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This paper presents a novel method for building scalable 3D generative models utilizing pre-trained video diffusion models. The primary obstacle in developing foundation 3D generative models is the limited availability of 3D data. Unlike…

Computer Vision and Pattern Recognition · Computer Science 2024-07-22 Junlin Han , Filippos Kokkinos , Philip Torr

The recent advancement of generative foundational models has ushered in a new era of image generation in the realm of natural images, revolutionizing art design, entertainment, environment simulation, and beyond. Despite producing…

Computer Vision and Pattern Recognition · Computer Science 2024-10-16 Zhiping Yu , Chenyang Liu , Liqin Liu , Zhenwei Shi , Zhengxia Zou

The creation of 3D human face avatars from a single unconstrained image is a fundamental task that underlies numerous real-world vision and graphics applications. Despite the significant progress made in generative models, existing methods…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Wenqing Wang , Haosen Yang , Josef Kittler , Xiatian Zhu

Generating realistic 3D indoor scenes from user inputs remains a challenging problem in computer vision and graphics, requiring careful balance of geometric consistency, spatial relationships, and visual realism. While neural generation…

Computer Vision and Pattern Recognition · Computer Science 2025-06-30 Mengqi Zhou , Xipeng Wang , Yuxi Wang , Zhaoxiang Zhang

Diffusion-based methods have achieved remarkable achievements in 2D image or 3D object generation, however, the generation of 3D scenes and even $360^{\circ}$ images remains constrained, due to the limited number of scene datasets, the…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Weicai Ye , Chenhao Ji , Zheng Chen , Junyao Gao , Xiaoshui Huang , Song-Hai Zhang , Wanli Ouyang , Tong He , Cairong Zhao , Guofeng Zhang

As several industries are moving towards modeling massive 3D virtual worlds, the need for content creation tools that can scale in terms of the quantity, quality, and diversity of 3D content is becoming evident. In our work, we aim to train…

Computer Vision and Pattern Recognition · Computer Science 2022-09-23 Jun Gao , Tianchang Shen , Zian Wang , Wenzheng Chen , Kangxue Yin , Daiqing Li , Or Litany , Zan Gojcic , Sanja Fidler

Although Multimodal Large Language Models have achieved remarkable progress, they still struggle with complex 3D spatial reasoning due to the reliance on 2D visual priors. Existing approaches typically mitigate this limitation either…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Jiahua Chen , Qihong Tang , Weinong Wang , Qi Fan

Video generative models can be regarded as world simulators due to their ability to capture dynamic, continuous changes inherent in real-world environments. These models integrate high-dimensional information across visual, temporal,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Hengyuan Cao , Yutong Feng , Biao Gong , Yijing Tian , Yunhong Lu , Chuang Liu , Bin Wang

Recent advances in 3D scene generation produce visually appealing output, but current representations hinder artists' workflows that require modifiable 3D textured mesh scenes for visual effects and game development. Despite significant…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Tobias Sautter , Jan-Niklas Dihlmann , Hendrik P. A. Lensch

This report presents a comprehensive framework for generating high-quality 3D shapes and textures from diverse input prompts, including single images, multi-view images, and text descriptions. The framework consists of 3D shape generation…

Panorama images have a much larger field-of-view thus naturally encode enriched scene context information compared to standard perspective images, which however is not well exploited in the previous scene understanding methods. In this…

Computer Vision and Pattern Recognition · Computer Science 2021-08-25 Cheng Zhang , Zhaopeng Cui , Cai Chen , Shuaicheng Liu , Bing Zeng , Hujun Bao , Yinda Zhang

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

Automatic 3D content creation seeks to replace labor-intensive modeling and scanning pipelines with systems that can synthesize or recover 3D assets directly from text or images. Its applications span video games, virtual reality, robotics,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Jiahao Li

Reconstructing 3D representations from 2D inputs is a fundamental task in computer vision and graphics, serving as a cornerstone for understanding and interacting with the physical world. While traditional methods achieve high fidelity,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-16 Weijie Wang , Qihang Cao , Sensen Gao , Donny Y. Chen , Haofei Xu , Wenjing Bian , Songyou Peng , Tat-Jen Cham , Chuanxia Zheng , Andreas Geiger , Jianfei Cai , Jia-Wang Bian , Bohan Zhuang

In this paper, we present a novel, scalable approach for constructing open set, instance-level 3D scene representations, advancing open world understanding of 3D environments. Existing methods require pre-constructed 3D scenes and face…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Rafay Mohiuddin , Sai Manoj Prakhya , Fiona Collins , Ziyuan Liu , André Borrmann

Wide-baseline panorama reconstruction has emerged as a highly effective and pivotal approach for not only achieving geometric reconstruction of the surrounding 3D environment, but also generating highly realistic and immersive novel views.…

Computer Vision and Pattern Recognition · Computer Science 2025-07-30 Jiahui Ren , Mochu Xiang , Jiajun Zhu , Yuchao Dai

Feed-forward 3D Gaussian Splatting (3DGS) has shown great promise for real-time novel view synthesis, but its application to panoramic imagery remains challenging. Existing methods often rely on multi-view cost volumes for geometric…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Qiwei Wang , Xianghui Ze , Jingyi Yu , Yujiao Shi

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

Creating immersive and playable 3D worlds from texts or images remains a fundamental challenge in computer vision and graphics. Existing world generation approaches typically fall into two categories: video-based methods that offer rich…

We introduce Vid-CamEdit, a novel framework for video camera trajectory editing, enabling the re-synthesis of monocular videos along user-defined camera paths. This task is challenging due to its ill-posed nature and the limited multi-view…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Junyoung Seo , Jisang Han , Jaewoo Jung , Siyoon Jin , Joungbin Lee , Takuya Narihira , Kazumi Fukuda , Takashi Shibuya , Donghoon Ahn , Shoukang Hu , Seungryong Kim , Yuki Mitsufuji