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3D content creation from a single image is a long-standing yet highly desirable task. Recent advances introduce 2D diffusion priors, yielding reasonable results. However, existing methods are not hyper-realistic enough for post-generation…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Tong Wu , Zhibing Li , Shuai Yang , Pan Zhang , Xinggang Pan , Jiaqi Wang , Dahua Lin , Ziwei Liu

While generative models such as text-to-image, large language models and text-to-video have seen significant progress, the extension to text-to-virtual-reality remains largely unexplored, due to a deficit in training data and the complexity…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Vriksha Srihari , R. Bhavya , Shruti Jayaraman , V. Mary Anita Rajam

Producing long, coherent video sequences with stable 3D structure remains a major challenge, particularly in streaming scenarios. Motivated by this, we introduce Endless World, a real-time framework for infinite, 3D-consistent video…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Ke Zhang , Yiqun Mei , Jiacong Xu , Vishal M. Patel

We present DreamWaltz, a novel framework for generating and animating complex 3D avatars given text guidance and parametric human body prior. While recent methods have shown encouraging results for text-to-3D generation of common objects,…

Computer Vision and Pattern Recognition · Computer Science 2023-11-07 Yukun Huang , Jianan Wang , Ailing Zeng , He Cao , Xianbiao Qi , Yukai Shi , Zheng-Jun Zha , Lei Zhang

World engines aim to synthesize long, 3D-consistent videos that support interactive exploration of a scene under user-controlled camera motion. However, existing systems struggle under aggressive 6-DoF trajectories and complex outdoor…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Yu-Cheng Chou , Xingrui Wang , Yitong Li , Jiahao Wang , Hanting Liu , Cihang Xie , Alan Yuille , Junfei Xiao

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

Recent text-to-scene generation approaches largely reduced the manual efforts required to create 3D scenes. However, their focus is either to generate a scene layout or to generate objects, and few generate both. The generated scene layout…

Computer Vision and Pattern Recognition · Computer Science 2026-04-30 Zhenggang Tang , Yuehao Wang , Yuchen Fan , Jun-Kun Chen , Yu-Ying Yeh , Kihyuk Sohn , Zhangyang Wang , Qixing Huang , Alexander Schwing , Rakesh Ranjan , Dilin Wang , Zhicheng Yan

Understanding the geometric relationships between objects in a scene is a core capability in enabling both humans and autonomous agents to navigate in new environments. A sparse, unified representation of the scene topology will allow…

Computer Vision and Pattern Recognition · Computer Science 2022-05-18 Zachary Seymour , Niluthpol Chowdhury Mithun , Han-Pang Chiu , Supun Samarasekera , Rakesh Kumar

This paper addresses the challenge of learning semantically and functionally meaningful 3D motion priors from real-world videos, in order to enable prediction of future 3D scene motion from a single input image. We propose a novel…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Jiahui Lei , Kyle Genova , George Kopanas , Noah Snavely , Leonidas Guibas

World models serve as essential building blocks toward Artificial General Intelligence (AGI), enabling intelligent agents to predict future states and plan actions by simulating complex physical interactions. However, existing interactive…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Junyi Chen , Haoyi Zhu , Xianglong He , Yifan Wang , Jianjun Zhou , Wenzheng Chang , Yang Zhou , Zizun Li , Zhoujie Fu , Jiangmiao Pang , Tong He

Emerging world models autoregressively generate video frames in response to actions, such as camera movements and text prompts, among other control signals. Due to limited temporal context window sizes, these models often struggle to…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Tong Wu , Shuai Yang , Ryan Po , Yinghao Xu , Ziwei Liu , Dahua Lin , Gordon Wetzstein

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

Low-dimensional visualizations, or "projection maps," are widely used in scientific and creative domains to interpret large-scale and complex datasets. These visualizations not only aid in understanding existing knowledge spaces but also…

Artificial Intelligence · Computer Science 2025-05-16 Xingjian Zhang , Ziyang Xiong , Shixuan Liu , Yutong Xie , Tolga Ergen , Dongsub Shim , Hua Xu , Honglak Lee , Qiaozhu Me

Text-to-3D scene generation holds immense potential for the gaming, film, and architecture sectors. Despite significant progress, existing methods struggle with maintaining high quality, consistency, and editing flexibility. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-22 Haoran Li , Haolin Shi , Wenli Zhang , Wenjun Wu , Yong Liao , Lin Wang , Lik-hang Lee , Pengyuan Zhou

Generative video editing has enabled several intuitive editing operations for short video clips that would previously have been difficult to achieve, especially for non-expert editors. Existing methods focus on prescribing an object's 3D or…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Kiran Chhatre , Hyeonho Jeong , Yulia Gryaditskaya , Christopher E. Peters , Chun-Hao Paul Huang , Paul Guerrero

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

The generation of sounding videos has seen significant advancements with the advent of diffusion models. However, existing methods often lack the fine-grained control needed to generate viewpoint-specific content from larger, immersive…

3D Content Generation is at the heart of many computer graphics applications, including video gaming, film-making, virtual and augmented reality, etc. This paper proposes a novel deep-learning based approach for automatically generating…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Yongzhi Xu , Yonhon Ng , Yifu Wang , Inkyu Sa , Yunfei Duan , Zhenhong Sun , Yang Li , Pan Ji , Hongdong Li

We introduce HY-World 2.0, a multi-modal world model framework that advances our prior project HY-World 1.0. HY-World 2.0 accommodates diverse input modalities, including text prompts, single-view images, multi-view images, and videos, and…

Automatic 3D generation has recently attracted widespread attention. Recent methods have greatly accelerated the generation speed, but usually produce less-detailed objects due to limited model capacity or 3D data. Motivated by recent…

Computer Vision and Pattern Recognition · Computer Science 2024-03-12 Zilong Chen , Yikai Wang , Feng Wang , Zhengyi Wang , Huaping Liu