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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

In this paper, we propose Extend3D, a training-free pipeline for 3D scene generation from a single image, built upon an object-centric 3D generative model. To overcome the limitations of fixed-size latent spaces in object-centric models for…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Seungwoo Yoon , Jinmo Kim , Jaesik Park

Text-to-3D generation has achieved remarkable progress in recent years, yet evaluating these methods remains challenging for two reasons: i) Existing benchmarks lack fine-grained evaluation on different prompt categories and evaluation…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Yujie Zhang , Bingyang Cui , Qi Yang , Zhu Li , Yiling Xu

Personalized text-to-image generation aims to create images tailored to user-defined concepts and textual descriptions. Balancing the fidelity of the learned concept with its ability for generation in various contexts presents a significant…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Vera Soboleva , Maksim Nakhodnov , Aibek Alanov

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-driven 3D indoor scene generation is useful for gaming, the film industry, and AR/VR applications. However, existing methods cannot faithfully capture the room layout, nor do they allow flexible editing of individual objects in the…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Chuan Fang , Yuan Dong , Kunming Luo , Xiaotao Hu , Rakesh Shrestha , Ping Tan

Large Language Models(LLMs) have revolutionized text generation and multimodal perception,but their capabilities in 3D content generation remain underexplored. Existing methods compromise by producing either low-resolution meshes or coarse…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Junming Huang , Chi Wang , Letian Li , Guangkai Xu , Donglin Huang , Hao Chen , Qiang Dai , Weiwei Xu

Auto-regressive text generation models usually focus on local fluency, and may cause inconsistent semantic meaning in long text generation. Further, automatically generating words with similar semantics is challenging, and hand-crafted…

Computation and Language · Computer Science 2020-05-05 Ruiyi Zhang , Changyou Chen , Zhe Gan , Wenlin Wang , Dinghan Shen , Guoyin Wang , Zheng Wen , Lawrence Carin

We propose a high-quality 3D-to-3D conversion method, Instruct 3D-to-3D. Our method is designed for a novel task, which is to convert a given 3D scene to another scene according to text instructions. Instruct 3D-to-3D applies pretrained…

Computer Vision and Pattern Recognition · Computer Science 2023-03-29 Hiromichi Kamata , Yuiko Sakuma , Akio Hayakawa , Masato Ishii , Takuya Narihira

Although existing text-to-motion (T2M) methods can produce realistic human motion from text description, it is still difficult to align the generated motion with the desired postures since using text alone is insufficient for precisely…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Ling-An Zeng , Gaojie Wu , Ancong Wu , Jian-Fang Hu , Wei-Shi Zheng

While recent generative models for 2D images achieve impressive visual results, they clearly lack the ability to perform 3D reasoning. This heavily restricts the degree of control over generated objects as well as the possible applications…

Computer Vision and Pattern Recognition · Computer Science 2020-10-26 Dario Pavllo , Graham Spinks , Thomas Hofmann , Marie-Francine Moens , Aurelien Lucchi

We introduce WorldGen, a system that enables the automatic creation of large-scale, interactive 3D worlds directly from text prompts. Our approach transforms natural language descriptions into traversable, fully textured environments that…

Recent progress in text-to-3D generation has been achieved through the utilization of score distillation methods: they make use of the pre-trained text-to-image (T2I) diffusion models by distilling via the diffusion model training…

Computer Vision and Pattern Recognition · Computer Science 2024-03-25 Kyungmin Lee , Kihyuk Sohn , Jinwoo Shin

2D concept art generation for 3D scenes is a crucial yet challenging task in computer graphics, as creating natural intuitive environments still demands extensive manual effort in concept design. While generative AI has simplified 2D…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Zhenhong Sun , Yifu Wang , Yonhon Ng , Yongzhi Xu , Daoyi Dong , Hongdong Li , Pan Ji

Generic generation and manipulation of text is challenging and has limited success compared to recent deep generative modeling in visual domain. This paper aims at generating plausible natural language sentences, whose attributes are…

Machine Learning · Computer Science 2018-09-14 Zhiting Hu , Zichao Yang , Xiaodan Liang , Ruslan Salakhutdinov , Eric P. Xing

Creating 3D assets from single-view images is a complex task that demands a deep understanding of the world. Recently, feed-forward 3D generative models have made significant progress by training large reconstruction models on extensive 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Wenqiang Sun , Zhengyi Wang , Shuo Chen , Yikai Wang , Zilong Chen , Jun Zhu , Jun Zhang

The recent advances in text and image synthesis show a great promise for the future of generative models in creative fields. However, a less explored area is the one of 3D model generation, with a lot of potential applications to game…

Computer Vision and Pattern Recognition · Computer Science 2023-12-14 Antoine Schnepf , Flavian Vasile , Ugo Tanielian

This paper addresses the task of 3D clothed human generation from textural descriptions. Previous works usually encode the human body and clothes as a holistic model and generate the whole model in a single-stage optimization, which makes…

Computer Vision and Pattern Recognition · Computer Science 2024-04-26 Junting Dong , Qi Fang , Zehuan Huang , Xudong Xu , Jingbo Wang , Sida Peng , Bo Dai

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

This paper presents a systematic survey on recent development of neural text generation models. Specifically, we start from recurrent neural network language models with the traditional maximum likelihood estimation training scheme and…

Computation and Language · Computer Science 2018-03-21 Sidi Lu , Yaoming Zhu , Weinan Zhang , Jun Wang , Yong Yu
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