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Current text recognition systems, including those for handwritten scripts and scene text, have relied heavily on image synthesis and augmentation, since it is difficult to realize real-world complexity and diversity through collecting and…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Yuanzhi Zhu , Zhaohai Li , Tianwei Wang , Mengchao He , Cong Yao

Model customization introduces new concepts to existing text-to-image models, enabling the generation of these new concepts/objects in novel contexts. However, such methods lack accurate camera view control with respect to the new object,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Nupur Kumari , Grace Su , Richard Zhang , Taesung Park , Eli Shechtman , Jun-Yan Zhu

The field of generative models has recently witnessed significant progress, with diffusion models showing remarkable performance in image generation. In light of this success, there is a growing interest in exploring the application of…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Ariel Lapid , Idan Achituve , Lior Bracha , Ethan Fetaya

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

In this paper, we tackle a new task of 3D object synthesis, where a 3D model is composited with another object category to create a novel 3D model. However, most existing text/image/3D-to-3D methods struggle to effectively integrate…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Zeren Xiong , Zikun Chen , Zedong Zhang , Xiang Li , Ying Tai , Jian Yang , Jun Li

Generating lifelike 3D humans from a single RGB image remains a challenging task in computer vision, as it requires accurate modeling of geometry, high-quality texture, and plausible unseen parts. Existing methods typically use multi-view…

Computer Vision and Pattern Recognition · Computer Science 2025-10-13 Zhibin Liu , Haoye Dong , Aviral Chharia , Hefeng Wu

Diffusion models have achieved great success in generating 2D images. However, the quality and generalizability of 3D content generation remain limited. State-of-the-art methods often require large-scale 3D assets for training, which are…

Graphics · Computer Science 2025-03-24 Jiantao Lin , Xin Yang , Meixi Chen , Yingjie Xu , Dongyu Yan , Leyi Wu , Xinli Xu , Lie XU , Shunsi Zhang , Ying-Cong Chen

Most existing cross-modal generative methods based on diffusion models use guidance to provide control over the latent space to enable conditional generation across different modalities. Such methods focus on providing guidance through…

Machine Learning · Computer Science 2023-05-31 Zizhao Hu , Mohammad Rostami

Photo-realistic and controllable 3D avatars are crucial for various applications such as virtual and mixed reality (VR/MR), telepresence, gaming, and film production. Traditional methods for avatar creation often involve time-consuming…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Keqiang Sun , Amin Jourabloo , Riddhish Bhalodia , Moustafa Meshry , Yu Rong , Zhengyu Yang , Thu Nguyen-Phuoc , Christian Haene , Jiu Xu , Sam Johnson , Hongsheng Li , Sofien Bouaziz

Diffusion probabilistic models (DPMs) have become a popular approach to conditional generation, due to their promising results and support for cross-modal synthesis. A key desideratum in conditional synthesis is to achieve high…

Computer Vision and Pattern Recognition · Computer Science 2023-02-17 Ye Zhu , Yu Wu , Kyle Olszewski , Jian Ren , Sergey Tulyakov , Yan Yan

Recent 3D human generative models have achieved remarkable progress by learning 3D-aware GANs from 2D images. However, existing 3D human generative methods model humans in a compact 1D latent space, ignoring the articulated structure and…

Computer Vision and Pattern Recognition · Computer Science 2024-07-03 Tao Hu , Fangzhou Hong , Ziwei Liu

Existing generative approaches for guided image synthesis of multi-object scenes typically rely on 2D controls in the image or text space. As a result, these methods struggle to maintain and respect consistent three-dimensional geometric…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Léopold Maillard , Tom Durand , Adrien Ramanana Rahary , Maks Ovsjanikov

We introduce a new diffusion-based approach for shape completion on 3D range scans. Compared with prior deterministic and probabilistic methods, we strike a balance between realism, multi-modality, and high fidelity. We propose DiffComplete…

Computer Vision and Pattern Recognition · Computer Science 2023-06-29 Ruihang Chu , Enze Xie , Shentong Mo , Zhenguo Li , Matthias Nießner , Chi-Wing Fu , Jiaya Jia

Layout generation aims to synthesize realistic graphic scenes consisting of elements with different attributes including category, size, position, and between-element relation. It is a crucial task for reducing the burden on heavy-duty…

Computer Vision and Pattern Recognition · Computer Science 2023-03-10 Mude Hui , Zhizheng Zhang , Xiaoyi Zhang , Wenxuan Xie , Yuwang Wang , Yan Lu

This study investigates human-computer interface generation based on diffusion models to overcome the limitations of traditional template-based design and fixed rule-driven methods. It first analyzes the key challenges of interface…

Human-Computer Interaction · Computer Science 2026-01-13 Rui Liu , Liuqingqing Yang , Runsheng Zhang , Shixiao Wang

Generating sewing patterns in garment design is receiving increasing attention due to its CG-friendly and flexible-editing nature. Previous sewing pattern generation methods have been able to produce exquisite clothing, but struggle to…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Shengqi Liu , Yuhao Cheng , Zhuo Chen , Xingyu Ren , Wenhan Zhu , Lincheng Li , Mengxiao Bi , Xiaokang Yang , Yichao Yan

Significant progress has been made in text-to-video generation through the use of powerful generative models and large-scale internet data. However, substantial challenges remain in precisely controlling individual concepts within the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Hanxin Zhu , Tianyu He , Anni Tang , Junliang Guo , Zhibo Chen , Jiang Bian

Research in vision-language models has seen rapid developments off-late, enabling natural language-based interfaces for image generation and manipulation. Many existing text guided manipulation techniques are restricted to specific classes…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Paramanand Chandramouli , Kanchana Vaishnavi Gandikota

Recent years have seen significant progress in human image generation, particularly with the advancements in diffusion models. However, existing diffusion methods encounter challenges when producing consistent hand anatomy and the generated…

Computer Vision and Pattern Recognition · Computer Science 2024-05-01 Anton Pelykh , Ozge Mercanoglu Sincan , Richard Bowden

This paper introduces a generative model designed for multimodal control over text-to-image foundation generative AI models such as Stable Diffusion, specifically tailored for engineering design synthesis. Our model proposes parametric,…

Artificial Intelligence · Computer Science 2024-12-09 Rui Zhou , Yanxia Zhang , Chenyang Yuan , Frank Permenter , Nikos Arechiga , Matt Klenk , Faez Ahmed
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