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Related papers: Sat3DGen: Comprehensive Street-Level 3D Scene Gene…

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Directly generating scenes from satellite imagery offers exciting possibilities for integration into applications like games and map services. However, challenges arise from significant view changes and scene scale. Previous efforts mainly…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Zuoyue Li , Zhenqiang Li , Zhaopeng Cui , Marc Pollefeys , Martin R. Oswald

In recent years, 3D generation has made great strides in both academia and industry. However, generating 3D scenes from a single RGB image remains a significant challenge, as current approaches often struggle to ensure both object…

Graphics · Computer Science 2026-02-18 Xiang Tang , Ruotong Li , Xiaopeng Fan

With the growing demand for high-fidelity 3D models from 2D images, existing methods still face significant challenges in accurately reproducing fine-grained geometric details due to limitations in domain gaps and inherent ambiguities in…

Graphics · Computer Science 2025-04-01 Chongjie Ye , Yushuang Wu , Ziteng Lu , Jiahao Chang , Xiaoyang Guo , Jiaqing Zhou , Hao Zhao , Xiaoguang Han

We introduce a new generative approach for synthesizing 3D geometry and images from single-view collections. Most existing approaches predict volumetric density to render multi-view consistent images. By employing volumetric rendering using…

Computer Vision and Pattern Recognition · Computer Science 2024-06-17 Salvatore Esposito , Qingshan Xu , Kacper Kania , Charlie Hewitt , Octave Mariotti , Lohit Petikam , Julien Valentin , Arno Onken , Oisin Mac Aodha

Recent advancements in generative models have enabled 3D urban scene generation from satellite imagery, unlocking promising applications in gaming, digital twins, and beyond. However, most existing methods rely heavily on neural rendering…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Tongyan Hua , Lutao Jiang , Ying-Cong Chen , Wufan Zhao

We present SatSkylines, a 3D building generation approach that takes satellite imagery and coarse geometric priors. Without proper geometric guidance, existing image-based 3D generation methods struggle to recover accurate building…

Computer Vision and Pattern Recognition · Computer Science 2025-08-27 Zhangyu Jin , Andrew Feng

City-scale 3D reconstruction from satellite imagery presents the challenge of extreme viewpoint extrapolation, where our goal is to synthesize ground-level novel views from sparse orbital images with minimal parallax. This requires…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Fei Yu , Yu Liu , Luyang Tang , Mingchao Sun , Zengye Ge , Rui Bu , Yuchao Jin , Haisen Zhao , He Sun , Yangyan Li , Mu Xu , Wenzheng Chen , Baoquan Chen

We present a novel method for synthesizing both temporally and geometrically consistent street-view panoramic video from a single satellite image and camera trajectory. Existing cross-view synthesis approaches focus on images, while video…

Computer Vision and Pattern Recognition · Computer Science 2021-05-11 Zuoyue Li , Zhenqiang Li , Zhaopeng Cui , Rongjun Qin , Marc Pollefeys , Martin R. Oswald

This paper aims to develop an accurate 3D geometry representation of satellite images using satellite-ground image pairs. Our focus is on the challenging problem of 3D-aware ground-views synthesis from a satellite image. We draw inspiration…

Computer Vision and Pattern Recognition · Computer Science 2023-08-30 Ming Qian , Jincheng Xiong , Gui-Song Xia , Nan Xue

In this paper, we propose VideoFrom3D, a novel framework for synthesizing high-quality 3D scene videos from coarse geometry, a camera trajectory, and a reference image. Our approach streamlines the 3D graphic design workflow, enabling…

Graphics · Computer Science 2025-09-23 Geonung Kim , Janghyeok Han , Sunghyun Cho

Synthesizing large-scale, explorable, and geometrically accurate 3D urban scenes is a challenging yet valuable task for immersive and embodied applications. The challenge lies in the lack of large-scale and high-quality real-world 3D scans…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Jie-Ying Lee , Yi-Ruei Liu , Shr-Ruei Tsai , Wei-Cheng Chang , Chung-Ho Wu , Jiewen Chan , Zhenjun Zhao , Chieh Hubert Lin , Yu-Lun Liu

Recent advances in generative modeling have substantially enhanced 3D urban generation, enabling applications in digital twins, virtual cities, and large-scale simulations. However, existing methods face two key challenges: (1) the need for…

Computer Vision and Pattern Recognition · Computer Science 2025-11-17 Yijie Kang , Xinliang Wang , Zhenyu Wu , Yifeng Shi , Hailong Zhu

3D-aware GANs aim to synthesize realistic 3D scenes such that they can be rendered in arbitrary perspectives to produce images. Although previous methods produce realistic images, they suffer from unstable training or degenerate solutions…

Computer Vision and Pattern Recognition · Computer Science 2023-11-13 Minjung Shin , Yunji Seo , Jeongmin Bae , Young Sun Choi , Hyunsu Kim , Hyeran Byun , Youngjung Uh

Large-scale scene data is essential for training and testing in robot learning. Neural reconstruction methods have promised the capability of reconstructing large physically-grounded outdoor scenes from captured sensor data. However, these…

Computer Vision and Pattern Recognition · Computer Science 2025-08-27 Julian Ost , Andrea Ramazzina , Amogh Joshi , Maximilian Bömer , Mario Bijelic , Felix Heide

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

We present GuidedSceneGen, a text-to-3D generation framework that produces metrically accurate, globally consistent, and semantically interpretable indoor scenes. Unlike prior text-driven methods that often suffer from geometric drift or…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Stefan Ainetter , Thomas Deixelberger , Edoardo A. Dominici , Philipp Drescher , Konstantinos Vardis , Markus Steinberger

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

We introduce a high resolution, 3D-consistent image and shape generation technique which we call StyleSDF. Our method is trained on single-view RGB data only, and stands on the shoulders of StyleGAN2 for image generation, while solving two…

Computer Vision and Pattern Recognition · Computer Science 2022-03-31 Roy Or-El , Xuan Luo , Mengyi Shan , Eli Shechtman , Jeong Joon Park , Ira Kemelmacher-Shlizerman

Previous works leveraging video models for image-to-3D scene generation tend to suffer from geometric distortions and blurry content. In this paper, we renovate the pipeline of image-to-3D scene generation by unlocking the potential of…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Yuhao Wan , Lijuan Liu , Jingzhi Zhou , Zihan Zhou , Xuying Zhang , Dongbo Zhang , Shaohui Jiao , Qibin Hou , Ming-Ming Cheng

3D scene generation is a core technology for gaming, film/VFX, and VR/AR. Growing demand for rapid iteration, high-fidelity detail, and accessible content creation has further increased interest in this area. Existing methods broadly follow…

Computer Vision and Pattern Recognition · Computer Science 2026-01-29 Haozhi Zhu , Miaomiao Zhao , Dingyao Liu , Runze Tian , Yan Zhang , Jie Guo , Fenggen Yu
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