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Related papers: Precise-Physics Driven Text-to-3D Generation

200 papers

Text-driven 3D scene generation techniques have made rapid progress in recent years. Their success is mainly attributed to using existing generative models to iteratively perform image warping and inpainting to generate 3D scenes. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Frank Zhang , Yibo Zhang , Quan Zheng , Rui Ma , Wei Hua , Hujun Bao , Weiwei Xu , Changqing Zou

3D scene generation conditioned on text prompts has significantly progressed due to the development of 2D diffusion generation models. However, the textual description of 3D scenes is inherently inaccurate and lacks fine-grained control…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Minglin Chen , Longguang Wang , Sheng Ao , Ye Zhang , Kai Xu , Yulan Guo

Existing neural rendering-based text-to-3D-portrait generation methods typically make use of human geometry prior and diffusion models to obtain guidance. However, relying solely on geometry information introduces issues such as the Janus…

Computer Vision and Pattern Recognition · Computer Science 2024-04-17 Yiqian Wu , Hao Xu , Xiangjun Tang , Xien Chen , Siyu Tang , Zhebin Zhang , Chen Li , Xiaogang Jin

Human motion generation is a significant pursuit in generative computer vision with widespread applications in film-making, video games, AR/VR, and human-robot interaction. Current methods mainly utilize either diffusion-based generative…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Canxuan Gang

We present DIRECT-3D, a diffusion-based 3D generative model for creating high-quality 3D assets (represented by Neural Radiance Fields) from text prompts. Unlike recent 3D generative models that rely on clean and well-aligned 3D data,…

Computer Vision and Pattern Recognition · Computer Science 2024-06-10 Qihao Liu , Yi Zhang , Song Bai , Adam Kortylewski , Alan Yuille

Text-guided 3D face synthesis has achieved remarkable results by leveraging text-to-image (T2I) diffusion models. However, most existing works focus solely on the direct generation, ignoring the editing, restricting them from synthesizing…

Computer Vision and Pattern Recognition · Computer Science 2023-12-04 Yunjie Wu , Yapeng Meng , Zhipeng Hu , Lincheng Li , Haoqian Wu , Kun Zhou , Weiwei Xu , Xin Yu

Although recent 3D-native generators have made great progress in synthesizing reliable geometry, they still fall short in achieving realistic appearances. A key obstacle lies in the lack of diverse and high-quality real-world 3D assets with…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Xinyue Liang , Zhinyuan Ma , Lingchen Sun , Yanjun Guo , Lei Zhang

Recently, the impressive generative capabilities of diffusion models have been demonstrated, producing images with remarkable fidelity. Particularly, existing methods for the 3D object generation tasks, which is one of the fastest-growing…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Jaeseok Lee , Jaekoo Lee

Recently, text-to-image generation has exhibited remarkable advancements, with the ability to produce visually impressive results. In contrast, text-to-3D generation has not yet reached a comparable level of quality. Existing methods…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Yukang Cao , Yan-Pei Cao , Kai Han , Ying Shan , Kwan-Yee K. Wong

Recent advancements in Text-to-3D modeling have shown significant potential for the creation of 3D content. However, due to the complex geometric shapes of objects in the natural world, generating 3D content remains a challenging task.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Huanning Dong , Fan Li , Ping Kuang , Jianwen Min

Recent advancements in 3D generation have leveraged synthetic datasets with ground truth 3D assets and predefined cameras. However, the potential of adopting real-world datasets, which can produce significantly more realistic 3D scenes,…

Computer Vision and Pattern Recognition · Computer Science 2024-06-26 Xinyang Li , Zhangyu Lai , Linning Xu , Yansong Qu , Liujuan Cao , Shengchuan Zhang , Bo Dai , Rongrong Ji

Generative models have achieved success in producing semantically plausible 2D images, but it remains challenging in 3D generation due to the absence of spatial geometry constraints. Typically, existing methods utilize geometric features as…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Haonan Wang , Hanyu Zhou , Haoyue Liu , Tao Gu , Luxin Yan

Recent advances in Gaussian Splatting have enabled fast, high-fidelity 3D scene generation, yet these methods remain purely visual and lack an understanding of how shapes behave in the physical world. We introduce Physics-Guided 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Zachary Lee , Maxwell Jacobson , Yexiang Xue

The recent availability and adaptability of text-to-image models has sparked a new era in many related domains that benefit from the learned text priors as well as high-quality and fast generation capabilities, one of which is texture…

Computer Vision and Pattern Recognition · Computer Science 2024-07-03 Raphael Bensadoun , Yanir Kleiman , Idan Azuri , Omri Harosh , Andrea Vedaldi , Natalia Neverova , Oran Gafni

Distilling 3D representations from pretrained 2D diffusion models is essential for 3D creative applications across gaming, film, and interior design. Current SDS-based methods are hindered by inefficient information distillation from…

Computer Vision and Pattern Recognition · Computer Science 2025-03-13 Haoran Li , Yuli Tian , Yonghui Wang , Yong Liao , Lin Wang , Yuyang Wang , Peng Yuan Zhou

The generation of industrial Computer-Aided Design (CAD) models from user requests and specifications is crucial to enhancing efficiency in modern manufacturing. Traditional methods of CAD generation rely heavily on manual inputs and…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Mohsen Yavartanoo , Sangmin Hong , Reyhaneh Neshatavar , Kyoung Mu Lee

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

Synthetic polymeric materials underpin fundamental technologies in the energy, electronics, consumer goods, and medical sectors, yet their development still suffers from prolonged design timelines. Although polymer informatics tools have…

Computational Engineering, Finance, and Science · Computer Science 2025-06-12 Ayush Jain , Rampi Ramprasad

Recent advancements in diffusion techniques have propelled image and video generation to unprecedented levels of quality, significantly accelerating the deployment and application of generative AI. However, 3D shape generation technology…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Yangguang Li , Zi-Xin Zou , Zexiang Liu , Dehu Wang , Yuan Liang , Zhipeng Yu , Xingchao Liu , Yuan-Chen Guo , Ding Liang , Wanli Ouyang , Yan-Pei Cao

Automatic 3D content creation has achieved rapid progress recently due to the availability of pre-trained, large language models and image diffusion models, forming the emerging topic of text-to-3D content creation. Existing text-to-3D…

Computer Vision and Pattern Recognition · Computer Science 2023-09-28 Rui Chen , Yongwei Chen , Ningxin Jiao , Kui Jia