English
Related papers

Related papers: Hyper-3DG: Text-to-3D Gaussian Generation via Hype…

200 papers

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

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

Recent text-to-3D models can render high-quality assets, yet they still stumble on objects with complex attributes. The key obstacles are: (1) existing text-to-3D approaches typically lift text-to-image models to extract semantics via text…

Computer Vision and Pattern Recognition · Computer Science 2025-05-12 Yiming Qin , Zhu Xu , Yang Liu

Text-to-3D generation is a valuable technology in virtual reality and digital content creation. While recent works have pushed the boundaries of text-to-3D generation, producing high-fidelity 3D objects with inefficient prompts and…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Wenqing Wang , Yun Fu

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

In recent times, the generation of 3D assets from text prompts has shown impressive results. Both 2D and 3D diffusion models can help generate decent 3D objects based on prompts. 3D diffusion models have good 3D consistency, but their…

Computer Vision and Pattern Recognition · Computer Science 2024-05-14 Taoran Yi , Jiemin Fang , Junjie Wang , Guanjun Wu , Lingxi Xie , Xiaopeng Zhang , Wenyu Liu , Qi Tian , Xinggang Wang

Recent breakthroughs in text-guided image generation have significantly advanced the field of 3D generation. While generating a single high-quality 3D object is now feasible, generating multiple objects with reasonable interactions within a…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Chongjian Ge , Chenfeng Xu , Yuanfeng Ji , Chensheng Peng , Masayoshi Tomizuka , Ping Luo , Mingyu Ding , Varun Jampani , Wei Zhan

We present Turbo3D, an ultra-fast text-to-3D system capable of generating high-quality Gaussian splatting assets in under one second. Turbo3D employs a rapid 4-step, 4-view diffusion generator and an efficient feed-forward Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-12-06 Hanzhe Hu , Tianwei Yin , Fujun Luan , Yiwei Hu , Hao Tan , Zexiang Xu , Sai Bi , Shubham Tulsiani , Kai Zhang

Modeling and generating 3D human-object interactions from text is crucial for applications in AR, XR, and gaming. Existing approaches often rely on score distillation from text-to-image models, but their results suffer from the Janus…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Agniv Sharma , Xianghui Xie , Tom Fischer , Eddy Ilg , Gerard Pons-Moll

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

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

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

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

In recent years, 3D Gaussian splatting has emerged as a powerful technique for 3D reconstruction and generation, known for its fast and high-quality rendering capabilities. To address these shortcomings, this paper introduces a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Xianglong He , Junyi Chen , Sida Peng , Di Huang , Yangguang Li , Xiaoshui Huang , Chun Yuan , Wanli Ouyang , Tong He

Recent advances in 3D content creation mostly leverage optimization-based 3D generation via score distillation sampling (SDS). Though promising results have been exhibited, these methods often suffer from slow per-sample optimization,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Jiaxiang Tang , Jiawei Ren , Hang Zhou , Ziwei Liu , Gang Zeng

We propose L3DG, the first approach for generative 3D modeling of 3D Gaussians through a latent 3D Gaussian diffusion formulation. This enables effective generative 3D modeling, scaling to generation of entire room-scale scenes which can be…

Computer Vision and Pattern Recognition · Computer Science 2024-10-18 Barbara Roessle , Norman Müller , Lorenzo Porzi , Samuel Rota Bulò , Peter Kontschieder , Angela Dai , Matthias Nießner

To address the data scarcity associated with 3D assets, 2D-lifting techniques such as Score Distillation Sampling (SDS) have become a widely adopted practice in text-to-3D generation pipelines. However, the diffusion models used in these…

Computer Vision and Pattern Recognition · Computer Science 2025-01-23 Utkarsh Nath , Rajeev Goel , Eun Som Jeon , Changhoon Kim , Kyle Min , Yezhou Yang , Yingzhen Yang , Pavan Turaga

3D Gaussian Splatting has recently gained traction for its efficient training and real-time rendering. While its vanilla representation is mainly designed for view synthesis, recent works extended it to scene understanding with language…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Siyun Liang , Sen Wang , Kunyi Li , Michael Niemeyer , Stefano Gasperini , Hendrik P. A. Lensch , Nassir Navab , Federico Tombari

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

While text-to-3D and image-to-3D generation tasks have received considerable attention, one important but under-explored field between them is controllable text-to-3D generation, which we mainly focus on in this work. To address this task,…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Zhiqi Li , Yiming Chen , Lingzhe Zhao , Peidong Liu
‹ Prev 1 2 3 10 Next ›