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Modern learning-based approaches to 3D-aware image synthesis achieve high photorealism and 3D-consistent viewpoint changes for the generated images. Existing approaches represent instances in a shared canonical space. However, for…

Computer Vision and Pattern Recognition · Computer Science 2024-04-15 Katja Schwarz , Seung Wook Kim , Jun Gao , Sanja Fidler , Andreas Geiger , Karsten Kreis

Previous works leveraging video models for image-to-3D scene generation tend to suffer from geometric distortions and blurry content. In this paper, we renovate the pipeline of image-to-3D scene generation by unlocking the potential of…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Yuhao Wan , Lijuan Liu , Jingzhi Zhou , Zihan Zhou , Xuying Zhang , Dongbo Zhang , Shaohui Jiao , Qibin Hou , Ming-Ming Cheng

Despite the availability of large-scale 3D datasets and advancements in 3D generative models, the complexity and uneven quality of 3D geometry and texture data continue to hinder the performance of 3D generation techniques. In most existing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-29 Xin Yang , Jiantao Lin , Yingjie Xu , Haodong Li , Yingcong Chen

Surface topography refers to the geometric micro-structure of a surface and defines its tactile characteristics (typically in the sub-millimeter range). High-resolution 3D scanning techniques developed recently enable the 3D reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2015-05-07 Matthias Zeppelzauer , Markus Seidl

Recent progress in text-to-3D object generation enables the synthesis of detailed geometry from text input by leveraging 2D diffusion models and differentiable 3D representations. However, the approaches often suffer from limited…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Ming He , Zhixiang Chen , Steve Maddock

The lack of spatial dimensional information remains a challenge in normal estimation from a single image. Recent diffusion-based methods have demonstrated significant potential in 2D-to-3D implicit mapping, they rely on data-driven…

Computer Vision and Pattern Recognition · Computer Science 2025-08-11 Yanxing Liang , Yinghui Wang , Jinlong Yang , Wei Li

Directly generating scenes from satellite imagery offers exciting possibilities for integration into applications like games and map services. However, challenges arise from significant view changes and scene scale. Previous efforts mainly…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Zuoyue Li , Zhenqiang Li , Zhaopeng Cui , Marc Pollefeys , Martin R. Oswald

Articulated object generation has seen increasing advancements, yet existing models often lack the ability to be conditioned on text prompts. To address the significant gap between textual descriptions and 3D articulated object…

Computer Vision and Pattern Recognition · Computer Science 2025-12-04 Hao Sun , Lei Fan , Donglin Di , Shaohui Liu

Recent advancements in 3D object generation using diffusion models have achieved remarkable success, but generating realistic 3D urban scenes remains challenging. Existing methods relying solely on 3D diffusion models tend to suffer a…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Hanlei Guo , Jiahao Shao , Xinya Chen , Xiyang Tan , Sheng Miao , Yujun Shen , Yiyi Liao

Recently, diffusion models have achieved great success in image synthesis. However, when it comes to the layout-to-image generation where an image often has a complex scene of multiple objects, how to make strong control over both the…

Computer Vision and Pattern Recognition · Computer Science 2024-03-13 Guangcong Zheng , Xianpan Zhou , Xuewei Li , Zhongang Qi , Ying Shan , Xi Li

The recent advancements in image-text diffusion models have stimulated research interest in large-scale 3D generative models. Nevertheless, the limited availability of diverse 3D resources presents significant challenges to learning. In…

Computer Vision and Pattern Recognition · Computer Science 2023-06-01 Chi Zhang , Yiwen Chen , Yijun Fu , Zhenglin Zhou , Gang YU , Billzb Wang , Bin Fu , Tao Chen , Guosheng Lin , Chunhua Shen

Human motion modeling is important for many modern graphics applications, which typically require professional skills. In order to remove the skill barriers for laymen, recent motion generation methods can directly generate human motions…

Computer Vision and Pattern Recognition · Computer Science 2022-09-01 Mingyuan Zhang , Zhongang Cai , Liang Pan , Fangzhou Hong , Xinying Guo , Lei Yang , Ziwei Liu

Garment sewing patterns are fundamental design elements that bridge the gap between design concepts and practical manufacturing. The generative modeling of sewing patterns is crucial for creating diversified garments. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Xinyu Li , Qi Yao , Yuanda Wang

Text-to-3D is an emerging task that allows users to create 3D content with infinite possibilities. Existing works tackle the problem by optimizing a 3D representation with guidance from pre-trained diffusion models. An apparent drawback is…

Computer Vision and Pattern Recognition · Computer Science 2023-06-06 Yiji Cheng , Fei Yin , Xiaoke Huang , Xintong Yu , Jiaxiang Liu , Shikun Feng , Yujiu Yang , Yansong Tang

3D hand-object interaction data is scarce due to the hardware constraints in scaling up the data collection process. In this paper, we propose HOIDiffusion for generating realistic and diverse 3D hand-object interaction data. Our model is a…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Mengqi Zhang , Yang Fu , Zheng Ding , Sifei Liu , Zhuowen Tu , Xiaolong Wang

Diffusion-based generative models have shown promise in synthesizing histopathology images to address data scarcity caused by privacy constraints. Diagnostic text reports provide high-level semantic descriptions, and masks offer…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Mahesh Bhosale , Abdul Wasi , Yuanhao Zhai , Yunjie Tian , Samuel Border , Nan Xi , Pinaki Sarder , Junsong Yuan , David Doermann , Xuan Gong

This survey reviews the progress of diffusion models in generating images from text, ~\textit{i.e.} text-to-image diffusion models. As a self-contained work, this survey starts with a brief introduction of how diffusion models work for…

Computer Vision and Pattern Recognition · Computer Science 2024-11-11 Chenshuang Zhang , Chaoning Zhang , Mengchun Zhang , In So Kweon , Junmo Kim

Diffusion models (DMs) excel in photo-realistic image synthesis, but their adaptation to LiDAR scene generation poses a substantial hurdle. This is primarily because DMs operating in the point space struggle to preserve the curve-like…

Computer Vision and Pattern Recognition · Computer Science 2024-04-22 Haoxi Ran , Vitor Guizilini , Yue Wang

Text-to-image generation models have achieved remarkable capabilities in synthesizing images, but often struggle to provide fine-grained control over the output. Existing guidance approaches, such as segmentation maps and depth maps,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Sangmin Jung , Utkarsh Nath , Yezhou Yang , Giulia Pedrielli , Joydeep Biswas , Amy Zhang , Hassan Ghasemzadeh , Pavan Turaga

Recent 3D large reconstruction models typically employ a two-stage process, including first generate multi-view images by a multi-view diffusion model, and then utilize a feed-forward model to reconstruct images to 3D content.However,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Zhenyu Tang , Junwu Zhang , Xinhua Cheng , Wangbo Yu , Chaoran Feng , Yatian Pang , Bin Lin , Li Yuan