles , Simon Donné

In recent years, the demand for 3D content has grown exponentially with the intelligent upgrade of interactive media, extended reality (XR), and Metaverse industries. In order to overcome the limitations of traditional manual modeling…

Graphics · Computer Science 2025-12-23 Xiang Tang , Ruotong Li , Xiaopeng Fan

Generating 3D models has traditionally been a complex task requiring specialized expertise. While recent advances in generative AI have sought to automate this process, existing methods produce non-editable representation, such as meshes or…

Graphics · Computer Science 2026-01-21 Fadlullah Raji , Stefano Petrangeli , Matheus Gadelha , Yu Shen , Uttaran Bhattacharya , Gang Wu

Text-guided generative diffusion models unlock powerful image creation and editing tools. While these have been extended to video generation, current approaches that edit the content of existing footage while retaining structure require…

Computer Vision and Pattern Recognition · Computer Science 2023-02-07 Patrick Esser , Johnathan Chiu , Parmida Atighehchian , Jonathan Granskog , Anastasis Germanidis

This paper explores the burgeoning field of 3D content generation within the landscape of Artificial Intelligence Generated Content (AIGC) and large-scale models. It investigates innovative methods like Text-to-3D and Image-to-3D, which…

Graphics · Computer Science 2024-05-27 Ke Zhao , Andreas Larsen

Language-guided image generation has achieved great success nowadays by using diffusion models. However, texts can be less detailed to describe highly-specific subjects such as a particular dog or a certain car, which makes pure…

Computer Vision and Pattern Recognition · Computer Science 2023-03-17 Yiyang Ma , Huan Yang , Wenjing Wang , Jianlong Fu , Jiaying Liu