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Related papers: Matrix-3D: Omnidirectional Explorable 3D World Gen…

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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

Synthesizing realistic Martian landscape videos is crucial for mission rehearsal and robotic simulation. However, this task poses unique challenges due to the scarcity of high-quality Martian data and the significant domain gap between…

Computer Vision and Pattern Recognition · Computer Science 2025-12-08 Longfei Li , Zhiwen Fan , Wenyan Cong , Xinhang Liu , Yuyang Yin , Matt Foutter , Panwang Pan , Chenyu You , Yue Wang , Zhangyang Wang , Yao Zhao , Marco Pavone , Yunchao Wei

With the rapid advancement and widespread adoption of VR/AR technologies, there is a growing demand for the creation of high-quality, immersive dynamic scenes. However, existing generation works predominantly concentrate on the creation of…

Computer Vision and Pattern Recognition · Computer Science 2025-08-22 Ke Xing , Hanwen Liang , Dejia Xu , Yuyang Yin , Konstantinos N. Plataniotis , Yao Zhao , Yunchao Wei

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…

Generating immersive 360{\deg} indoor panoramas from 2D top-down views has applications in virtual reality, interior design, real estate, and robotics. This task is challenging due to the lack of explicit 3D structure and the need for…

Computer Vision and Pattern Recognition · Computer Science 2025-07-30 Zitong Zhang , Suranjan Gautam , Rui Yu

Realistic reconstruction of dynamic 4D scenes from monocular videos is essential for understanding the physical world. Despite recent progress in neural rendering, existing methods often struggle to recover accurate 3D geometry and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Haoran Zhou , Gim Hee Lee

We propose a method for generating fly-through videos of a scene, from a single image and a given camera trajectory. We build upon an image-to-video latent diffusion model. We condition its UNet denoiser on the camera trajectory, using four…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Stefan Popov , Amit Raj , Michael Krainin , Yuanzhen Li , William T. Freeman , Michael Rubinstein

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

3D data that contains rich geometry information of objects and scenes is valuable for understanding 3D physical world. With the recent emergence of large-scale 3D datasets, it becomes increasingly crucial to have a powerful 3D generative…

Computer Vision and Pattern Recognition · Computer Science 2020-12-29 Jianwen Xie , Zilong Zheng , Ruiqi Gao , Wenguan Wang , Song-Chun Zhu , Ying Nian Wu

Recent multimodal large language models have achieved strong performance in unified text and image understanding and generation, yet extending such native capability to 3D remains challenging due to limited data. Compared to abundant 2D…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Chongjie Ye , Cheng Cao , Chuanyu Pan , Yiming Hao , Yihao Zhi , Yuanming Hu , Xiaoguang Han

This paper presents Matrix, an advanced AI-powered framework designed for real-time 3D object generation in Augmented Reality (AR) environments. By integrating a cutting-edge text-to-3D generative AI model, multilingual speech-to-text…

Human-Computer Interaction · Computer Science 2025-03-24 Majid Behravan , Denis Gracanin

We introduce GAUDI, a generative model capable of capturing the distribution of complex and realistic 3D scenes that can be rendered immersively from a moving camera. We tackle this challenging problem with a scalable yet powerful approach,…

Recent breakthroughs in 3D generation have enabled the synthesis of high-fidelity individual assets. However, generating 3D compositional objects from single images--particularly under occlusions--remains challenging. Existing methods often…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Hui Shan , Keyang Luo , Ming Li , Sizhe Zheng , Yanwei Fu , Zhen Chen , Xiangru Huang

In the current era of generative AI breakthroughs, generating panoramic scenes from a single input image remains a key challenge. Most existing methods use diffusion-based iterative or simultaneous multi-view inpainting. However, the lack…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Zhipeng Cai , Matthias Mueller , Reiner Birkl , Diana Wofk , Shao-Yen Tseng , JunDa Cheng , Gabriela Ben-Melech Stan , Vasudev Lal , Michael Paulitsch

Text-driven 3D scene generation has seen significant advancements recently. However, most existing methods generate single-view images using generative models and then stitch them together in 3D space. This independent generation for each…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Wenrui Li , Fucheng Cai , Yapeng Mi , Zhe Yang , Wangmeng Zuo , Xingtao Wang , Xiaopeng Fan

Recently, multi-view diffusion-based 3D generation methods have gained significant attention. However, these methods often suffer from shape and texture misalignment across generated multi-view images, leading to low-quality 3D generation…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Zhuojiang Cai , Yiheng Zhang , Meitong Guo , Mingdao Wang , Yuwang Wang

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

Generative reconstruction methods compute the 3D configuration (such as pose and/or geometry) of a shape by optimizing the overlap of the projected 3D shape model with images. Proper handling of occlusions is a big challenge, since the…

Computer Vision and Pattern Recognition · Computer Science 2016-02-12 Helge Rhodin , Nadia Robertini , Christian Richardt , Hans-Peter Seidel , Christian Theobalt

In this work, we present CineMaster, a novel framework for 3D-aware and controllable text-to-video generation. Our goal is to empower users with comparable controllability as professional film directors: precise placement of objects within…

Computer Vision and Pattern Recognition · Computer Science 2025-02-13 Qinghe Wang , Yawen Luo , Xiaoyu Shi , Xu Jia , Huchuan Lu , Tianfan Xue , Xintao Wang , Pengfei Wan , Di Zhang , Kun Gai

Interactive 3D scene generation from a single image has gained significant attention due to its potential to create immersive virtual worlds. However, a key challenge in current 3D generation methods is the limited explorability, which…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Chaojun Ni , Jie Li , Haoyun Li , Hengyu Liu , Xiaofeng Wang , Zheng Zhu , Guosheng Zhao , Boyuan Wang , Chenxin Li , Guan Huang , Wenjun Mei