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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

We present a cascaded diffusion model based on a part-level implicit 3D representation. Our model achieves state-of-the-art generation quality and also enables part-level shape editing and manipulation without any additional training in…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Juil Koo , Seungwoo Yoo , Minh Hieu Nguyen , Minhyuk Sung

Recent 3D generative models have achieved remarkable performance in synthesizing high resolution photorealistic images with view consistency and detailed 3D shapes, but training them for diverse domains is challenging since it requires…

Computer Vision and Pattern Recognition · Computer Science 2023-04-03 Gwanghyun Kim , Se Young Chun

3D style transfer enables the creation of visually expressive 3D content, enriching the visual appearance of 3D scenes and objects. However, existing VGG- and CLIP-based methods struggle to model multi-view consistency within the model…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Yitong Yang , Xuexin Liu , Yinglin Wang , Jing Wang , Hao Dou , Changshuo Wang , Shuting He

High-quality textures are critical for realistic 3D content creation, yet existing generative methods are slow, rely on UV maps, and often fail to remain faithful to a reference image. To address these challenges, we propose a…

Computer Vision and Pattern Recognition · Computer Science 2025-09-08 Arianna Rampini , Kanika Madan , Bruno Roy , AmirHossein Zamani , Derek Cheung

Image generation based on text-to-image generation models is a task with practical application scenarios that fine-grained styles cannot be precisely described and controlled in natural language, while the guidance information of stylized…

Computer Vision and Pattern Recognition · Computer Science 2025-10-03 Shuochen Chang

3D generation methods have shown visually compelling results powered by diffusion image priors. However, they often fail to produce realistic geometric details, resulting in overly smooth surfaces or geometric details inaccurately baked in…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Ruihan Gao , Kangle Deng , Gengshan Yang , Wenzhen Yuan , Jun-Yan Zhu

Generating images from hand-drawings is a crucial and fundamental task in content creation. The translation is difficult as there exist infinite possibilities and the different users usually expect different outcomes. Therefore, we propose…

Computer Vision and Pattern Recognition · Computer Science 2022-09-02 Shin-I Cheng , Yu-Jie Chen , Wei-Chen Chiu , Hung-Yu Tseng , Hsin-Ying Lee

We present LT3SD, a novel latent diffusion model for large-scale 3D scene generation. Recent advances in diffusion models have shown impressive results in 3D object generation, but are limited in spatial extent and quality when extended to…

Computer Vision and Pattern Recognition · Computer Science 2025-05-02 Quan Meng , Lei Li , Matthias Nießner , Angela Dai

Existing attribute editing methods treat semantic attributes as binary, resulting in a single edit per attribute. However, attributes such as eyeglasses, smiles, or hairstyles exhibit a vast range of diversity. In this work, we formulate…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Rishubh Parihar , Prasanna Balaji , Raghav Magazine , Sarthak Vora , Tejan Karmali , Varun Jampani , R. Venkatesh Babu

Creating 3D textured meshes using generative artificial intelligence has garnered significant attention recently. While existing methods support text-based generative texture generation or editing on 3D meshes, they often struggle to…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Yudi Zhang , Qi Xu , Lei Zhang

To represent people in mixed reality applications for collaboration and communication, we need to generate realistic and faithful avatar poses. However, the signal streams that can be applied for this task from head-mounted devices (HMDs)…

Computer Vision and Pattern Recognition · Computer Science 2022-03-14 Sadegh Aliakbarian , Pashmina Cameron , Federica Bogo , Andrew Fitzgibbon , Thomas J. Cashman

Design inspiration is crucial for establishing the direction of a design as well as evoking feelings and conveying meanings during the conceptual design process. Many practice designers use text-based searches on platforms like Pinterest to…

Human-Computer Interaction · Computer Science 2024-07-18 Ye Wang , Nicole B. Damen , Thomas Gale , Voho Seo , Hooman Shayani

Recent progress in deep generative models has led to tremendous breakthroughs in image generation. However, while existing models can synthesize photorealistic images, they lack an understanding of our underlying 3D world. We present a new…

Computer Vision and Pattern Recognition · Computer Science 2018-12-07 Jun-Yan Zhu , Zhoutong Zhang , Chengkai Zhang , Jiajun Wu , Antonio Torralba , Joshua B. Tenenbaum , William T. Freeman

3D human generation is an important problem with a wide range of applications in computer vision and graphics. Despite recent progress in generative AI such as diffusion models or rendering methods like Neural Radiance Fields or Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Maksym Ivashechkin , Oscar Mendez , Richard Bowden

Generating realistic 3D point clouds is a fundamental problem in computer vision with applications in remote sensing, robotics, and digital object modeling. Existing generative approaches primarily capture geometry, and when semantics are…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Gunner Stone , Sushmita Sarker , Alireza Tavakkoli

Diffusion-based methods have achieved remarkable achievements in 2D image or 3D object generation, however, the generation of 3D scenes and even $360^{\circ}$ images remains constrained, due to the limited number of scene datasets, the…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Weicai Ye , Chenhao Ji , Zheng Chen , Junyao Gao , Xiaoshui Huang , Song-Hai Zhang , Wanli Ouyang , Tong He , Cairong Zhao , Guofeng Zhang

Fashionable image generation aims to synthesize images of diverse fashion prevalent around the globe, helping fashion designers in real-time visualization by giving them a basic customized structure of how a specific design preference would…

Computer Vision and Pattern Recognition · Computer Science 2023-06-14 Krishna Sri Ipsit Mantri , Nevasini Sasikumar

Talking head synthesis, an advanced method for generating portrait videos from a still image driven by specific content, has garnered widespread attention in virtual reality, augmented reality and game production. Recently, significant…

Computer Vision and Pattern Recognition · Computer Science 2024-06-19 Ming Meng , Yufei Zhao , Bo Zhang , Yonggui Zhu , Weimin Shi , Maxwell Wen , Zhaoxin Fan

Generating accurate 3D models is a challenging problem that traditionally requires explicit learning from 3D datasets using supervised learning. Although recent advances have shown promise in learning 3D models from 2D images, these methods…

Computer Vision and Pattern Recognition · Computer Science 2024-02-05 Qijia Shen , Guangrun Wang