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The generation of 3D scenes from user-specified conditions offers a promising avenue for alleviating the production burden in 3D applications. Previous studies required significant effort to realize the desired scene, owing to limited…

Computer Vision and Pattern Recognition · Computer Science 2024-11-28 Takayuki Hara , Tatsuya Harada

Recent research has been increasingly focusing on developing 3D world models that simulate complex real-world scenarios. World models have found broad applications across various domains, including embodied AI, autonomous driving,…

Artificial Intelligence · Computer Science 2025-09-09 Yinglin Duan , Zhengxia Zou , Tongwei Gu , Wei Jia , Zhan Zhao , Luyi Xu , Xinzhu Liu , Yenan Lin , Hao Jiang , Kang Chen , Shuang Qiu

We introduce a recipe for generating immersive 3D worlds from a single image by framing the task as an in-context learning problem for 2D inpainting models. This approach requires minimal training and uses existing generative models. Our…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Katja Schwarz , Denys Rozumnyi , Samuel Rota Bulò , Lorenzo Porzi , Peter Kontschieder

Generative world models have become essential data engines for autonomous driving, yet most existing efforts focus on videos or occupancy grids, overlooking the unique LiDAR properties. Extending LiDAR generation to dynamic 4D world…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Ao Liang , Youquan Liu , Yu Yang , Dongyue Lu , Linfeng Li , Lingdong Kong , Huaici Zhao , Wei Tsang Ooi

In this work, we present a novel method for extensive multi-scale generative terrain modeling. At the core of our model is a cascade of superresolution diffusion models that can be combined to produce consistent images across multiple…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Ansh Sharma , Albert Xiao , Praneet Rathi , Rohit Kundu , Albert Zhai , Yuan Shen , Shenlong Wang

Recent advancements in object-centric text-to-3D generation have shown impressive results. However, generating complex 3D scenes remains an open challenge due to the intricate relations between objects. Moreover, existing methods are…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Yu-Hsiang Huang , Wei Wang , Sheng-Yu Huang , Yu-Chiang Frank Wang

Recent progress in driving video generation has shown significant potential for enhancing self-driving systems by providing scalable and controllable training data. Although pretrained state-of-the-art generation models, guided by 2D layout…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Yishen Ji , Ziyue Zhu , Zhenxin Zhu , Kaixin Xiong , Ming Lu , Zhiqi Li , Lijun Zhou , Haiyang Sun , Bing Wang , Tong Lu

Despite recent advancements in neural 3D reconstruction, the dependence on dense multi-view captures restricts their broader applicability. Additionally, 3D scene generation is vital for advancing embodied AI and world models, which depend…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Yuxin Zhang , Ziyu Lu , Hongbo Duan , Keyu Fan , Pengting Luo , Peiyu Zhuang , Mengyu Yang , Houde Liu

Recent developments in generative models and large-scale datasets have substantially advanced 3D world generation, facilitating a broad range of domains including spatial intelligence, embodied intelligence, and autonomous driving. While…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Hanxin Zhu , Cong Wang , Peiyan Tu , Jiayi Luo , Tianyu He , Xin Jin , Zhibo Chen

With the rapid advancement of intelligent transportation systems, text-driven image generation and editing techniques have demonstrated significant potential in providing rich, controllable visual scene data for applications such as traffic…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Feng Lv , Haoxuan Feng , Zilu Zhang , Chunlong Xia , Yanfeng Li

Constrained generative modeling is fundamental to applications such as robotic control and autonomous driving, where models must respect physical laws and safety-critical constraints. In real-world settings, these constraints rarely take…

Machine Learning · Computer Science 2026-03-10 Xiaoxuan Liang , Saeid Naderiparizi , Yunpeng Liu , Berend Zwartsenberg , Frank Wood

We present WonderZoom, a novel approach to generating 3D scenes with contents across multiple spatial scales from a single image. Existing 3D world generation models remain limited to single-scale synthesis and cannot produce coherent scene…

Computer Vision and Pattern Recognition · Computer Science 2025-12-11 Jin Cao , Hong-Xing Yu , Jiajun Wu

We address the challenge of generating 3D worlds from textual descriptions. We propose SynCity, a training- and optimization-free approach, which leverages the geometric precision of pre-trained 3D generative models and the artistic…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Paul Engstler , Aleksandar Shtedritski , Iro Laina , Christian Rupprecht , Andrea Vedaldi

Despite increasingly realistic image quality, recent 3D image generative models often operate on 3D volumes of fixed extent with limited camera motions. We investigate the task of unconditionally synthesizing unbounded nature scenes,…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Lucy Chai , Richard Tucker , Zhengqi Li , Phillip Isola , Noah Snavely

3D scene generation has garnered growing attention in recent years and has made significant progress. Generating 4D cities is more challenging than 3D scenes due to the presence of structurally complex, visually diverse objects like…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Haozhe Xie , Zhaoxi Chen , Fangzhou Hong , Ziwei Liu

In the era of deep learning, data is the critical determining factor in the performance of neural network models. Generating large datasets suffers from various difficulties such as scalability, cost efficiency and photorealism. To avoid…

Computer Vision and Pattern Recognition · Computer Science 2022-10-04 Chahat Deep Singh , Riya Kumari , Cornelia Fermüller , Nitin J. Sanket , Yiannis Aloimonos

We present Blocks2World, a novel method for 3D scene rendering and editing that leverages a two-step process: convex decomposition of images and conditioned synthesis. Our technique begins by extracting 3D parallelepipeds from various…

Computer Vision and Pattern Recognition · Computer Science 2023-07-14 Vaibhav Vavilala , Seemandhar Jain , Rahul Vasanth , Anand Bhattad , David Forsyth

Recent video foundation models demonstrate impressive visual synthesis but frequently suffer from geometric inconsistencies. While existing methods attempt to inject 3D priors via architectural modifications, they often incur high…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Weijie Wang , Xiaoxuan He , Youping Gu , Yifan Yang , Zeyu Zhang , Yefei He , Yanbo Ding , Xirui Hu , Donny Y. Chen , Zhiyuan He , Yuqing Yang , Bohan Zhuang

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 advances in text-to-3D scene generation have demonstrated significant potential to transform content creation across multiple industries. Although the research community has made impressive progress in addressing the challenges of…