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Automatic text-to-3D generation that combines Score Distillation Sampling (SDS) with the optimization of volume rendering has achieved remarkable progress in synthesizing realistic 3D objects. Yet most existing text-to-3D methods by SDS and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Zilong Chen , Feng Wang , Yikai Wang , Huaping Liu

We present GALA3D, generative 3D GAussians with LAyout-guided control, for effective compositional text-to-3D generation. We first utilize large language models (LLMs) to generate the initial layout and introduce a layout-guided 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-06-12 Xiaoyu Zhou , Xingjian Ran , Yajiao Xiong , Jinlin He , Zhiwei Lin , Yongtao Wang , Deqing Sun , Ming-Hsuan Yang

With the onset of diffusion-based generative models and their ability to generate text-conditioned images, content generation has received a massive invigoration. Recently, these models have been shown to provide useful guidance for the…

Computer Vision and Pattern Recognition · Computer Science 2023-11-30 Alexander Vilesov , Pradyumna Chari , Achuta Kadambi

Recent advances in text-to-3D creation integrate the potent prior of Diffusion Models from text-to-image generation into 3D domain. Nevertheless, generating 3D scenes with multiple objects remains challenging. Therefore, we present…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Yueming Zhao , Xuening Yuan , Hongyu Yang , Di Huang

Text-to-3D generation represents an exciting field that has seen rapid advancements, facilitating the transformation of textual descriptions into detailed 3D models. However, current progress often neglects the intricate high-order…

Computer Vision and Pattern Recognition · Computer Science 2025-01-10 Donglin Di , Jiahui Yang , Chaofan Luo , Zhou Xue , Wei Chen , Xun Yang , Yue Gao

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

Text-to-3D content creation has recently received much attention, especially with the prevalence of 3D Gaussians Splatting. In general, GS-based methods comprise two key stages: initialization and rendering optimization. To achieve…

Computer Vision and Pattern Recognition · Computer Science 2024-08-05 Lutao Jiang , Hangyu Li , Lin Wang

Recently, 3D Gaussian splatting (3D-GS) has achieved great success in reconstructing and rendering real-world scenes. To transfer the high rendering quality to generation tasks, a series of research works attempt to generate 3D-Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-06-27 Taoran Yi , Jiemin Fang , Zanwei Zhou , Junjie Wang , Guanjun Wu , Lingxi Xie , Xiaopeng Zhang , Wenyu Liu , Xinggang Wang , Qi Tian

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

We propose VideoRFSplat, a direct text-to-3D model leveraging a video generation model to generate realistic 3D Gaussian Splatting (3DGS) for unbounded real-world scenes. To generate diverse camera poses and unbounded spatial extent of…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Hyojun Go , Byeongjun Park , Hyelin Nam , Byung-Hoon Kim , Hyungjin Chung , Changick Kim

Recent advancements in Generalizable Gaussian Splatting have enabled robust 3D reconstruction from sparse input views by utilizing feed-forward Gaussian Splatting models, achieving superior cross-scene generalization. However, while many…

Computer Vision and Pattern Recognition · Computer Science 2025-08-22 Zhicong Wu , Hongbin Xu , Gang Xu , Ping Nie , Zhixin Yan , Jinkai Zheng , Liangqiong Qu , Ming Li , Liqiang Nie

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

3D content creation has achieved significant progress in terms of both quality and speed. Although current feed-forward models can produce 3D objects in seconds, their resolution is constrained by the intensive computation required during…

Computer Vision and Pattern Recognition · Computer Science 2024-02-08 Jiaxiang Tang , Zhaoxi Chen , Xiaokang Chen , Tengfei Wang , Gang Zeng , Ziwei Liu

Text-to-3D synthesis has recently seen intriguing advances by combining the text-to-image priors with 3D representation methods, e.g., 3D Gaussian Splatting (3D GS), via Score Distillation Sampling (SDS). However, a hurdle of existing…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Lutao Jiang , Xu Zheng , Yuanhuiyi Lyu , Jiazhou Zhou , Lin Wang

We introduce Text2Immersion, an elegant method for producing high-quality 3D immersive scenes from text prompts. Our proposed pipeline initiates by progressively generating a Gaussian cloud using pre-trained 2D diffusion and depth…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Hao Ouyang , Kathryn Heal , Stephen Lombardi , Tiancheng Sun

Text-to-3D generation has shown great promise in generating novel 3D content based on given text prompts. However, existing generative methods mostly focus on geometric or visual plausibility while ignoring precise physics perception for…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Qingshan Xu , Jiao Liu , Melvin Wong , Caishun Chen , Yew-Soon Ong

Realistic 3D human generation from text prompts is a desirable yet challenging task. Existing methods optimize 3D representations like mesh or neural fields via score distillation sampling (SDS), which suffers from inadequate fine details…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Xian Liu , Xiaohang Zhan , Jiaxiang Tang , Ying Shan , Gang Zeng , Dahua Lin , Xihui Liu , Ziwei Liu

The field of text-to-3D content generation has made significant progress in generating realistic 3D objects, with existing methodologies like Score Distillation Sampling (SDS) offering promising guidance. However, these methods often…

Computer Vision and Pattern Recognition · Computer Science 2024-09-11 Phu Pham , Aradhya N. Mathur , Ojaswa Sharma , Aniket Bera

Text-to-3D, known for its efficient generation methods and expansive creative potential, has garnered significant attention in the AIGC domain. However, the pixel-wise rendering of NeRF and its ray marching light sampling constrain the…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Xinhai Li , Huaibin Wang , Kuo-Kun Tseng

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
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