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Related papers: WonderVerse: Extendable 3D Scene Generation with V…

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Recent video generators achieve striking photorealism, yet remain fundamentally inconsistent in 3D. We present WorldReel, a 4D video generator that is natively spatio-temporally consistent. WorldReel jointly produces RGB frames together…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Shaoheng Fang , Hanwen Jiang , Yunpeng Bai , Niloy J. Mitra , Qixing Huang

We introduce a novel 3D generative method, Generative 3D Reconstruction (G3DR) in ImageNet, capable of generating diverse and high-quality 3D objects from single images, addressing the limitations of existing methods. At the heart of our…

Computer Vision and Pattern Recognition · Computer Science 2024-04-04 Pradyumna Reddy , Ismail Elezi , Jiankang Deng

Generating coherent and useful image/video scenes from a free-form textual description is technically a very difficult problem to handle. Textual description of the same scene can vary greatly from person to person, or sometimes even for…

Computer Vision and Pattern Recognition · Computer Science 2020-12-01 Faria Huq , Nafees Ahmed , Anindya Iqbal

Text-driven 3D indoor scene generation holds broad applications, ranging from gaming and smart homes to AR/VR applications. Fast and high-fidelity scene generation is paramount for ensuring user-friendly experiences. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2024-05-10 Yikun Ma , Dandan Zhan , Zhi Jin

Modeling scenes using video generation models has garnered growing research interest in recent years. However, most existing approaches rely on perspective video models that synthesize only limited observations of a scene, leading to issues…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Yuheng Liu , Xin Lin , Xinke Li , Baihan Yang , Chen Wang , Kalyan Sunkavalli , Yannick Hold-Geoffroy , Hao Tan , Kai Zhang , Xiaohui Xie , Zifan Shi , Yiwei Hu

Recent advances in diffusion models have revolutionized 2D and 3D content creation, yet generating photorealistic dynamic 4D scenes remains a significant challenge. Existing dynamic 4D generation methods typically rely on distilling…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Vinayak Gupta , Yunze Man , Yu-Xiong Wang

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

We introduce the problem of perpetual view generation - long-range generation of novel views corresponding to an arbitrarily long camera trajectory given a single image. This is a challenging problem that goes far beyond the capabilities of…

Computer Vision and Pattern Recognition · Computer Science 2021-12-02 Andrew Liu , Richard Tucker , Varun Jampani , Ameesh Makadia , Noah Snavely , Angjoo Kanazawa

This paper tackles the challenge of robust reconstruction, i.e., the task of reconstructing a 3D scene from a set of inconsistent multi-view images. Some recent works have attempted to simultaneously remove image inconsistencies and perform…

Computer Vision and Pattern Recognition · Computer Science 2025-10-06 Jin Cao , Hongrui Wu , Ziyong Feng , Hujun Bao , Xiaowei Zhou , Sida Peng

This paper presents ShareVerse, a video generation framework enabling multi-agent shared world modeling, addressing the gap in existing works that lack support for unified shared world construction with multi-agent interaction. ShareVerse…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Jiayi Zhu , Jianing Zhang , Yiying Yang , Wei Cheng , Xiaoyun Yuan

Generating high-quality textures for 3D scenes is crucial for applications in interior design, gaming, and augmented/virtual reality (AR/VR). Although recent advancements in 3D generative models have enhanced content creation, significant…

Computer Vision and Pattern Recognition · Computer Science 2025-01-27 Yunfan Zhang , Zhiwei Xiong , Zhiqi Shen , Guosheng Lin , Hao Wang , Nicolas Vun

Recent advances in 3D generation have been remarkable, with methods such as DreamFusion leveraging large-scale text-to-image diffusion-based models to guide 3D object generation. These methods enable the synthesis of detailed and…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Bohan Zeng , Shanglin Li , Yutang Feng , Ling Yang , Hong Li , Sicheng Gao , Jiaming Liu , Conghui He , Wentao Zhang , Jianzhuang Liu , Baochang Zhang , Shuicheng Yan

Diffusion models have become central to various image editing tasks, yet they often fail to fully adhere to physical laws, particularly with effects like shadows, reflections, and occlusions. In this work, we address the challenge of…

Computer Vision and Pattern Recognition · Computer Science 2025-04-23 Ankit Dhiman , Manan Shah , R Venkatesh Babu

In recent years, Generative Adversarial Networks have achieved impressive results in photorealistic image synthesis. This progress nurtures hopes that one day the classical rendering pipeline can be replaced by efficient models that are…

Computer Vision and Pattern Recognition · Computer Science 2020-03-25 Yiyi Liao , Katja Schwarz , Lars Mescheder , Andreas Geiger

Existing diffusion-based 3D scene generation methods primarily operate in 2D image/video latent spaces, which makes maintaining cross-view appearance and geometric consistency inherently challenging. To bridge this gap, we present OneWorld,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Sensen Gao , Zhaoqing Wang , Qihang Cao , Dongdong Yu , Changhu Wang , Tongliang Liu , Mingming Gong , Jiawang Bian

We present LT3SD, a novel latent diffusion model for large-scale 3D scene generation. Recent advances in diffusion models have shown impressive results in 3D object generation, but are limited in spatial extent and quality when extended to…

Computer Vision and Pattern Recognition · Computer Science 2025-05-02 Quan Meng , Lei Li , Matthias Nießner , Angela Dai

The demand for efficient 3D model generation techniques has grown exponentially, as manual creation of 3D models is time-consuming and requires specialized expertise. While generative models have shown potential in creating 3D textured…

Computer Vision and Pattern Recognition · Computer Science 2023-07-28 Fanghua Yu , Xintao Wang , Zheyuan Li , Yan-Pei Cao , Ying Shan , Chao Dong

We study the problem of synthesizing immersive 3D indoor scenes from one or more images. Our aim is to generate high-resolution images and videos from novel viewpoints, including viewpoints that extrapolate far beyond the input images while…

Computer Vision and Pattern Recognition · Computer Science 2022-12-02 Jing Yu Koh , Harsh Agrawal , Dhruv Batra , Richard Tucker , Austin Waters , Honglak Lee , Yinfei Yang , Jason Baldridge , Peter Anderson

Advancements in 3D scene reconstruction have transformed 2D images from the real world into 3D models, producing realistic 3D results from hundreds of input photos. Despite great success in dense-view reconstruction scenarios, rendering a…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Fangfu Liu , Wenqiang Sun , Hanyang Wang , Yikai Wang , Haowen Sun , Junliang Ye , Jun Zhang , Yueqi Duan

The problem of generating a perpetual dynamic scene from a single view is an important problem with widespread applications in augmented and virtual reality, and robotics. However, since dynamic scenes regularly change over time, a key…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Fengrui Tian , Tianjiao Ding , Jinqi Luo , Hancheng Min , René Vidal
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