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Controllable 3D scene generation has extensive applications in virtual reality and interior design, where the generated scenes should exhibit high levels of realism and controllability in terms of geometry. Scene graphs provide a suitable…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Zhifei Yang , Keyang Lu , Chao Zhang , Jiaxing Qi , Hanqi Jiang , Ruifei Ma , Shenglin Yin , Yifan Xu , Mingzhe Xing , Zhen Xiao , Jieyi Long , Guangyao Zhai

With the recent development of generative models, Text-to-3D generations have also seen significant growth, opening a door for creating video-game 3D assets from a more general public. Nonetheless, people without any professional 3D editing…

Computer Vision and Pattern Recognition · Computer Science 2024-08-12 Zhaoning Wang , Ming Li , Chen Chen

We present DreamPolisher, a novel Gaussian Splatting based method with geometric guidance, tailored to learn cross-view consistency and intricate detail from textual descriptions. While recent progress on text-to-3D generation methods have…

Computer Vision and Pattern Recognition · Computer Science 2024-03-27 Yuanze Lin , Ronald Clark , Philip Torr

As pretrained text-to-image diffusion models become increasingly powerful, recent efforts have been made to distill knowledge from these text-to-image pretrained models for optimizing a text-guided 3D model. Most of the existing methods…

Computer Vision and Pattern Recognition · Computer Science 2024-06-12 Gege Gao , Weiyang Liu , Anpei Chen , Andreas Geiger , Bernhard Schölkopf

We present TextureDreamer, a novel image-guided texture synthesis method to transfer relightable textures from a small number of input images (3 to 5) to target 3D shapes across arbitrary categories. Texture creation is a pivotal challenge…

Computer Vision and Pattern Recognition · Computer Science 2024-01-18 Yu-Ying Yeh , Jia-Bin Huang , Changil Kim , Lei Xiao , Thu Nguyen-Phuoc , Numair Khan , Cheng Zhang , Manmohan Chandraker , Carl S Marshall , Zhao Dong , Zhengqin Li

This paper introduces a pioneering 3D volumetric encoder designed for text-to-3D generation. To scale up the training data for the diffusion model, a lightweight network is developed to efficiently acquire feature volumes from multi-view…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Zhicong Tang , Shuyang Gu , Chunyu Wang , Ting Zhang , Jianmin Bao , Dong Chen , Baining Guo

Text-to-Image diffusion models have made tremendous progress over the past two years, enabling the generation of highly realistic images based on open-domain text descriptions. However, despite their success, text descriptions often…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Shihao Zhao , Dongdong Chen , Yen-Chun Chen , Jianmin Bao , Shaozhe Hao , Lu Yuan , Kwan-Yee K. Wong

Recent advances in text-driven 3D scene editing and stylization, which leverage the powerful capabilities of 2D generative models, have demonstrated promising outcomes. However, challenges remain in ensuring high-quality stylization and…

Graphics · Computer Science 2026-03-03 Haruo Fujiwara , Yusuke Mukuta , Tatsuya Harada

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

3D asset generation is getting massive amounts of attention, inspired by the recent success of text-guided 2D content creation. Existing text-to-3D methods use pretrained text-to-image diffusion models in an optimization problem or…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Lukas Höllein , Aljaž Božič , Norman Müller , David Novotny , Hung-Yu Tseng , Christian Richardt , Michael Zollhöfer , Matthias Nießner

Recent methods in text-to-3D leverage powerful pretrained diffusion models to optimize NeRF. Notably, these methods are able to produce high-quality 3D scenes without training on 3D data. Due to the open-ended nature of the task, most…

Computer Vision and Pattern Recognition · Computer Science 2024-04-18 Yuze He , Yushi Bai , Matthieu Lin , Wang Zhao , Yubin Hu , Jenny Sheng , Ran Yi , Juanzi Li , Yong-Jin Liu

We introduce MVControl, a novel neural network architecture that enhances existing pre-trained multi-view 2D diffusion models by incorporating additional input conditions, e.g. edge maps. Our approach enables the generation of controllable…

Computer Vision and Pattern Recognition · Computer Science 2023-11-29 Zhiqi Li , Yiming Chen , Lingzhe Zhao , Peidong Liu

The field of advanced text-to-image generation is witnessing the emergence of unified frameworks that integrate powerful text encoders, such as CLIP and T5, with Diffusion Transformer backbones. Although there have been efforts to control…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Liang Chen , Shuai Bai , Wenhao Chai , Weichu Xie , Haozhe Zhao , Leon Vinci , Junyang Lin , Baobao Chang

Recently, the field of text-guided 3D scene generation has garnered significant attention. High-quality generation that aligns with physical realism and high controllability is crucial for practical 3D scene applications. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Yang Zhou , Zongjin He , Qixuan Li , Chao Wang

Generating images that fit a given text description using machine learning has improved greatly with the release of technologies such as the CLIP image-text encoder model; however, current methods lack artistic control of the style of image…

Computer Vision and Pattern Recognition · Computer Science 2022-03-02 Peter Schaldenbrand , Zhixuan Liu , Jean Oh

Recent progresses in large-scale text-to-image models have yielded remarkable accomplishments, finding various applications in art domain. However, expressing unique characteristics of an artwork (e.g. brushwork, colortone, or composition)…

Computer Vision and Pattern Recognition · Computer Science 2023-12-19 Namhyuk Ahn , Junsoo Lee , Chunggi Lee , Kunhee Kim , Daesik Kim , Seung-Hun Nam , Kibeom Hong

Recently, text-to-3D generation has attracted significant attention, resulting in notable performance enhancements. Previous methods utilize end-to-end 3D generation models to initialize 3D Gaussians, multi-view diffusion models to enforce…

Computer Vision and Pattern Recognition · Computer Science 2024-07-22 Shuo Huang , Shikun Sun , Zixuan Wang , Xiaoyu Qin , Yanmin Xiong , Yuan Zhang , Pengfei Wan , Di Zhang , Jia Jia

Text-to-3D generation is to craft a 3D object according to a natural language description. This can significantly reduce the workload for manually designing 3D models and provide a more natural way of interaction for users. However, this…

Computer Vision and Pattern Recognition · Computer Science 2023-09-27 Han Yi , Zhedong Zheng , Xiangyu Xu , Tat-seng Chua

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 emergence of virtual reality has necessitated the generation of detailed and customizable 3D hand models for interaction in the virtual world. However, the current methods for 3D hand model generation are both expensive and cumbersome,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Green Rosh , Prateek Kukreja , Vishakha SR , Pawan Prasad B H